4 This chapter documents the statistical procedures that @pspp{} supports so
8 * DESCRIPTIVES:: Descriptive statistics.
9 * FREQUENCIES:: Frequency tables.
10 * EXAMINE:: Testing data for normality.
12 * CORRELATIONS:: Correlation tables.
13 * CROSSTABS:: Crosstabulation tables.
14 * FACTOR:: Factor analysis and Principal Components analysis.
15 * GLM:: Univariate Linear Models.
16 * LOGISTIC REGRESSION:: Bivariate Logistic Regression.
17 * MEANS:: Average values and other statistics.
18 * NPAR TESTS:: Nonparametric tests.
19 * T-TEST:: Test hypotheses about means.
20 * ONEWAY:: One way analysis of variance.
21 * QUICK CLUSTER:: K-Means clustering.
22 * RANK:: Compute rank scores.
23 * REGRESSION:: Linear regression.
24 * RELIABILITY:: Reliability analysis.
25 * ROC:: Receiver Operating Characteristic.
34 /VARIABLES=@var{var_list}
35 /MISSING=@{VARIABLE,LISTWISE@} @{INCLUDE,NOINCLUDE@}
36 /FORMAT=@{LABELS,NOLABELS@} @{NOINDEX,INDEX@} @{LINE,SERIAL@}
38 /STATISTICS=@{ALL,MEAN,SEMEAN,STDDEV,VARIANCE,KURTOSIS,
39 SKEWNESS,RANGE,MINIMUM,MAXIMUM,SUM,DEFAULT,
40 SESKEWNESS,SEKURTOSIS@}
41 /SORT=@{NONE,MEAN,SEMEAN,STDDEV,VARIANCE,KURTOSIS,SKEWNESS,
42 RANGE,MINIMUM,MAXIMUM,SUM,SESKEWNESS,SEKURTOSIS,NAME@}
46 The @cmd{DESCRIPTIVES} procedure reads the active dataset and outputs
48 statistics requested by the user. In addition, it can optionally
51 The @subcmd{VARIABLES} subcommand, which is required, specifies the list of
52 variables to be analyzed. Keyword @subcmd{VARIABLES} is optional.
54 All other subcommands are optional:
56 The @subcmd{MISSING} subcommand determines the handling of missing variables. If
57 @subcmd{INCLUDE} is set, then user-missing values are included in the
58 calculations. If @subcmd{NOINCLUDE} is set, which is the default, user-missing
59 values are excluded. If @subcmd{VARIABLE} is set, then missing values are
60 excluded on a variable by variable basis; if @subcmd{LISTWISE} is set, then
61 the entire case is excluded whenever any value in that case has a
62 system-missing or, if @subcmd{INCLUDE} is set, user-missing value.
64 The @subcmd{FORMAT} subcommand affects the output format. Currently the
65 @subcmd{LABELS/NOLABELS} and @subcmd{NOINDEX/INDEX} settings are not used.
66 When @subcmd{SERIAL} is
67 set, both valid and missing number of cases are listed in the output;
68 when @subcmd{NOSERIAL} is set, only valid cases are listed.
70 The @subcmd{SAVE} subcommand causes @cmd{DESCRIPTIVES} to calculate Z scores for all
71 the specified variables. The Z scores are saved to new variables.
72 Variable names are generated by trying first the original variable name
73 with Z prepended and truncated to a maximum of 8 characters, then the
74 names ZSC000 through ZSC999, STDZ00 through STDZ09, ZZZZ00 through
75 ZZZZ09, ZQZQ00 through ZQZQ09, in that sequence. In addition, Z score
76 variable names can be specified explicitly on @subcmd{VARIABLES} in the variable
77 list by enclosing them in parentheses after each variable.
78 When Z scores are calculated, @pspp{} ignores @cmd{TEMPORARY},
79 treating temporary transformations as permanent.
81 The @subcmd{STATISTICS} subcommand specifies the statistics to be displayed:
85 All of the statistics below.
89 Standard error of the mean.
92 @item @subcmd{VARIANCE}
94 @item @subcmd{KURTOSIS}
95 Kurtosis and standard error of the kurtosis.
96 @item @subcmd{SKEWNESS}
97 Skewness and standard error of the skewness.
107 Mean, standard deviation of the mean, minimum, maximum.
109 Standard error of the kurtosis.
111 Standard error of the skewness.
114 The @subcmd{SORT} subcommand specifies how the statistics should be sorted. Most
115 of the possible values should be self-explanatory. @subcmd{NAME} causes the
116 statistics to be sorted by name. By default, the statistics are listed
117 in the order that they are specified on the @subcmd{VARIABLES} subcommand.
118 The @subcmd{A} and @subcmd{D} settings request an ascending or descending
119 sort order, respectively.
127 /VARIABLES=@var{var_list}
128 /FORMAT=@{TABLE,NOTABLE,LIMIT(@var{limit})@}
129 @{AVALUE,DVALUE,AFREQ,DFREQ@}
130 /MISSING=@{EXCLUDE,INCLUDE@}
131 /STATISTICS=@{DEFAULT,MEAN,SEMEAN,MEDIAN,MODE,STDDEV,VARIANCE,
132 KURTOSIS,SKEWNESS,RANGE,MINIMUM,MAXIMUM,SUM,
133 SESKEWNESS,SEKURTOSIS,ALL,NONE@}
135 /PERCENTILES=percent@dots{}
136 /HISTOGRAM=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
137 [@{FREQ[(@var{y_max})],PERCENT[(@var{y_max})]@}] [@{NONORMAL,NORMAL@}]
138 /PIECHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
139 [@{FREQ,PERCENT@}] [@{NOMISSING,MISSING@}]
140 /BARCHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
142 /ORDER=@{ANALYSIS,VARIABLE@}
145 (These options are not currently implemented.)
150 The @cmd{FREQUENCIES} procedure outputs frequency tables for specified
152 @cmd{FREQUENCIES} can also calculate and display descriptive statistics
153 (including median and mode) and percentiles, and various graphical representations
154 of the frequency distribution.
156 The @subcmd{VARIABLES} subcommand is the only required subcommand. Specify the
157 variables to be analyzed.
159 The @subcmd{FORMAT} subcommand controls the output format. It has several
164 @subcmd{TABLE}, the default, causes a frequency table to be output for every
165 variable specified. @subcmd{NOTABLE} prevents them from being output. @subcmd{LIMIT}
166 with a numeric argument causes them to be output except when there are
167 more than the specified number of values in the table.
170 Normally frequency tables are sorted in ascending order by value. This
171 is @subcmd{AVALUE}. @subcmd{DVALUE} tables are sorted in descending order by value.
172 @subcmd{AFREQ} and @subcmd{DFREQ} tables are sorted in ascending and descending order,
173 respectively, by frequency count.
176 The @subcmd{MISSING} subcommand controls the handling of user-missing values.
177 When @subcmd{EXCLUDE}, the default, is set, user-missing values are not included
178 in frequency tables or statistics. When @subcmd{INCLUDE} is set, user-missing
179 are included. System-missing values are never included in statistics,
180 but are listed in frequency tables.
182 The available @subcmd{STATISTICS} are the same as available
183 in @cmd{DESCRIPTIVES} (@pxref{DESCRIPTIVES}), with the addition
184 of @subcmd{MEDIAN}, the data's median
185 value, and MODE, the mode. (If there are multiple modes, the smallest
186 value is reported.) By default, the mean, standard deviation of the
187 mean, minimum, and maximum are reported for each variable.
190 @subcmd{PERCENTILES} causes the specified percentiles to be reported.
191 The percentiles should be presented at a list of numbers between 0
193 The @subcmd{NTILES} subcommand causes the percentiles to be reported at the
194 boundaries of the data set divided into the specified number of ranges.
195 For instance, @subcmd{/NTILES=4} would cause quartiles to be reported.
198 The @subcmd{HISTOGRAM} subcommand causes the output to include a histogram for
199 each specified numeric variable. The X axis by default ranges from
200 the minimum to the maximum value observed in the data, but the @subcmd{MINIMUM}
201 and @subcmd{MAXIMUM} keywords can set an explicit range.
202 @footnote{The number of
203 bins is chosen according to the Freedman-Diaconis rule:
204 @math{2 \times IQR(x)n^{-1/3}}, where @math{IQR(x)} is the interquartile range of @math{x}
205 and @math{n} is the number of samples. Note that
206 @cmd{EXAMINE} uses a different algorithm to determine bin sizes.}
207 Histograms are not created for string variables.
209 Specify @subcmd{NORMAL} to superimpose a normal curve on the
213 The @subcmd{PIECHART} subcommand adds a pie chart for each variable to the data. Each
214 slice represents one value, with the size of the slice proportional to
215 the value's frequency. By default, all non-missing values are given
217 The @subcmd{MINIMUM} and @subcmd{MAXIMUM} keywords can be used to limit the
218 displayed slices to a given range of values.
219 The keyword @subcmd{NOMISSING} causes missing values to be omitted from the
220 piechart. This is the default.
221 If instead, @subcmd{MISSING} is specified, then a single slice
222 will be included representing all system missing and user-missing cases.
225 The @subcmd{BARCHART} subcommand produces a bar chart for each variable.
226 The @subcmd{MINIMUM} and @subcmd{MAXIMUM} keywords can be used to omit
227 categories whose counts which lie outside the specified limits.
228 The @subcmd{FREQ} option (default) causes the ordinate to display the frequency
229 of each category, whereas the @subcmd{PERCENT} option will display relative
232 The @subcmd{FREQ} and @subcmd{PERCENT} options on @subcmd{HISTOGRAM} and
233 @subcmd{PIECHART} are accepted but not currently honoured.
235 The @subcmd{ORDER} subcommand is accepted but ignored.
241 @cindex Exploratory data analysis
242 @cindex normality, testing
246 VARIABLES= @var{var1} [@var{var2}] @dots{} [@var{varN}]
247 [BY @var{factor1} [BY @var{subfactor1}]
248 [ @var{factor2} [BY @var{subfactor2}]]
250 [ @var{factor3} [BY @var{subfactor3}]]
252 /STATISTICS=@{DESCRIPTIVES, EXTREME[(@var{n})], ALL, NONE@}
253 /PLOT=@{BOXPLOT, NPPLOT, HISTOGRAM, SPREADLEVEL[(@var{t})], ALL, NONE@}
255 /COMPARE=@{GROUPS,VARIABLES@}
256 /ID=@var{identity_variable}
258 /PERCENTILE=[@var{percentiles}]=@{HAVERAGE, WAVERAGE, ROUND, AEMPIRICAL, EMPIRICAL @}
259 /MISSING=@{LISTWISE, PAIRWISE@} [@{EXCLUDE, INCLUDE@}]
260 [@{NOREPORT,REPORT@}]
264 The @cmd{EXAMINE} command is used to perform exploratory data analysis.
265 In particular, it is useful for testing how closely a distribution follows a
266 normal distribution, and for finding outliers and extreme values.
268 The @subcmd{VARIABLES} subcommand is mandatory.
269 It specifies the dependent variables and optionally variables to use as
270 factors for the analysis.
271 Variables listed before the first @subcmd{BY} keyword (if any) are the
273 The dependent variables may optionally be followed by a list of
274 factors which tell @pspp{} how to break down the analysis for each
277 Following the dependent variables, factors may be specified.
278 The factors (if desired) should be preceded by a single @subcmd{BY} keyword.
279 The format for each factor is
281 @var{factorvar} [BY @var{subfactorvar}].
283 Each unique combination of the values of @var{factorvar} and
284 @var{subfactorvar} divide the dataset into @dfn{cells}.
285 Statistics will be calculated for each cell
286 and for the entire dataset (unless @subcmd{NOTOTAL} is given).
288 The @subcmd{STATISTICS} subcommand specifies which statistics to show.
289 @subcmd{DESCRIPTIVES} will produce a table showing some parametric and
290 non-parametrics statistics.
291 @subcmd{EXTREME} produces a table showing the extremities of each cell.
292 A number in parentheses, @var{n} determines
293 how many upper and lower extremities to show.
294 The default number is 5.
296 The subcommands @subcmd{TOTAL} and @subcmd{NOTOTAL} are mutually exclusive.
297 If @subcmd{TOTAL} appears, then statistics will be produced for the entire dataset
298 as well as for each cell.
299 If @subcmd{NOTOTAL} appears, then statistics will be produced only for the cells
300 (unless no factor variables have been given).
301 These subcommands have no effect if there have been no factor variables
307 @cindex spreadlevel plot
308 The @subcmd{PLOT} subcommand specifies which plots are to be produced if any.
309 Available plots are @subcmd{HISTOGRAM}, @subcmd{NPPLOT}, @subcmd{BOXPLOT} and
310 @subcmd{SPREADLEVEL}.
311 The first three can be used to visualise how closely each cell conforms to a
312 normal distribution, whilst the spread vs.@: level plot can be useful to visualise
313 how the variance of differs between factors.
314 Boxplots will also show you the outliers and extreme values.
315 @footnote{@subcmd{HISTOGRAM} uses Sturges' rule to determine the number of
316 bins, as approximately @math{1 + \log2(n)}, where @math{n} is the number of samples.
317 Note that @cmd{FREQUENCIES} uses a different algorithm to find the bin size.}
319 The @subcmd{SPREADLEVEL} plot displays the interquartile range versus the
320 median. It takes an optional parameter @var{t}, which specifies how the data
321 should be transformed prior to plotting.
322 The given value @var{t} is a power to which the data is raised. For example, if
323 @var{t} is given as 2, then the data will be squared.
324 Zero, however is a special value. If @var{t} is 0 or
325 is omitted, then data will be transformed by taking its natural logarithm instead of
326 raising to the power of @var{t}.
328 The @subcmd{COMPARE} subcommand is only relevant if producing boxplots, and it is only
329 useful there is more than one dependent variable and at least one factor.
331 @subcmd{/COMPARE=GROUPS} is specified, then one plot per dependent variable is produced,
332 each of which contain boxplots for all the cells.
333 If @subcmd{/COMPARE=VARIABLES} is specified, then one plot per cell is produced,
334 each containing one boxplot per dependent variable.
335 If the @subcmd{/COMPARE} subcommand is omitted, then @pspp{} behaves as if
336 @subcmd{/COMPARE=GROUPS} were given.
338 The @subcmd{ID} subcommand is relevant only if @subcmd{/PLOT=BOXPLOT} or
339 @subcmd{/STATISTICS=EXTREME} has been given.
340 If given, it should provide the name of a variable which is to be used
341 to labels extreme values and outliers.
342 Numeric or string variables are permissible.
343 If the @subcmd{ID} subcommand is not given, then the case number will be used for
346 The @subcmd{CINTERVAL} subcommand specifies the confidence interval to use in
347 calculation of the descriptives command. The default is 95%.
350 The @subcmd{PERCENTILES} subcommand specifies which percentiles are to be calculated,
351 and which algorithm to use for calculating them. The default is to
352 calculate the 5, 10, 25, 50, 75, 90, 95 percentiles using the
353 @subcmd{HAVERAGE} algorithm.
355 The @subcmd{TOTAL} and @subcmd{NOTOTAL} subcommands are mutually exclusive. If @subcmd{NOTOTAL}
356 is given and factors have been specified in the @subcmd{VARIABLES} subcommand,
357 then then statistics for the unfactored dependent variables are
358 produced in addition to the factored variables. If there are no
359 factors specified then @subcmd{TOTAL} and @subcmd{NOTOTAL} have no effect.
362 The following example will generate descriptive statistics and histograms for
363 two variables @var{score1} and @var{score2}.
364 Two factors are given, @i{viz}: @var{gender} and @var{gender} BY @var{culture}.
365 Therefore, the descriptives and histograms will be generated for each
367 of @var{gender} @emph{and} for each distinct combination of the values
368 of @var{gender} and @var{race}.
369 Since the @subcmd{NOTOTAL} keyword is given, statistics and histograms for
370 @var{score1} and @var{score2} covering the whole dataset are not produced.
372 EXAMINE @var{score1} @var{score2} BY
374 @var{gender} BY @var{culture}
375 /STATISTICS = DESCRIPTIVES
380 Here is a second example showing how the @cmd{examine} command can be used to find extremities.
382 EXAMINE @var{height} @var{weight} BY
384 /STATISTICS = EXTREME (3)
389 In this example, we look at the height and weight of a sample of individuals and
390 how they differ between male and female.
391 A table showing the 3 largest and the 3 smallest values of @var{height} and
392 @var{weight} for each gender, and for the whole dataset will be shown.
393 Boxplots will also be produced.
394 Because @subcmd{/COMPARE = GROUPS} was given, boxplots for male and female will be
395 shown in the same graphic, allowing us to easily see the difference between
397 Since the variable @var{name} was specified on the @subcmd{ID} subcommand, this will be
398 used to label the extreme values.
401 If many dependent variables are specified, or if factor variables are
403 there are many distinct values, then @cmd{EXAMINE} will produce a very
404 large quantity of output.
410 @cindex Exploratory data analysis
411 @cindex normality, testing
415 /HISTOGRAM [(NORMAL)]= @var{var}
416 /SCATTERPLOT [(BIVARIATE)] = @var{var1} WITH @var{var2} [BY @var{var3}]
417 /BAR = @{@var{summary-function}(@var{var1}) | @var{count-function}@} BY @var{var2} [BY @var{var3}]
418 [ /MISSING=@{LISTWISE, VARIABLE@} [@{EXCLUDE, INCLUDE@}] ]
419 [@{NOREPORT,REPORT@}]
423 The @cmd{GRAPH} produces graphical plots of data. Only one of the subcommands
424 @subcmd{HISTOGRAM} or @subcmd{SCATTERPLOT} can be specified, i.e. only one plot
425 can be produced per call of @cmd{GRAPH}. The @subcmd{MISSING} is optional.
428 * SCATTERPLOT:: Cartesian Plots
429 * HISTOGRAM:: Histograms
430 * BAR CHART:: Bar Charts
434 @subsection Scatterplot
437 The subcommand @subcmd{SCATTERPLOT} produces an xy plot of the
438 data. The different values of the optional third variable @var{var3}
439 will result in different colours and/or markers for the plot. The
440 following is an example for producing a scatterplot.
444 /SCATTERPLOT = @var{height} WITH @var{weight} BY @var{gender}.
447 This example will produce a scatterplot where @var{height} is plotted versus @var{weight}. Depending
448 on the value of the @var{gender} variable, the colour of the datapoint is different. With
449 this plot it is possible to analyze gender differences for @var{height} vs.@: @var{weight} relation.
452 @subsection Histogram
455 The subcommand @subcmd{HISTOGRAM} produces a histogram. Only one variable is allowed for
457 The keyword @subcmd{NORMAL} may be specified in parentheses, to indicate that the ideal normal curve
458 should be superimposed over the histogram.
459 For an alternative method to produce histograms @pxref{EXAMINE}. The
460 following example produces a histogram plot for the variable @var{weight}.
464 /HISTOGRAM = @var{weight}.
468 @subsection Bar Chart
471 The subcommand @subcmd{BAR} produces a bar chart.
472 This subcommand requires that a @var{count-function} be specified (with no arguments) or a @var{summary-function} with a variable @var{var1} in parentheses.
473 Following the summary or count function, the keyword @subcmd{BY} should be specified and then a catagorical variable, @var{var2}.
474 The values of the variable @var{var2} determine the labels of the bars to be plotted.
475 Optionally a second categorical variable @var{var3} may be specified in which case a clustered (grouped) bar chart is produced.
477 Valid count functions are
480 The weighted counts of the cases in each category.
482 The weighted counts of the cases in each category expressed as a percentage of the total weights of the cases.
484 The cumulative weighted counts of the cases in each category.
486 The cumulative weighted counts of the cases in each category expressed as a percentage of the total weights of the cases.
489 The summary function is applied to @var{var1} across all cases in each category.
490 The recognised summary functions are:
502 The following examples assume a dataset which is the results of a survey.
503 Each respondent has indicated annual income, their sex and city of residence.
504 One could create a bar chart showing how the mean income varies between of residents of different cities, thus:
506 GRAPH /BAR = MEAN(@var{income}) BY @var{city}.
509 This can be extended to also indicate how income in each city differs between the sexes.
511 GRAPH /BAR = MEAN(@var{income}) BY @var{city} BY @var{sex}.
514 One might also want to see how many respondents there are from each city. This can be achieved as follows:
516 GRAPH /BAR = COUNT BY @var{city}.
519 Bar charts can also be produced using the @ref{FREQUENCIES} and @ref{CROSSTABS} commands.
522 @section CORRELATIONS
527 /VARIABLES = @var{var_list} [ WITH @var{var_list} ]
532 /VARIABLES = @var{var_list} [ WITH @var{var_list} ]
533 /VARIABLES = @var{var_list} [ WITH @var{var_list} ]
536 [ /PRINT=@{TWOTAIL, ONETAIL@} @{SIG, NOSIG@} ]
537 [ /STATISTICS=DESCRIPTIVES XPROD ALL]
538 [ /MISSING=@{PAIRWISE, LISTWISE@} @{INCLUDE, EXCLUDE@} ]
542 The @cmd{CORRELATIONS} procedure produces tables of the Pearson correlation coefficient
543 for a set of variables. The significance of the coefficients are also given.
545 At least one @subcmd{VARIABLES} subcommand is required. If the @subcmd{WITH}
546 keyword is used, then a non-square correlation table will be produced.
547 The variables preceding @subcmd{WITH}, will be used as the rows of the table,
548 and the variables following will be the columns of the table.
549 If no @subcmd{WITH} subcommand is given, then a square, symmetrical table using all variables is produced.
552 The @cmd{MISSING} subcommand determines the handling of missing variables.
553 If @subcmd{INCLUDE} is set, then user-missing values are included in the
554 calculations, but system-missing values are not.
555 If @subcmd{EXCLUDE} is set, which is the default, user-missing
556 values are excluded as well as system-missing values.
558 If @subcmd{LISTWISE} is set, then the entire case is excluded from analysis
559 whenever any variable specified in any @cmd{/VARIABLES} subcommand
560 contains a missing value.
561 If @subcmd{PAIRWISE} is set, then a case is considered missing only if either of the
562 values for the particular coefficient are missing.
563 The default is @subcmd{PAIRWISE}.
565 The @subcmd{PRINT} subcommand is used to control how the reported significance values are printed.
566 If the @subcmd{TWOTAIL} option is used, then a two-tailed test of significance is
567 printed. If the @subcmd{ONETAIL} option is given, then a one-tailed test is used.
568 The default is @subcmd{TWOTAIL}.
570 If the @subcmd{NOSIG} option is specified, then correlation coefficients with significance less than
571 0.05 are highlighted.
572 If @subcmd{SIG} is specified, then no highlighting is performed. This is the default.
575 The @subcmd{STATISTICS} subcommand requests additional statistics to be displayed. The keyword
576 @subcmd{DESCRIPTIVES} requests that the mean, number of non-missing cases, and the non-biased
577 estimator of the standard deviation are displayed.
578 These statistics will be displayed in a separated table, for all the variables listed
579 in any @subcmd{/VARIABLES} subcommand.
580 The @subcmd{XPROD} keyword requests cross-product deviations and covariance estimators to
581 be displayed for each pair of variables.
582 The keyword @subcmd{ALL} is the union of @subcmd{DESCRIPTIVES} and @subcmd{XPROD}.
590 /TABLES=@var{var_list} BY @var{var_list} [BY @var{var_list}]@dots{}
591 /MISSING=@{TABLE,INCLUDE,REPORT@}
592 /WRITE=@{NONE,CELLS,ALL@}
593 /FORMAT=@{TABLES,NOTABLES@}
598 /CELLS=@{COUNT,ROW,COLUMN,TOTAL,EXPECTED,RESIDUAL,SRESIDUAL,
599 ASRESIDUAL,ALL,NONE@}
600 /COUNT=@{ASIS,CASE,CELL@}
602 /STATISTICS=@{CHISQ,PHI,CC,LAMBDA,UC,BTAU,CTAU,RISK,GAMMA,D,
603 KAPPA,ETA,CORR,ALL,NONE@}
607 /VARIABLES=@var{var_list} (@var{low},@var{high})@dots{}
610 The @cmd{CROSSTABS} procedure displays crosstabulation
611 tables requested by the user. It can calculate several statistics for
612 each cell in the crosstabulation tables. In addition, a number of
613 statistics can be calculated for each table itself.
615 The @subcmd{TABLES} subcommand is used to specify the tables to be reported. Any
616 number of dimensions is permitted, and any number of variables per
617 dimension is allowed. The @subcmd{TABLES} subcommand may be repeated as many
618 times as needed. This is the only required subcommand in @dfn{general
621 Occasionally, one may want to invoke a special mode called @dfn{integer
622 mode}. Normally, in general mode, @pspp{} automatically determines
623 what values occur in the data. In integer mode, the user specifies the
624 range of values that the data assumes. To invoke this mode, specify the
625 @subcmd{VARIABLES} subcommand, giving a range of data values in parentheses for
626 each variable to be used on the @subcmd{TABLES} subcommand. Data values inside
627 the range are truncated to the nearest integer, then assigned to that
628 value. If values occur outside this range, they are discarded. When it
629 is present, the @subcmd{VARIABLES} subcommand must precede the @subcmd{TABLES}
632 In general mode, numeric and string variables may be specified on
633 TABLES. In integer mode, only numeric variables are allowed.
635 The @subcmd{MISSING} subcommand determines the handling of user-missing values.
636 When set to @subcmd{TABLE}, the default, missing values are dropped on a table by
637 table basis. When set to @subcmd{INCLUDE}, user-missing values are included in
638 tables and statistics. When set to @subcmd{REPORT}, which is allowed only in
639 integer mode, user-missing values are included in tables but marked with
640 an @samp{M} (for ``missing'') and excluded from statistical
643 Currently the @subcmd{WRITE} subcommand is ignored.
645 The @subcmd{FORMAT} subcommand controls the characteristics of the
646 crosstabulation tables to be displayed. It has a number of possible
651 @subcmd{TABLES}, the default, causes crosstabulation tables to be output.
652 @subcmd{NOTABLES} suppresses them.
655 @subcmd{PIVOT}, the default, causes each @subcmd{TABLES} subcommand to be displayed in a
656 pivot table format. @subcmd{NOPIVOT} causes the old-style crosstabulation format
660 @subcmd{AVALUE}, the default, causes values to be sorted in ascending order.
661 @subcmd{DVALUE} asserts a descending sort order.
664 @subcmd{INDEX} and @subcmd{NOINDEX} are currently ignored.
667 @subcmd{BOX} and @subcmd{NOBOX} is currently ignored.
670 The @subcmd{CELLS} subcommand controls the contents of each cell in the displayed
671 crosstabulation table. The possible settings are:
687 Standardized residual.
689 Adjusted standardized residual.
693 Suppress cells entirely.
696 @samp{/CELLS} without any settings specified requests @subcmd{COUNT}, @subcmd{ROW},
697 @subcmd{COLUMN}, and @subcmd{TOTAL}.
698 If @subcmd{CELLS} is not specified at all then only @subcmd{COUNT}
701 By default, crosstabulation and statistics use raw case weights,
702 without rounding. Use the @subcmd{/COUNT} subcommand to perform
703 rounding: CASE rounds the weights of individual weights as cases are
704 read, CELL rounds the weights of cells within each crosstabulation
705 table after it has been constructed, and ASIS explicitly specifies the
706 default non-rounding behavior. When rounding is requested, ROUND, the
707 default, rounds to the nearest integer and TRUNCATE rounds toward
710 The @subcmd{STATISTICS} subcommand selects statistics for computation:
717 Pearson chi-square, likelihood ratio, Fisher's exact test, continuity
718 correction, linear-by-linear association.
722 Contingency coefficient.
726 Uncertainty coefficient.
742 Spearman correlation, Pearson's r.
749 Selected statistics are only calculated when appropriate for the
750 statistic. Certain statistics require tables of a particular size, and
751 some statistics are calculated only in integer mode.
753 @samp{/STATISTICS} without any settings selects CHISQ. If the
754 @subcmd{STATISTICS} subcommand is not given, no statistics are calculated.
757 The @samp{/BARCHART} subcommand produces a clustered bar chart for the first two
758 variables on each table.
759 If a table has more than two variables, the counts for the third and subsequent levels
760 will be aggregated and the chart will be produces as if there were only two variables.
763 @strong{Please note:} Currently the implementation of @cmd{CROSSTABS} has the
764 following limitations:
768 Significance of some symmetric and directional measures is not calculated.
770 Asymptotic standard error is not calculated for
771 Goodman and Kruskal's tau or symmetric Somers' d.
773 Approximate T is not calculated for symmetric uncertainty coefficient.
776 Fixes for any of these deficiencies would be welcomed.
782 @cindex factor analysis
783 @cindex principal components analysis
784 @cindex principal axis factoring
785 @cindex data reduction
788 FACTOR VARIABLES=@var{var_list}
790 [ /METHOD = @{CORRELATION, COVARIANCE@} ]
792 [ /ANALYSIS=@var{var_list} ]
794 [ /EXTRACTION=@{PC, PAF@}]
796 [ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, PROMAX[(@var{k})], NOROTATE@}]
798 [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [KMO] [SIG] [ALL] [DEFAULT] ]
802 [ /FORMAT=[SORT] [BLANK(@var{n})] [DEFAULT] ]
804 [ /CRITERIA=[FACTORS(@var{n})] [MINEIGEN(@var{l})] [ITERATE(@var{m})] [ECONVERGE (@var{delta})] [DEFAULT] ]
806 [ /MISSING=[@{LISTWISE, PAIRWISE@}] [@{INCLUDE, EXCLUDE@}] ]
809 The @cmd{FACTOR} command performs Factor Analysis or Principal Axis Factoring on a dataset. It may be used to find
810 common factors in the data or for data reduction purposes.
812 The @subcmd{VARIABLES} subcommand is required. It lists the variables
813 which are to partake in the analysis. (The @subcmd{ANALYSIS}
814 subcommand may optionally further limit the variables that
815 participate; it is not useful and implemented only for compatibility.)
817 The @subcmd{/EXTRACTION} subcommand is used to specify the way in which factors (components) are extracted from the data.
818 If @subcmd{PC} is specified, then Principal Components Analysis is used.
819 If @subcmd{PAF} is specified, then Principal Axis Factoring is
820 used. By default Principal Components Analysis will be used.
822 The @subcmd{/ROTATION} subcommand is used to specify the method by which the extracted solution will be rotated.
823 Three orthogonal rotation methods are available:
824 @subcmd{VARIMAX} (which is the default), @subcmd{EQUAMAX}, and @subcmd{QUARTIMAX}.
825 There is one oblique rotation method, @i{viz}: @subcmd{PROMAX}.
826 Optionally you may enter the power of the promax rotation @var{k}, which must be enclosed in parentheses.
827 The default value of @var{k} is 5.
828 If you don't want any rotation to be performed, the word @subcmd{NOROTATE} will prevent the command from performing any
829 rotation on the data.
831 The @subcmd{/METHOD} subcommand should be used to determine whether the covariance matrix or the correlation matrix of the data is
832 to be analysed. By default, the correlation matrix is analysed.
834 The @subcmd{/PRINT} subcommand may be used to select which features of the analysis are reported:
837 @item @subcmd{UNIVARIATE}
838 A table of mean values, standard deviations and total weights are printed.
839 @item @subcmd{INITIAL}
840 Initial communalities and eigenvalues are printed.
841 @item @subcmd{EXTRACTION}
842 Extracted communalities and eigenvalues are printed.
843 @item @subcmd{ROTATION}
844 Rotated communalities and eigenvalues are printed.
845 @item @subcmd{CORRELATION}
846 The correlation matrix is printed.
847 @item @subcmd{COVARIANCE}
848 The covariance matrix is printed.
850 The determinant of the correlation or covariance matrix is printed.
852 The Kaiser-Meyer-Olkin measure of sampling adequacy and the Bartlett test of sphericity is printed.
854 The significance of the elements of correlation matrix is printed.
856 All of the above are printed.
857 @item @subcmd{DEFAULT}
858 Identical to @subcmd{INITIAL} and @subcmd{EXTRACTION}.
861 If @subcmd{/PLOT=EIGEN} is given, then a ``Scree'' plot of the eigenvalues will be printed. This can be useful for visualizing
862 which factors (components) should be retained.
864 The @subcmd{/FORMAT} subcommand determined how data are to be displayed in loading matrices. If @subcmd{SORT} is specified, then the variables
865 are sorted in descending order of significance. If @subcmd{BLANK(@var{n})} is specified, then coefficients whose absolute value is less
866 than @var{n} will not be printed. If the keyword @subcmd{DEFAULT} is given, or if no @subcmd{/FORMAT} subcommand is given, then no sorting is
867 performed, and all coefficients will be printed.
869 The @subcmd{/CRITERIA} subcommand is used to specify how the number of extracted factors (components) are chosen.
870 If @subcmd{FACTORS(@var{n})} is
871 specified, where @var{n} is an integer, then @var{n} factors will be extracted. Otherwise, the @subcmd{MINEIGEN} setting will
873 @subcmd{MINEIGEN(@var{l})} requests that all factors whose eigenvalues are greater than or equal to @var{l} are extracted.
874 The default value of @var{l} is 1.
875 The @subcmd{ECONVERGE} setting has effect only when iterative algorithms for factor
876 extraction (such as Principal Axis Factoring) are used.
877 @subcmd{ECONVERGE(@var{delta})} specifies that
878 iteration should cease when
879 the maximum absolute value of the communality estimate between one iteration and the previous is less than @var{delta}. The
880 default value of @var{delta} is 0.001.
881 The @subcmd{ITERATE(@var{m})} may appear any number of times and is used for two different purposes.
882 It is used to set the maximum number of iterations (@var{m}) for convergence and also to set the maximum number of iterations
884 Whether it affects convergence or rotation depends upon which subcommand follows the @subcmd{ITERATE} subcommand.
885 If @subcmd{EXTRACTION} follows, it affects convergence.
886 If @subcmd{ROTATION} follows, it affects rotation.
887 If neither @subcmd{ROTATION} nor @subcmd{EXTRACTION} follow a @subcmd{ITERATE} subcommand it will be ignored.
888 The default value of @var{m} is 25.
890 The @cmd{MISSING} subcommand determines the handling of missing variables.
891 If @subcmd{INCLUDE} is set, then user-missing values are included in the
892 calculations, but system-missing values are not.
893 If @subcmd{EXCLUDE} is set, which is the default, user-missing
894 values are excluded as well as system-missing values.
896 If @subcmd{LISTWISE} is set, then the entire case is excluded from analysis
897 whenever any variable specified in the @cmd{VARIABLES} subcommand
898 contains a missing value.
899 If @subcmd{PAIRWISE} is set, then a case is considered missing only if either of the
900 values for the particular coefficient are missing.
901 The default is @subcmd{LISTWISE}.
907 @cindex univariate analysis of variance
908 @cindex fixed effects
909 @cindex factorial anova
910 @cindex analysis of variance
915 GLM @var{dependent_vars} BY @var{fixed_factors}
916 [/METHOD = SSTYPE(@var{type})]
917 [/DESIGN = @var{interaction_0} [@var{interaction_1} [... @var{interaction_n}]]]
918 [/INTERCEPT = @{INCLUDE|EXCLUDE@}]
919 [/MISSING = @{INCLUDE|EXCLUDE@}]
922 The @cmd{GLM} procedure can be used for fixed effects factorial Anova.
924 The @var{dependent_vars} are the variables to be analysed.
925 You may analyse several variables in the same command in which case they should all
926 appear before the @code{BY} keyword.
928 The @var{fixed_factors} list must be one or more categorical variables. Normally it
929 will not make sense to enter a scalar variable in the @var{fixed_factors} and doing
930 so may cause @pspp{} to do a lot of unnecessary processing.
932 The @subcmd{METHOD} subcommand is used to change the method for producing the sums of
933 squares. Available values of @var{type} are 1, 2 and 3. The default is type 3.
935 You may specify a custom design using the @subcmd{DESIGN} subcommand.
936 The design comprises a list of interactions where each interaction is a
937 list of variables separated by a @samp{*}. For example the command
939 GLM subject BY sex age_group race
940 /DESIGN = age_group sex group age_group*sex age_group*race
942 @noindent specifies the model @math{subject = age_group + sex + race + age_group*sex + age_group*race}.
943 If no @subcmd{DESIGN} subcommand is specified, then the default is all possible combinations
944 of the fixed factors. That is to say
946 GLM subject BY sex age_group race
949 @math{subject = age_group + sex + race + age_group*sex + age_group*race + sex*race + age_group*sex*race}.
952 The @subcmd{MISSING} subcommand determines the handling of missing
954 If @subcmd{INCLUDE} is set, then user-missing values are included in the
955 calculations, but system-missing values are not.
956 If @subcmd{EXCLUDE} is set, which is the default, user-missing
957 values are excluded as well as system-missing values.
961 @node LOGISTIC REGRESSION
962 @section LOGISTIC REGRESSION
964 @vindex LOGISTIC REGRESSION
965 @cindex logistic regression
966 @cindex bivariate logistic regression
969 LOGISTIC REGRESSION [VARIABLES =] @var{dependent_var} WITH @var{predictors}
971 [/CATEGORICAL = @var{categorical_predictors}]
973 [@{/NOCONST | /ORIGIN | /NOORIGIN @}]
975 [/PRINT = [SUMMARY] [DEFAULT] [CI(@var{confidence})] [ALL]]
977 [/CRITERIA = [BCON(@var{min_delta})] [ITERATE(@var{max_interations})]
978 [LCON(@var{min_likelihood_delta})] [EPS(@var{min_epsilon})]
979 [CUT(@var{cut_point})]]
981 [/MISSING = @{INCLUDE|EXCLUDE@}]
984 Bivariate Logistic Regression is used when you want to explain a dichotomous dependent
985 variable in terms of one or more predictor variables.
987 The minimum command is
989 LOGISTIC REGRESSION @var{y} WITH @var{x1} @var{x2} @dots{} @var{xn}.
991 Here, @var{y} is the dependent variable, which must be dichotomous and @var{x1} @dots{} @var{xn}
992 are the predictor variables whose coefficients the procedure estimates.
994 By default, a constant term is included in the model.
995 Hence, the full model is
998 = b_0 + b_1 {\bf x_1}
1004 Predictor variables which are categorical in nature should be listed on the @subcmd{/CATEGORICAL} subcommand.
1005 Simple variables as well as interactions between variables may be listed here.
1007 If you want a model without the constant term @math{b_0}, use the keyword @subcmd{/ORIGIN}.
1008 @subcmd{/NOCONST} is a synonym for @subcmd{/ORIGIN}.
1010 An iterative Newton-Raphson procedure is used to fit the model.
1011 The @subcmd{/CRITERIA} subcommand is used to specify the stopping criteria of the procedure,
1012 and other parameters.
1013 The value of @var{cut_point} is used in the classification table. It is the
1014 threshold above which predicted values are considered to be 1. Values
1015 of @var{cut_point} must lie in the range [0,1].
1016 During iterations, if any one of the stopping criteria are satisfied, the procedure is
1017 considered complete.
1018 The stopping criteria are:
1020 @item The number of iterations exceeds @var{max_iterations}.
1021 The default value of @var{max_iterations} is 20.
1022 @item The change in the all coefficient estimates are less than @var{min_delta}.
1023 The default value of @var{min_delta} is 0.001.
1024 @item The magnitude of change in the likelihood estimate is less than @var{min_likelihood_delta}.
1025 The default value of @var{min_delta} is zero.
1026 This means that this criterion is disabled.
1027 @item The differential of the estimated probability for all cases is less than @var{min_epsilon}.
1028 In other words, the probabilities are close to zero or one.
1029 The default value of @var{min_epsilon} is 0.00000001.
1033 The @subcmd{PRINT} subcommand controls the display of optional statistics.
1034 Currently there is one such option, @subcmd{CI}, which indicates that the
1035 confidence interval of the odds ratio should be displayed as well as its value.
1036 @subcmd{CI} should be followed by an integer in parentheses, to indicate the
1037 confidence level of the desired confidence interval.
1039 The @subcmd{MISSING} subcommand determines the handling of missing
1041 If @subcmd{INCLUDE} is set, then user-missing values are included in the
1042 calculations, but system-missing values are not.
1043 If @subcmd{EXCLUDE} is set, which is the default, user-missing
1044 values are excluded as well as system-missing values.
1045 This is the default.
1056 [ BY @{@var{var_list}@} [BY @{@var{var_list}@} [BY @{@var{var_list}@} @dots{} ]]]
1058 [ /@{@var{var_list}@}
1059 [ BY @{@var{var_list}@} [BY @{@var{var_list}@} [BY @{@var{var_list}@} @dots{} ]]] ]
1061 [/CELLS = [MEAN] [COUNT] [STDDEV] [SEMEAN] [SUM] [MIN] [MAX] [RANGE]
1062 [VARIANCE] [KURT] [SEKURT]
1063 [SKEW] [SESKEW] [FIRST] [LAST]
1064 [HARMONIC] [GEOMETRIC]
1069 [/MISSING = [TABLE] [INCLUDE] [DEPENDENT]]
1072 You can use the @cmd{MEANS} command to calculate the arithmetic mean and similar
1073 statistics, either for the dataset as a whole or for categories of data.
1075 The simplest form of the command is
1079 @noindent which calculates the mean, count and standard deviation for @var{v}.
1080 If you specify a grouping variable, for example
1082 MEANS @var{v} BY @var{g}.
1084 @noindent then the means, counts and standard deviations for @var{v} after having
1085 been grouped by @var{g} will be calculated.
1086 Instead of the mean, count and standard deviation, you could specify the statistics
1087 in which you are interested:
1089 MEANS @var{x} @var{y} BY @var{g}
1090 /CELLS = HARMONIC SUM MIN.
1092 This example calculates the harmonic mean, the sum and the minimum values of @var{x} and @var{y}
1095 The @subcmd{CELLS} subcommand specifies which statistics to calculate. The available statistics
1099 @cindex arithmetic mean
1100 The arithmetic mean.
1101 @item @subcmd{COUNT}
1102 The count of the values.
1103 @item @subcmd{STDDEV}
1104 The standard deviation.
1105 @item @subcmd{SEMEAN}
1106 The standard error of the mean.
1108 The sum of the values.
1113 @item @subcmd{RANGE}
1114 The difference between the maximum and minimum values.
1115 @item @subcmd{VARIANCE}
1117 @item @subcmd{FIRST}
1118 The first value in the category.
1120 The last value in the category.
1123 @item @subcmd{SESKEW}
1124 The standard error of the skewness.
1127 @item @subcmd{SEKURT}
1128 The standard error of the kurtosis.
1129 @item @subcmd{HARMONIC}
1130 @cindex harmonic mean
1132 @item @subcmd{GEOMETRIC}
1133 @cindex geometric mean
1137 In addition, three special keywords are recognized:
1139 @item @subcmd{DEFAULT}
1140 This is the same as @subcmd{MEAN} @subcmd{COUNT} @subcmd{STDDEV}.
1142 All of the above statistics will be calculated.
1144 No statistics will be calculated (only a summary will be shown).
1148 More than one @dfn{table} can be specified in a single command.
1149 Each table is separated by a @samp{/}. For
1153 @var{c} @var{d} @var{e} BY @var{x}
1154 /@var{a} @var{b} BY @var{x} @var{y}
1155 /@var{f} BY @var{y} BY @var{z}.
1157 has three tables (the @samp{TABLE =} is optional).
1158 The first table has three dependent variables @var{c}, @var{d} and @var{e}
1159 and a single categorical variable @var{x}.
1160 The second table has two dependent variables @var{a} and @var{b},
1161 and two categorical variables @var{x} and @var{y}.
1162 The third table has a single dependent variables @var{f}
1163 and a categorical variable formed by the combination of @var{y} and @var{z}.
1166 By default values are omitted from the analysis only if missing values
1167 (either system missing or user missing)
1168 for any of the variables directly involved in their calculation are
1170 This behaviour can be modified with the @subcmd{/MISSING} subcommand.
1171 Three options are possible: @subcmd{TABLE}, @subcmd{INCLUDE} and @subcmd{DEPENDENT}.
1173 @subcmd{/MISSING = TABLE} causes cases to be dropped if any variable is missing
1174 in the table specification currently being processed, regardless of
1175 whether it is needed to calculate the statistic.
1177 @subcmd{/MISSING = INCLUDE} says that user missing values, either in the dependent
1178 variables or in the categorical variables should be taken at their face
1179 value, and not excluded.
1181 @subcmd{/MISSING = DEPENDENT} says that user missing values, in the dependent
1182 variables should be taken at their face value, however cases which
1183 have user missing values for the categorical variables should be omitted
1184 from the calculation.
1190 @cindex nonparametric tests
1195 nonparametric test subcommands
1200 [ /STATISTICS=@{DESCRIPTIVES@} ]
1202 [ /MISSING=@{ANALYSIS, LISTWISE@} @{INCLUDE, EXCLUDE@} ]
1204 [ /METHOD=EXACT [ TIMER [(@var{n})] ] ]
1207 @cmd{NPAR TESTS} performs nonparametric tests.
1208 Non parametric tests make very few assumptions about the distribution of the
1210 One or more tests may be specified by using the corresponding subcommand.
1211 If the @subcmd{/STATISTICS} subcommand is also specified, then summary statistics are
1212 produces for each variable that is the subject of any test.
1214 Certain tests may take a long time to execute, if an exact figure is required.
1215 Therefore, by default asymptotic approximations are used unless the
1216 subcommand @subcmd{/METHOD=EXACT} is specified.
1217 Exact tests give more accurate results, but may take an unacceptably long
1218 time to perform. If the @subcmd{TIMER} keyword is used, it sets a maximum time,
1219 after which the test will be abandoned, and a warning message printed.
1220 The time, in minutes, should be specified in parentheses after the @subcmd{TIMER} keyword.
1221 If the @subcmd{TIMER} keyword is given without this figure, then a default value of 5 minutes
1226 * BINOMIAL:: Binomial Test
1227 * CHISQUARE:: Chisquare Test
1228 * COCHRAN:: Cochran Q Test
1229 * FRIEDMAN:: Friedman Test
1230 * KENDALL:: Kendall's W Test
1231 * KOLMOGOROV-SMIRNOV:: Kolmogorov Smirnov Test
1232 * KRUSKAL-WALLIS:: Kruskal-Wallis Test
1233 * MANN-WHITNEY:: Mann Whitney U Test
1234 * MCNEMAR:: McNemar Test
1235 * MEDIAN:: Median Test
1237 * SIGN:: The Sign Test
1238 * WILCOXON:: Wilcoxon Signed Ranks Test
1243 @subsection Binomial test
1245 @cindex binomial test
1248 [ /BINOMIAL[(@var{p})]=@var{var_list}[(@var{value1}[, @var{value2})] ] ]
1251 The @subcmd{/BINOMIAL} subcommand compares the observed distribution of a dichotomous
1252 variable with that of a binomial distribution.
1253 The variable @var{p} specifies the test proportion of the binomial
1255 The default value of 0.5 is assumed if @var{p} is omitted.
1257 If a single value appears after the variable list, then that value is
1258 used as the threshold to partition the observed values. Values less
1259 than or equal to the threshold value form the first category. Values
1260 greater than the threshold form the second category.
1262 If two values appear after the variable list, then they will be used
1263 as the values which a variable must take to be in the respective
1265 Cases for which a variable takes a value equal to neither of the specified
1266 values, take no part in the test for that variable.
1268 If no values appear, then the variable must assume dichotomous
1270 If more than two distinct, non-missing values for a variable
1271 under test are encountered then an error occurs.
1273 If the test proportion is equal to 0.5, then a two tailed test is
1274 reported. For any other test proportion, a one tailed test is
1276 For one tailed tests, if the test proportion is less than
1277 or equal to the observed proportion, then the significance of
1278 observing the observed proportion or more is reported.
1279 If the test proportion is more than the observed proportion, then the
1280 significance of observing the observed proportion or less is reported.
1281 That is to say, the test is always performed in the observed
1284 @pspp{} uses a very precise approximation to the gamma function to
1285 compute the binomial significance. Thus, exact results are reported
1286 even for very large sample sizes.
1291 @subsection Chisquare Test
1293 @cindex chisquare test
1297 [ /CHISQUARE=@var{var_list}[(@var{lo},@var{hi})] [/EXPECTED=@{EQUAL|@var{f1}, @var{f2} @dots{} @var{fn}@}] ]
1301 The @subcmd{/CHISQUARE} subcommand produces a chi-square statistic for the differences
1302 between the expected and observed frequencies of the categories of a variable.
1303 Optionally, a range of values may appear after the variable list.
1304 If a range is given, then non integer values are truncated, and values
1305 outside the specified range are excluded from the analysis.
1307 The @subcmd{/EXPECTED} subcommand specifies the expected values of each
1309 There must be exactly one non-zero expected value, for each observed
1310 category, or the @subcmd{EQUAL} keyword must be specified.
1311 You may use the notation @subcmd{@var{n}*@var{f}} to specify @var{n}
1312 consecutive expected categories all taking a frequency of @var{f}.
1313 The frequencies given are proportions, not absolute frequencies. The
1314 sum of the frequencies need not be 1.
1315 If no @subcmd{/EXPECTED} subcommand is given, then then equal frequencies
1320 @subsection Cochran Q Test
1322 @cindex Cochran Q test
1323 @cindex Q, Cochran Q
1326 [ /COCHRAN = @var{var_list} ]
1329 The Cochran Q test is used to test for differences between three or more groups.
1330 The data for @var{var_list} in all cases must assume exactly two distinct values (other than missing values).
1332 The value of Q will be displayed and its Asymptotic significance based on a chi-square distribution.
1335 @subsection Friedman Test
1337 @cindex Friedman test
1340 [ /FRIEDMAN = @var{var_list} ]
1343 The Friedman test is used to test for differences between repeated measures when
1344 there is no indication that the distributions are normally distributed.
1346 A list of variables which contain the measured data must be given. The procedure
1347 prints the sum of ranks for each variable, the test statistic and its significance.
1350 @subsection Kendall's W Test
1352 @cindex Kendall's W test
1353 @cindex coefficient of concordance
1356 [ /KENDALL = @var{var_list} ]
1359 The Kendall test investigates whether an arbitrary number of related samples come from the
1361 It is identical to the Friedman test except that the additional statistic W, Kendall's Coefficient of Concordance is printed.
1362 It has the range [0,1] --- a value of zero indicates no agreement between the samples whereas a value of
1363 unity indicates complete agreement.
1366 @node KOLMOGOROV-SMIRNOV
1367 @subsection Kolmogorov-Smirnov Test
1368 @vindex KOLMOGOROV-SMIRNOV
1370 @cindex Kolmogorov-Smirnov test
1373 [ /KOLMOGOROV-SMIRNOV (@{NORMAL [@var{mu}, @var{sigma}], UNIFORM [@var{min}, @var{max}], POISSON [@var{lambda}], EXPONENTIAL [@var{scale}] @}) = @var{var_list} ]
1376 The one sample Kolmogorov-Smirnov subcommand is used to test whether or not a dataset is
1377 drawn from a particular distribution. Four distributions are supported, @i{viz:}
1378 Normal, Uniform, Poisson and Exponential.
1380 Ideally you should provide the parameters of the distribution against which you wish to test
1381 the data. For example, with the normal distribution the mean (@var{mu})and standard deviation (@var{sigma})
1382 should be given; with the uniform distribution, the minimum (@var{min})and maximum (@var{max}) value should
1384 However, if the parameters are omitted they will be imputed from the data. Imputing the
1385 parameters reduces the power of the test so should be avoided if possible.
1387 In the following example, two variables @var{score} and @var{age} are tested to see if
1388 they follow a normal distribution with a mean of 3.5 and a standard deviation of 2.0.
1391 /KOLMOGOROV-SMIRNOV (normal 3.5 2.0) = @var{score} @var{age}.
1393 If the variables need to be tested against different distributions, then a separate
1394 subcommand must be used. For example the following syntax tests @var{score} against
1395 a normal distribution with mean of 3.5 and standard deviation of 2.0 whilst @var{age}
1396 is tested against a normal distribution of mean 40 and standard deviation 1.5.
1399 /KOLMOGOROV-SMIRNOV (normal 3.5 2.0) = @var{score}
1400 /KOLMOGOROV-SMIRNOV (normal 40 1.5) = @var{age}.
1403 The abbreviated subcommand @subcmd{K-S} may be used in place of @subcmd{KOLMOGOROV-SMIRNOV}.
1405 @node KRUSKAL-WALLIS
1406 @subsection Kruskal-Wallis Test
1407 @vindex KRUSKAL-WALLIS
1409 @cindex Kruskal-Wallis test
1412 [ /KRUSKAL-WALLIS = @var{var_list} BY var (@var{lower}, @var{upper}) ]
1415 The Kruskal-Wallis test is used to compare data from an
1416 arbitrary number of populations. It does not assume normality.
1417 The data to be compared are specified by @var{var_list}.
1418 The categorical variable determining the groups to which the
1419 data belongs is given by @var{var}. The limits @var{lower} and
1420 @var{upper} specify the valid range of @var{var}. Any cases for
1421 which @var{var} falls outside [@var{lower}, @var{upper}] will be
1424 The mean rank of each group as well as the chi-squared value and significance
1425 of the test will be printed.
1426 The abbreviated subcommand @subcmd{K-W} may be used in place of @subcmd{KRUSKAL-WALLIS}.
1430 @subsection Mann-Whitney U Test
1431 @vindex MANN-WHITNEY
1433 @cindex Mann-Whitney U test
1434 @cindex U, Mann-Whitney U
1437 [ /MANN-WHITNEY = @var{var_list} BY var (@var{group1}, @var{group2}) ]
1440 The Mann-Whitney subcommand is used to test whether two groups of data come from different populations.
1441 The variables to be tested should be specified in @var{var_list} and the grouping variable, that determines to which group the test variables belong, in @var{var}.
1442 @var{Var} may be either a string or an alpha variable.
1443 @var{Group1} and @var{group2} specify the
1444 two values of @var{var} which determine the groups of the test data.
1445 Cases for which the @var{var} value is neither @var{group1} or @var{group2} will be ignored.
1447 The value of the Mann-Whitney U statistic, the Wilcoxon W, and the significance will be printed.
1448 The abbreviated subcommand @subcmd{M-W} may be used in place of @subcmd{MANN-WHITNEY}.
1451 @subsection McNemar Test
1453 @cindex McNemar test
1456 [ /MCNEMAR @var{var_list} [ WITH @var{var_list} [ (PAIRED) ]]]
1459 Use McNemar's test to analyse the significance of the difference between
1460 pairs of correlated proportions.
1462 If the @code{WITH} keyword is omitted, then tests for all
1463 combinations of the listed variables are performed.
1464 If the @code{WITH} keyword is given, and the @code{(PAIRED)} keyword
1465 is also given, then the number of variables preceding @code{WITH}
1466 must be the same as the number following it.
1467 In this case, tests for each respective pair of variables are
1469 If the @code{WITH} keyword is given, but the
1470 @code{(PAIRED)} keyword is omitted, then tests for each combination
1471 of variable preceding @code{WITH} against variable following
1472 @code{WITH} are performed.
1474 The data in each variable must be dichotomous. If there are more
1475 than two distinct variables an error will occur and the test will
1479 @subsection Median Test
1484 [ /MEDIAN [(@var{value})] = @var{var_list} BY @var{variable} (@var{value1}, @var{value2}) ]
1487 The median test is used to test whether independent samples come from
1488 populations with a common median.
1489 The median of the populations against which the samples are to be tested
1490 may be given in parentheses immediately after the
1491 @subcmd{/MEDIAN} subcommand. If it is not given, the median will be imputed from the
1492 union of all the samples.
1494 The variables of the samples to be tested should immediately follow the @samp{=} sign. The
1495 keyword @code{BY} must come next, and then the grouping variable. Two values
1496 in parentheses should follow. If the first value is greater than the second,
1497 then a 2 sample test is performed using these two values to determine the groups.
1498 If however, the first variable is less than the second, then a @i{k} sample test is
1499 conducted and the group values used are all values encountered which lie in the
1500 range [@var{value1},@var{value2}].
1504 @subsection Runs Test
1509 [ /RUNS (@{MEAN, MEDIAN, MODE, @var{value}@}) = @var{var_list} ]
1512 The @subcmd{/RUNS} subcommand tests whether a data sequence is randomly ordered.
1514 It works by examining the number of times a variable's value crosses a given threshold.
1515 The desired threshold must be specified within parentheses.
1516 It may either be specified as a number or as one of @subcmd{MEAN}, @subcmd{MEDIAN} or @subcmd{MODE}.
1517 Following the threshold specification comes the list of variables whose values are to be
1520 The subcommand shows the number of runs, the asymptotic significance based on the
1524 @subsection Sign Test
1529 [ /SIGN @var{var_list} [ WITH @var{var_list} [ (PAIRED) ]]]
1532 The @subcmd{/SIGN} subcommand tests for differences between medians of the
1534 The test does not make any assumptions about the
1535 distribution of the data.
1537 If the @code{WITH} keyword is omitted, then tests for all
1538 combinations of the listed variables are performed.
1539 If the @code{WITH} keyword is given, and the @code{(PAIRED)} keyword
1540 is also given, then the number of variables preceding @code{WITH}
1541 must be the same as the number following it.
1542 In this case, tests for each respective pair of variables are
1544 If the @code{WITH} keyword is given, but the
1545 @code{(PAIRED)} keyword is omitted, then tests for each combination
1546 of variable preceding @code{WITH} against variable following
1547 @code{WITH} are performed.
1550 @subsection Wilcoxon Matched Pairs Signed Ranks Test
1552 @cindex wilcoxon matched pairs signed ranks test
1555 [ /WILCOXON @var{var_list} [ WITH @var{var_list} [ (PAIRED) ]]]
1558 The @subcmd{/WILCOXON} subcommand tests for differences between medians of the
1560 The test does not make any assumptions about the variances of the samples.
1561 It does however assume that the distribution is symmetrical.
1563 If the @subcmd{WITH} keyword is omitted, then tests for all
1564 combinations of the listed variables are performed.
1565 If the @subcmd{WITH} keyword is given, and the @subcmd{(PAIRED)} keyword
1566 is also given, then the number of variables preceding @subcmd{WITH}
1567 must be the same as the number following it.
1568 In this case, tests for each respective pair of variables are
1570 If the @subcmd{WITH} keyword is given, but the
1571 @subcmd{(PAIRED)} keyword is omitted, then tests for each combination
1572 of variable preceding @subcmd{WITH} against variable following
1573 @subcmd{WITH} are performed.
1582 /MISSING=@{ANALYSIS,LISTWISE@} @{EXCLUDE,INCLUDE@}
1583 /CRITERIA=CI(@var{confidence})
1587 TESTVAL=@var{test_value}
1588 /VARIABLES=@var{var_list}
1591 (Independent Samples mode.)
1592 GROUPS=var(@var{value1} [, @var{value2}])
1593 /VARIABLES=@var{var_list}
1596 (Paired Samples mode.)
1597 PAIRS=@var{var_list} [WITH @var{var_list} [(PAIRED)] ]
1602 The @cmd{T-TEST} procedure outputs tables used in testing hypotheses about
1604 It operates in one of three modes:
1606 @item One Sample mode.
1607 @item Independent Groups mode.
1612 Each of these modes are described in more detail below.
1613 There are two optional subcommands which are common to all modes.
1615 The @cmd{/CRITERIA} subcommand tells @pspp{} the confidence interval used
1616 in the tests. The default value is 0.95.
1619 The @cmd{MISSING} subcommand determines the handling of missing
1621 If @subcmd{INCLUDE} is set, then user-missing values are included in the
1622 calculations, but system-missing values are not.
1623 If @subcmd{EXCLUDE} is set, which is the default, user-missing
1624 values are excluded as well as system-missing values.
1625 This is the default.
1627 If @subcmd{LISTWISE} is set, then the entire case is excluded from analysis
1628 whenever any variable specified in the @subcmd{/VARIABLES}, @subcmd{/PAIRS} or
1629 @subcmd{/GROUPS} subcommands contains a missing value.
1630 If @subcmd{ANALYSIS} is set, then missing values are excluded only in the analysis for
1631 which they would be needed. This is the default.
1635 * One Sample Mode:: Testing against a hypothesized mean
1636 * Independent Samples Mode:: Testing two independent groups for equal mean
1637 * Paired Samples Mode:: Testing two interdependent groups for equal mean
1640 @node One Sample Mode
1641 @subsection One Sample Mode
1643 The @subcmd{TESTVAL} subcommand invokes the One Sample mode.
1644 This mode is used to test a population mean against a hypothesized
1646 The value given to the @subcmd{TESTVAL} subcommand is the value against
1647 which you wish to test.
1648 In this mode, you must also use the @subcmd{/VARIABLES} subcommand to
1649 tell @pspp{} which variables you wish to test.
1651 @node Independent Samples Mode
1652 @subsection Independent Samples Mode
1654 The @subcmd{GROUPS} subcommand invokes Independent Samples mode or
1656 This mode is used to test whether two groups of values have the
1657 same population mean.
1658 In this mode, you must also use the @subcmd{/VARIABLES} subcommand to
1659 tell @pspp{} the dependent variables you wish to test.
1661 The variable given in the @subcmd{GROUPS} subcommand is the independent
1662 variable which determines to which group the samples belong.
1663 The values in parentheses are the specific values of the independent
1664 variable for each group.
1665 If the parentheses are omitted and no values are given, the default values
1666 of 1.0 and 2.0 are assumed.
1668 If the independent variable is numeric,
1669 it is acceptable to specify only one value inside the parentheses.
1670 If you do this, cases where the independent variable is
1671 greater than or equal to this value belong to the first group, and cases
1672 less than this value belong to the second group.
1673 When using this form of the @subcmd{GROUPS} subcommand, missing values in
1674 the independent variable are excluded on a listwise basis, regardless
1675 of whether @subcmd{/MISSING=LISTWISE} was specified.
1678 @node Paired Samples Mode
1679 @subsection Paired Samples Mode
1681 The @cmd{PAIRS} subcommand introduces Paired Samples mode.
1682 Use this mode when repeated measures have been taken from the same
1684 If the @subcmd{WITH} keyword is omitted, then tables for all
1685 combinations of variables given in the @cmd{PAIRS} subcommand are
1687 If the @subcmd{WITH} keyword is given, and the @subcmd{(PAIRED)} keyword
1688 is also given, then the number of variables preceding @subcmd{WITH}
1689 must be the same as the number following it.
1690 In this case, tables for each respective pair of variables are
1692 In the event that the @subcmd{WITH} keyword is given, but the
1693 @subcmd{(PAIRED)} keyword is omitted, then tables for each combination
1694 of variable preceding @subcmd{WITH} against variable following
1695 @subcmd{WITH} are generated.
1702 @cindex analysis of variance
1707 [/VARIABLES = ] @var{var_list} BY @var{var}
1708 /MISSING=@{ANALYSIS,LISTWISE@} @{EXCLUDE,INCLUDE@}
1709 /CONTRAST= @var{value1} [, @var{value2}] ... [,@var{valueN}]
1710 /STATISTICS=@{DESCRIPTIVES,HOMOGENEITY@}
1711 /POSTHOC=@{BONFERRONI, GH, LSD, SCHEFFE, SIDAK, TUKEY, ALPHA ([@var{value}])@}
1714 The @cmd{ONEWAY} procedure performs a one-way analysis of variance of
1715 variables factored by a single independent variable.
1716 It is used to compare the means of a population
1717 divided into more than two groups.
1719 The dependent variables to be analysed should be given in the @subcmd{VARIABLES}
1721 The list of variables must be followed by the @subcmd{BY} keyword and
1722 the name of the independent (or factor) variable.
1724 You can use the @subcmd{STATISTICS} subcommand to tell @pspp{} to display
1725 ancillary information. The options accepted are:
1728 Displays descriptive statistics about the groups factored by the independent
1731 Displays the Levene test of Homogeneity of Variance for the
1732 variables and their groups.
1735 The @subcmd{CONTRAST} subcommand is used when you anticipate certain
1736 differences between the groups.
1737 The subcommand must be followed by a list of numerals which are the
1738 coefficients of the groups to be tested.
1739 The number of coefficients must correspond to the number of distinct
1740 groups (or values of the independent variable).
1741 If the total sum of the coefficients are not zero, then @pspp{} will
1742 display a warning, but will proceed with the analysis.
1743 The @subcmd{CONTRAST} subcommand may be given up to 10 times in order
1744 to specify different contrast tests.
1745 The @subcmd{MISSING} subcommand defines how missing values are handled.
1746 If @subcmd{LISTWISE} is specified then cases which have missing values for
1747 the independent variable or any dependent variable will be ignored.
1748 If @subcmd{ANALYSIS} is specified, then cases will be ignored if the independent
1749 variable is missing or if the dependent variable currently being
1750 analysed is missing. The default is @subcmd{ANALYSIS}.
1751 A setting of @subcmd{EXCLUDE} means that variables whose values are
1752 user-missing are to be excluded from the analysis. A setting of
1753 @subcmd{INCLUDE} means they are to be included. The default is @subcmd{EXCLUDE}.
1755 Using the @code{POSTHOC} subcommand you can perform multiple
1756 pairwise comparisons on the data. The following comparison methods
1760 Least Significant Difference.
1761 @item @subcmd{TUKEY}
1762 Tukey Honestly Significant Difference.
1763 @item @subcmd{BONFERRONI}
1765 @item @subcmd{SCHEFFE}
1767 @item @subcmd{SIDAK}
1770 The Games-Howell test.
1774 The optional syntax @code{ALPHA(@var{value})} is used to indicate
1775 that @var{value} should be used as the
1776 confidence level for which the posthoc tests will be performed.
1777 The default is 0.05.
1780 @section QUICK CLUSTER
1781 @vindex QUICK CLUSTER
1783 @cindex K-means clustering
1787 QUICK CLUSTER @var{var_list}
1788 [/CRITERIA=CLUSTERS(@var{k}) [MXITER(@var{max_iter})] CONVERGE(@var{epsilon}) [NOINITIAL]]
1789 [/MISSING=@{EXCLUDE,INCLUDE@} @{LISTWISE, PAIRWISE@}]
1790 [/PRINT=@{INITIAL@} @{CLUSTER@}]
1793 The @cmd{QUICK CLUSTER} command performs k-means clustering on the
1794 dataset. This is useful when you wish to allocate cases into clusters
1795 of similar values and you already know the number of clusters.
1797 The minimum specification is @samp{QUICK CLUSTER} followed by the names
1798 of the variables which contain the cluster data. Normally you will also
1799 want to specify @subcmd{/CRITERIA=CLUSTERS(@var{k})} where @var{k} is the
1800 number of clusters. If this is not specified, then @var{k} defaults to 2.
1802 If you use @subcmd{/CRITERIA=NOINITIAL} then a naive algorithm to select
1803 the initial clusters is used. This will provide for faster execution but
1804 less well separated initial clusters and hence possibly an inferior final
1808 @cmd{QUICK CLUSTER} uses an iterative algorithm to select the clusters centers.
1809 The subcommand @subcmd{/CRITERIA=MXITER(@var{max_iter})} sets the maximum number of iterations.
1810 During classification, @pspp{} will continue iterating until until @var{max_iter}
1811 iterations have been done or the convergence criterion (see below) is fulfilled.
1812 The default value of @var{max_iter} is 2.
1814 If however, you specify @subcmd{/CRITERIA=NOUPDATE} then after selecting the initial centers,
1815 no further update to the cluster centers is done. In this case, @var{max_iter}, if specified.
1818 The subcommand @subcmd{/CRITERIA=CONVERGE(@var{epsilon})} is used
1819 to set the convergence criterion. The value of convergence criterion is @var{epsilon}
1820 times the minimum distance between the @emph{initial} cluster centers. Iteration stops when
1821 the mean cluster distance between one iteration and the next
1822 is less than the convergence criterion. The default value of @var{epsilon} is zero.
1824 The @subcmd{MISSING} subcommand determines the handling of missing variables.
1825 If @subcmd{INCLUDE} is set, then user-missing values are considered at their face
1826 value and not as missing values.
1827 If @subcmd{EXCLUDE} is set, which is the default, user-missing
1828 values are excluded as well as system-missing values.
1830 If @subcmd{LISTWISE} is set, then the entire case is excluded from the analysis
1831 whenever any of the clustering variables contains a missing value.
1832 If @subcmd{PAIRWISE} is set, then a case is considered missing only if all the
1833 clustering variables contain missing values. Otherwise it is clustered
1834 on the basis of the non-missing values.
1835 The default is @subcmd{LISTWISE}.
1837 The @subcmd{PRINT} subcommand requests additional output to be printed.
1838 If @subcmd{INITIAL} is set, then the initial cluster memberships will
1840 If @subcmd{CLUSTER} is set, the cluster memberships of the individual
1841 cases will be displayed (potentially generating lengthy output).
1850 [VARIABLES=] @var{var_list} [@{A,D@}] [BY @var{var_list}]
1851 /TIES=@{MEAN,LOW,HIGH,CONDENSE@}
1852 /FRACTION=@{BLOM,TUKEY,VW,RANKIT@}
1854 /MISSING=@{EXCLUDE,INCLUDE@}
1856 /RANK [INTO @var{var_list}]
1857 /NTILES(k) [INTO @var{var_list}]
1858 /NORMAL [INTO @var{var_list}]
1859 /PERCENT [INTO @var{var_list}]
1860 /RFRACTION [INTO @var{var_list}]
1861 /PROPORTION [INTO @var{var_list}]
1862 /N [INTO @var{var_list}]
1863 /SAVAGE [INTO @var{var_list}]
1866 The @cmd{RANK} command ranks variables and stores the results into new
1869 The @subcmd{VARIABLES} subcommand, which is mandatory, specifies one or
1870 more variables whose values are to be ranked.
1871 After each variable, @samp{A} or @samp{D} may appear, indicating that
1872 the variable is to be ranked in ascending or descending order.
1873 Ascending is the default.
1874 If a @subcmd{BY} keyword appears, it should be followed by a list of variables
1875 which are to serve as group variables.
1876 In this case, the cases are gathered into groups, and ranks calculated
1879 The @subcmd{TIES} subcommand specifies how tied values are to be treated. The
1880 default is to take the mean value of all the tied cases.
1882 The @subcmd{FRACTION} subcommand specifies how proportional ranks are to be
1883 calculated. This only has any effect if @subcmd{NORMAL} or @subcmd{PROPORTIONAL} rank
1884 functions are requested.
1886 The @subcmd{PRINT} subcommand may be used to specify that a summary of the rank
1887 variables created should appear in the output.
1889 The function subcommands are @subcmd{RANK}, @subcmd{NTILES}, @subcmd{NORMAL}, @subcmd{PERCENT}, @subcmd{RFRACTION},
1890 @subcmd{PROPORTION} and @subcmd{SAVAGE}. Any number of function subcommands may appear.
1891 If none are given, then the default is RANK.
1892 The @subcmd{NTILES} subcommand must take an integer specifying the number of
1893 partitions into which values should be ranked.
1894 Each subcommand may be followed by the @subcmd{INTO} keyword and a list of
1895 variables which are the variables to be created and receive the rank
1896 scores. There may be as many variables specified as there are
1897 variables named on the @subcmd{VARIABLES} subcommand. If fewer are specified,
1898 then the variable names are automatically created.
1900 The @subcmd{MISSING} subcommand determines how user missing values are to be
1901 treated. A setting of @subcmd{EXCLUDE} means that variables whose values are
1902 user-missing are to be excluded from the rank scores. A setting of
1903 @subcmd{INCLUDE} means they are to be included. The default is @subcmd{EXCLUDE}.
1905 @include regression.texi
1909 @section RELIABILITY
1914 /VARIABLES=@var{var_list}
1915 /SCALE (@var{name}) = @{@var{var_list}, ALL@}
1916 /MODEL=@{ALPHA, SPLIT[(@var{n})]@}
1917 /SUMMARY=@{TOTAL,ALL@}
1918 /MISSING=@{EXCLUDE,INCLUDE@}
1921 @cindex Cronbach's Alpha
1922 The @cmd{RELIABILITY} command performs reliability analysis on the data.
1924 The @subcmd{VARIABLES} subcommand is required. It determines the set of variables
1925 upon which analysis is to be performed.
1927 The @subcmd{SCALE} subcommand determines which variables reliability is to be
1928 calculated for. If it is omitted, then analysis for all variables named
1929 in the @subcmd{VARIABLES} subcommand will be used.
1930 Optionally, the @var{name} parameter may be specified to set a string name
1933 The @subcmd{MODEL} subcommand determines the type of analysis. If @subcmd{ALPHA} is specified,
1934 then Cronbach's Alpha is calculated for the scale. If the model is @subcmd{SPLIT},
1935 then the variables are divided into 2 subsets. An optional parameter
1936 @var{n} may be given, to specify how many variables to be in the first subset.
1937 If @var{n} is omitted, then it defaults to one half of the variables in the
1938 scale, or one half minus one if there are an odd number of variables.
1939 The default model is @subcmd{ALPHA}.
1941 By default, any cases with user missing, or system missing values for
1943 in the @subcmd{VARIABLES} subcommand will be omitted from analysis.
1944 The @subcmd{MISSING} subcommand determines whether user missing values are to
1945 be included or excluded in the analysis.
1947 The @subcmd{SUMMARY} subcommand determines the type of summary analysis to be performed.
1948 Currently there is only one type: @subcmd{SUMMARY=TOTAL}, which displays per-item
1949 analysis tested against the totals.
1957 @cindex Receiver Operating Characteristic
1958 @cindex Area under curve
1961 ROC @var{var_list} BY @var{state_var} (@var{state_value})
1962 /PLOT = @{ CURVE [(REFERENCE)], NONE @}
1963 /PRINT = [ SE ] [ COORDINATES ]
1964 /CRITERIA = [ CUTOFF(@{INCLUDE,EXCLUDE@}) ]
1965 [ TESTPOS (@{LARGE,SMALL@}) ]
1966 [ CI (@var{confidence}) ]
1967 [ DISTRIBUTION (@{FREE, NEGEXPO @}) ]
1968 /MISSING=@{EXCLUDE,INCLUDE@}
1972 The @cmd{ROC} command is used to plot the receiver operating characteristic curve
1973 of a dataset, and to estimate the area under the curve.
1974 This is useful for analysing the efficacy of a variable as a predictor of a state of nature.
1976 The mandatory @var{var_list} is the list of predictor variables.
1977 The variable @var{state_var} is the variable whose values represent the actual states,
1978 and @var{state_value} is the value of this variable which represents the positive state.
1980 The optional subcommand @subcmd{PLOT} is used to determine if and how the @subcmd{ROC} curve is drawn.
1981 The keyword @subcmd{CURVE} means that the @subcmd{ROC} curve should be drawn, and the optional keyword @subcmd{REFERENCE},
1982 which should be enclosed in parentheses, says that the diagonal reference line should be drawn.
1983 If the keyword @subcmd{NONE} is given, then no @subcmd{ROC} curve is drawn.
1984 By default, the curve is drawn with no reference line.
1986 The optional subcommand @subcmd{PRINT} determines which additional tables should be printed.
1987 Two additional tables are available.
1988 The @subcmd{SE} keyword says that standard error of the area under the curve should be printed as well as
1990 In addition, a p-value under the null hypothesis that the area under the curve equals 0.5 will be
1992 The @subcmd{COORDINATES} keyword says that a table of coordinates of the @subcmd{ROC} curve should be printed.
1994 The @subcmd{CRITERIA} subcommand has four optional parameters:
1996 @item The @subcmd{TESTPOS} parameter may be @subcmd{LARGE} or @subcmd{SMALL}.
1997 @subcmd{LARGE} is the default, and says that larger values in the predictor variables are to be
1998 considered positive. @subcmd{SMALL} indicates that smaller values should be considered positive.
2000 @item The @subcmd{CI} parameter specifies the confidence interval that should be printed.
2001 It has no effect if the @subcmd{SE} keyword in the @subcmd{PRINT} subcommand has not been given.
2003 @item The @subcmd{DISTRIBUTION} parameter determines the method to be used when estimating the area
2005 There are two possibilities, @i{viz}: @subcmd{FREE} and @subcmd{NEGEXPO}.
2006 The @subcmd{FREE} method uses a non-parametric estimate, and the @subcmd{NEGEXPO} method a bi-negative
2007 exponential distribution estimate.
2008 The @subcmd{NEGEXPO} method should only be used when the number of positive actual states is
2009 equal to the number of negative actual states.
2010 The default is @subcmd{FREE}.
2012 @item The @subcmd{CUTOFF} parameter is for compatibility and is ignored.
2015 The @subcmd{MISSING} subcommand determines whether user missing values are to
2016 be included or excluded in the analysis. The default behaviour is to
2018 Cases are excluded on a listwise basis; if any of the variables in @var{var_list}
2019 or if the variable @var{state_var} is missing, then the entire case will be
2022 @c LocalWords: subcmd subcommand