SESKEWNESS,SEKURTOSIS,ALL,NONE@}
/NTILES=@var{ntiles}
/PERCENTILES=percent@dots{}
- /HISTOGRAM=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
+ /HISTOGRAM=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
[@{FREQ[(@var{y_max})],PERCENT[(@var{y_max})]@}] [@{NONORMAL,NORMAL@}]
/PIECHART=[MINIMUM(@var{x_min})] [MAXIMUM(@var{x_max})]
[@{FREQ,PERCENT@}] [@{NOMISSING,MISSING@}]
variables to be analyzed.
The @subcmd{FORMAT} subcommand controls the output format. It has several
-possible settings:
+possible settings:
@itemize @subcmd{}
@item
are included. System-missing values are never included in statistics,
but are listed in frequency tables.
-The available @subcmd{STATISTICS} are the same as available
-in @cmd{DESCRIPTIVES} (@pxref{DESCRIPTIVES}), with the addition
+The available @subcmd{STATISTICS} are the same as available
+in @cmd{DESCRIPTIVES} (@pxref{DESCRIPTIVES}), with the addition
of @subcmd{MEDIAN}, the data's median
value, and MODE, the mode. (If there are multiple modes, the smallest
value is reported.) By default, the mean, standard deviation of the
@cindex percentiles
@subcmd{PERCENTILES} causes the specified percentiles to be reported.
The percentiles should be presented at a list of numbers between 0
-and 100 inclusive.
+and 100 inclusive.
The @subcmd{NTILES} subcommand causes the percentiles to be reported at the
boundaries of the data set divided into the specified number of ranges.
For instance, @subcmd{/NTILES=4} would cause quartiles to be reported.
The @subcmd{HISTOGRAM} subcommand causes the output to include a histogram for
each specified numeric variable. The X axis by default ranges from
the minimum to the maximum value observed in the data, but the @subcmd{MINIMUM}
-and @subcmd{MAXIMUM} keywords can set an explicit range.
+and @subcmd{MAXIMUM} keywords can set an explicit range.
@footnote{The number of
bins is chosen according to the Freedman-Diaconis rule:
@math{2 \times IQR(x)n^{-1/3}}, where @math{IQR(x)} is the interquartile range of @math{x}
The @subcmd{PIECHART} subcommand adds a pie chart for each variable to the data. Each
slice represents one value, with the size of the slice proportional to
the value's frequency. By default, all non-missing values are given
-slices.
+slices.
The @subcmd{MINIMUM} and @subcmd{MAXIMUM} keywords can be used to limit the
-displayed slices to a given range of values.
+displayed slices to a given range of values.
The keyword @subcmd{NOMISSING} causes missing values to be omitted from the
piechart. This is the default.
If instead, @subcmd{MISSING} is specified, then a single slice
of each category, whereas the @subcmd{PERCENT} option will display relative
percentages.
-The @subcmd{FREQ} and @subcmd{PERCENT} options on @subcmd{HISTOGRAM} and
+The @subcmd{FREQ} and @subcmd{PERCENT} options on @subcmd{HISTOGRAM} and
@subcmd{PIECHART} are accepted but not currently honoured.
The @subcmd{ORDER} subcommand is accepted but ignored.
/ID=@var{identity_variable}
/@{TOTAL,NOTOTAL@}
/PERCENTILE=[@var{percentiles}]=@{HAVERAGE, WAVERAGE, ROUND, AEMPIRICAL, EMPIRICAL @}
- /MISSING=@{LISTWISE, PAIRWISE@} [@{EXCLUDE, INCLUDE@}]
+ /MISSING=@{LISTWISE, PAIRWISE@} [@{EXCLUDE, INCLUDE@}]
[@{NOREPORT,REPORT@}]
@end display
In particular, it is useful for testing how closely a distribution follows a
normal distribution, and for finding outliers and extreme values.
-The @subcmd{VARIABLES} subcommand is mandatory.
+The @subcmd{VARIABLES} subcommand is mandatory.
It specifies the dependent variables and optionally variables to use as
factors for the analysis.
-Variables listed before the first @subcmd{BY} keyword (if any) are the
+Variables listed before the first @subcmd{BY} keyword (if any) are the
dependent variables.
The dependent variables may optionally be followed by a list of
factors which tell @pspp{} how to break down the analysis for each
-dependent variable.
+dependent variable.
Following the dependent variables, factors may be specified.
The factors (if desired) should be preceded by a single @subcmd{BY} keyword.
-The format for each factor is
+The format for each factor is
@display
@var{factorvar} [BY @var{subfactorvar}].
@end display
The @subcmd{PLOT} subcommand specifies which plots are to be produced if any.
Available plots are @subcmd{HISTOGRAM}, @subcmd{NPPLOT}, @subcmd{BOXPLOT} and
@subcmd{SPREADLEVEL}.
-The first three can be used to visualise how closely each cell conforms to a
+The first three can be used to visualise how closely each cell conforms to a
normal distribution, whilst the spread vs.@: level plot can be useful to visualise
how the variance of differs between factors.
Boxplots will also show you the outliers and extreme values.
bins, as approximately @math{1 + \log2(n)}, where @math{n} is the number of samples.
Note that @cmd{FREQUENCIES} uses a different algorithm to find the bin size.}
-The @subcmd{SPREADLEVEL} plot displays the interquartile range versus the
+The @subcmd{SPREADLEVEL} plot displays the interquartile range versus the
median. It takes an optional parameter @var{t}, which specifies how the data
should be transformed prior to plotting.
The given value @var{t} is a power to which the data is raised. For example, if
@var{t} is given as 2, then the data will be squared.
-Zero, however is a special value. If @var{t} is 0 or
+Zero, however is a special value. If @var{t} is 0 or
is omitted, then data will be transformed by taking its natural logarithm instead of
raising to the power of @var{t}.
@item The cumulative weight value must be in the range [3, 5000]
@end itemize
-The @subcmd{COMPARE} subcommand is only relevant if producing boxplots, and it is only
+The @subcmd{COMPARE} subcommand is only relevant if producing boxplots, and it is only
useful there is more than one dependent variable and at least one factor.
-If
+If
@subcmd{/COMPARE=GROUPS} is specified, then one plot per dependent variable is produced,
each of which contain boxplots for all the cells.
If @subcmd{/COMPARE=VARIABLES} is specified, then one plot per cell is produced,
each containing one boxplot per dependent variable.
If the @subcmd{/COMPARE} subcommand is omitted, then @pspp{} behaves as if
@subcmd{/COMPARE=GROUPS} were given.
-
-The @subcmd{ID} subcommand is relevant only if @subcmd{/PLOT=BOXPLOT} or
+
+The @subcmd{ID} subcommand is relevant only if @subcmd{/PLOT=BOXPLOT} or
@subcmd{/STATISTICS=EXTREME} has been given.
If given, it should provide the name of a variable which is to be used
to labels extreme values and outliers.
-Numeric or string variables are permissible.
+Numeric or string variables are permissible.
If the @subcmd{ID} subcommand is not given, then the case number will be used for
labelling.
calculation of the descriptives command. The default is 95%.
@cindex percentiles
-The @subcmd{PERCENTILES} subcommand specifies which percentiles are to be calculated,
+The @subcmd{PERCENTILES} subcommand specifies which percentiles are to be calculated,
and which algorithm to use for calculating them. The default is to
calculate the 5, 10, 25, 50, 75, 90, 95 percentiles using the
@subcmd{HAVERAGE} algorithm.
distinct value
of @var{gender} @emph{and} for each distinct combination of the values
of @var{gender} and @var{race}.
-Since the @subcmd{NOTOTAL} keyword is given, statistics and histograms for
+Since the @subcmd{NOTOTAL} keyword is given, statistics and histograms for
@var{score1} and @var{score2} covering the whole dataset are not produced.
@example
-EXAMINE @var{score1} @var{score2} BY
+EXAMINE @var{score1} @var{score2} BY
@var{gender}
@var{gender} BY @var{culture}
/STATISTICS = DESCRIPTIVES
Here is a second example showing how the @cmd{examine} command can be used to find extremities.
@example
-EXAMINE @var{height} @var{weight} BY
+EXAMINE @var{height} @var{weight} BY
@var{gender}
/STATISTICS = EXTREME (3)
/PLOT = BOXPLOT
@end example
In this example, we look at the height and weight of a sample of individuals and
how they differ between male and female.
-A table showing the 3 largest and the 3 smallest values of @var{height} and
+A table showing the 3 largest and the 3 smallest values of @var{height} and
@var{weight} for each gender, and for the whole dataset will be shown.
Boxplots will also be produced.
Because @subcmd{/COMPARE = GROUPS} was given, boxplots for male and female will be
GRAPH
/HISTOGRAM [(NORMAL)]= @var{var}
/SCATTERPLOT [(BIVARIATE)] = @var{var1} WITH @var{var2} [BY @var{var3}]
- /BAR = @{@var{summary-function}(@var{var1}) | @var{count-function}@} BY @var{var2} [BY @var{var3}]
- [ /MISSING=@{LISTWISE, VARIABLE@} [@{EXCLUDE, INCLUDE@}] ]
+ /BAR = @{@var{summary-function}(@var{var1}) | @var{count-function}@} BY @var{var2} [BY @var{var3}]
+ [ /MISSING=@{LISTWISE, VARIABLE@} [@{EXCLUDE, INCLUDE@}] ]
[@{NOREPORT,REPORT@}]
@end display
-The @cmd{GRAPH} produces graphical plots of data. Only one of the subcommands
+The @cmd{GRAPH} produces graphical plots of data. Only one of the subcommands
@subcmd{HISTOGRAM} or @subcmd{SCATTERPLOT} can be specified, i.e. only one plot
-can be produced per call of @cmd{GRAPH}. The @subcmd{MISSING} is optional.
+can be produced per call of @cmd{GRAPH}. The @subcmd{MISSING} is optional.
@menu
* SCATTERPLOT:: Cartesian Plots
following is an example for producing a scatterplot.
@example
-GRAPH
+GRAPH
/SCATTERPLOT = @var{height} WITH @var{weight} BY @var{gender}.
@end example
following example produces a histogram plot for the variable @var{weight}.
@example
-GRAPH
+GRAPH
/HISTOGRAM = @var{weight}.
@end example
[ /PRINT=@{TWOTAIL, ONETAIL@} @{SIG, NOSIG@} ]
[ /STATISTICS=DESCRIPTIVES XPROD ALL]
[ /MISSING=@{PAIRWISE, LISTWISE@} @{INCLUDE, EXCLUDE@} ]
-@end display
+@end display
@cindex correlation
The @cmd{CORRELATIONS} procedure produces tables of the Pearson correlation coefficient
for a set of variables. The significance of the coefficients are also given.
-At least one @subcmd{VARIABLES} subcommand is required. If the @subcmd{WITH}
+At least one @subcmd{VARIABLES} subcommand is required. If the @subcmd{WITH}
keyword is used, then a non-square correlation table will be produced.
The variables preceding @subcmd{WITH}, will be used as the rows of the table,
and the variables following will be the columns of the table.
If no @subcmd{WITH} subcommand is given, then a square, symmetrical table using all variables is produced.
-The @cmd{MISSING} subcommand determines the handling of missing variables.
+The @cmd{MISSING} subcommand determines the handling of missing variables.
If @subcmd{INCLUDE} is set, then user-missing values are included in the
calculations, but system-missing values are not.
If @subcmd{EXCLUDE} is set, which is the default, user-missing
-values are excluded as well as system-missing values.
+values are excluded as well as system-missing values.
If @subcmd{LISTWISE} is set, then the entire case is excluded from analysis
whenever any variable specified in any @cmd{/VARIABLES} subcommand
-contains a missing value.
+contains a missing value.
If @subcmd{PAIRWISE} is set, then a case is considered missing only if either of the
values for the particular coefficient are missing.
The default is @subcmd{PAIRWISE}.
The @subcmd{PRINT} subcommand is used to control how the reported significance values are printed.
-If the @subcmd{TWOTAIL} option is used, then a two-tailed test of significance is
+If the @subcmd{TWOTAIL} option is used, then a two-tailed test of significance is
printed. If the @subcmd{ONETAIL} option is given, then a one-tailed test is used.
The default is @subcmd{TWOTAIL}.
If @subcmd{SIG} is specified, then no highlighting is performed. This is the default.
@cindex covariance
-The @subcmd{STATISTICS} subcommand requests additional statistics to be displayed. The keyword
+The @subcmd{STATISTICS} subcommand requests additional statistics to be displayed. The keyword
@subcmd{DESCRIPTIVES} requests that the mean, number of non-missing cases, and the non-biased
estimator of the standard deviation are displayed.
These statistics will be displayed in a separated table, for all the variables listed
in any @subcmd{/VARIABLES} subcommand.
-The @subcmd{XPROD} keyword requests cross-product deviations and covariance estimators to
+The @subcmd{XPROD} keyword requests cross-product deviations and covariance estimators to
be displayed for each pair of variables.
The keyword @subcmd{ALL} is the union of @subcmd{DESCRIPTIVES} and @subcmd{XPROD}.
/STATISTICS=@{CHISQ,PHI,CC,LAMBDA,UC,BTAU,CTAU,RISK,GAMMA,D,
KAPPA,ETA,CORR,ALL,NONE@}
/BARCHART
-
+
(Integer mode.)
/VARIABLES=@var{var_list} (@var{low},@var{high})@dots{}
@end display
number of dimensions is permitted, and any number of variables per
dimension is allowed. The @subcmd{TABLES} subcommand may be repeated as many
times as needed. This is the only required subcommand in @dfn{general
-mode}.
+mode}.
Occasionally, one may want to invoke a special mode called @dfn{integer
mode}. Normally, in general mode, @pspp{} automatically determines
Table percent.
@item EXPECTED
Expected value.
-@item RESIDUAL
+@item RESIDUAL
Residual.
@item SRESIDUAL
Standardized residual.
@end table
@samp{/CELLS} without any settings specified requests @subcmd{COUNT}, @subcmd{ROW},
-@subcmd{COLUMN}, and @subcmd{TOTAL}.
+@subcmd{COLUMN}, and @subcmd{TOTAL}.
If @subcmd{CELLS} is not specified at all then only @subcmd{COUNT}
will be selected.
@cindex bar chart
The @samp{/BARCHART} subcommand produces a clustered bar chart for the first two
variables on each table.
-If a table has more than two variables, the counts for the third and subsequent levels
-will be aggregated and the chart will be produces as if there were only two variables.
+If a table has more than two variables, the counts for the third and subsequent levels
+will be aggregated and the chart will be produces as if there were only two variables.
@strong{Please note:} Currently the implementation of @cmd{CROSSTABS} has the
[ /ANALYSIS=@var{var_list} ]
- [ /EXTRACTION=@{PC, PAF@}]
+ [ /EXTRACTION=@{PC, PAF@}]
[ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, PROMAX[(@var{k})], NOROTATE@}]
format of the file.
The @subcmd{/EXTRACTION} subcommand is used to specify the way in which factors (components) are extracted from the data.
-If @subcmd{PC} is specified, then Principal Components Analysis is used.
+If @subcmd{PC} is specified, then Principal Components Analysis is used.
If @subcmd{PAF} is specified, then Principal Axis Factoring is
used. By default Principal Components Analysis will be used.
The @subcmd{/ROTATION} subcommand is used to specify the method by which the extracted solution will be rotated.
-Three orthogonal rotation methods are available:
+Three orthogonal rotation methods are available:
@subcmd{VARIMAX} (which is the default), @subcmd{EQUAMAX}, and @subcmd{QUARTIMAX}.
There is one oblique rotation method, @i{viz}: @subcmd{PROMAX}.
Optionally you may enter the power of the promax rotation @var{k}, which must be enclosed in parentheses.
The default value of @var{k} is 5.
If you don't want any rotation to be performed, the word @subcmd{NOROTATE} will prevent the command from performing any
-rotation on the data.
+rotation on the data.
The @subcmd{/METHOD} subcommand should be used to determine whether the covariance matrix or the correlation matrix of the data is
to be analysed. By default, the correlation matrix is analysed.
The @subcmd{/PRINT} subcommand may be used to select which features of the analysis are reported:
-@itemize
+@itemize
@item @subcmd{UNIVARIATE}
A table of mean values, standard deviations and total weights are printed.
@item @subcmd{INITIAL}
The @subcmd{/FORMAT} subcommand determined how data are to be displayed in loading matrices. If @subcmd{SORT} is specified, then the variables
are sorted in descending order of significance. If @subcmd{BLANK(@var{n})} is specified, then coefficients whose absolute value is less
-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
+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
performed, and all coefficients will be printed.
The @subcmd{/CRITERIA} subcommand is used to specify how the number of extracted factors (components) are chosen.
If @subcmd{FACTORS(@var{n})} is
specified, where @var{n} is an integer, then @var{n} factors will be extracted. Otherwise, the @subcmd{MINEIGEN} setting will
-be used.
+be used.
@subcmd{MINEIGEN(@var{l})} requests that all factors whose eigenvalues are greater than or equal to @var{l} are extracted.
-The default value of @var{l} is 1.
+The default value of @var{l} is 1.
The @subcmd{ECONVERGE} setting has effect only when iterative algorithms for factor
-extraction (such as Principal Axis Factoring) are used.
+extraction (such as Principal Axis Factoring) are used.
@subcmd{ECONVERGE(@var{delta})} specifies that
iteration should cease when
the maximum absolute value of the communality estimate between one iteration and the previous is less than @var{delta}. The
default value of @var{delta} is 0.001.
-The @subcmd{ITERATE(@var{m})} may appear any number of times and is used for two different purposes.
+The @subcmd{ITERATE(@var{m})} may appear any number of times and is used for two different purposes.
It is used to set the maximum number of iterations (@var{m}) for convergence and also to set the maximum number of iterations
for rotation.
Whether it affects convergence or rotation depends upon which subcommand follows the @subcmd{ITERATE} subcommand.
-If @subcmd{EXTRACTION} follows, it affects convergence.
-If @subcmd{ROTATION} follows, it affects rotation.
+If @subcmd{EXTRACTION} follows, it affects convergence.
+If @subcmd{ROTATION} follows, it affects rotation.
If neither @subcmd{ROTATION} nor @subcmd{EXTRACTION} follow a @subcmd{ITERATE} subcommand it will be ignored.
The default value of @var{m} is 25.
-The @cmd{MISSING} subcommand determines the handling of missing variables.
+The @cmd{MISSING} subcommand determines the handling of missing variables.
If @subcmd{INCLUDE} is set, then user-missing values are included in the
calculations, but system-missing values are not.
If @subcmd{EXCLUDE} is set, which is the default, user-missing
-values are excluded as well as system-missing values.
+values are excluded as well as system-missing values.
This is the default.
If @subcmd{LISTWISE} is set, then the entire case is excluded from analysis
whenever any variable specified in the @cmd{VARIABLES} subcommand
-contains a missing value.
+contains a missing value.
If @subcmd{PAIRWISE} is set, then a case is considered missing only if either of the
values for the particular coefficient are missing.
The default is @subcmd{LISTWISE}.
squares. Available values of @var{type} are 1, 2 and 3. The default is type 3.
You may specify a custom design using the @subcmd{DESIGN} subcommand.
-The design comprises a list of interactions where each interaction is a
+The design comprises a list of interactions where each interaction is a
list of variables separated by a @samp{*}. For example the command
@display
GLM subject BY sex age_group race
The @subcmd{MISSING} subcommand determines the handling of missing
-variables.
+variables.
If @subcmd{INCLUDE} is set then, for the purposes of GLM analysis,
only system-missing values are considered
to be missing; user-missing values are not regarded as missing.
If @subcmd{EXCLUDE} is set, which is the default, then user-missing
-values are considered to be missing as well as system-missing values.
+values are considered to be missing as well as system-missing values.
A case for which any dependent variable or any factor
variable has a missing value is excluded from the analysis.
By default, a constant term is included in the model.
Hence, the full model is
@math{
-{\bf y}
-= b_0 + b_1 {\bf x_1}
-+ b_2 {\bf x_2}
+{\bf y}
+= b_0 + b_1 {\bf x_1}
++ b_2 {\bf x_2}
+ \dots
+ b_n {\bf x_n}
}
An iterative Newton-Raphson procedure is used to fit the model.
The @subcmd{/CRITERIA} subcommand is used to specify the stopping criteria of the procedure,
and other parameters.
-The value of @var{cut_point} is used in the classification table. It is the
+The value of @var{cut_point} is used in the classification table. It is the
threshold above which predicted values are considered to be 1. Values
of @var{cut_point} must lie in the range [0,1].
During iterations, if any one of the stopping criteria are satisfied, the procedure is
considered complete.
The stopping criteria are:
@itemize
-@item The number of iterations exceeds @var{max_iterations}.
+@item The number of iterations exceeds @var{max_iterations}.
The default value of @var{max_iterations} is 20.
@item The change in the all coefficient estimates are less than @var{min_delta}.
The default value of @var{min_delta} is 0.001.
The @subcmd{PRINT} subcommand controls the display of optional statistics.
-Currently there is one such option, @subcmd{CI}, which indicates that the
+Currently there is one such option, @subcmd{CI}, which indicates that the
confidence interval of the odds ratio should be displayed as well as its value.
@subcmd{CI} should be followed by an integer in parentheses, to indicate the
confidence level of the desired confidence interval.
The @subcmd{MISSING} subcommand determines the handling of missing
-variables.
+variables.
If @subcmd{INCLUDE} is set, then user-missing values are included in the
calculations, but system-missing values are not.
If @subcmd{EXCLUDE} is set, which is the default, user-missing
-values are excluded as well as system-missing values.
+values are excluded as well as system-missing values.
This is the default.
@node MEANS
@vindex MEANS
@cindex means
-@display
-MEANS [TABLES =]
- @{@var{var_list}@}
+@display
+MEANS [TABLES =]
+ @{@var{var_list}@}
[ BY @{@var{var_list}@} [BY @{@var{var_list}@} [BY @{@var{var_list}@} @dots{} ]]]
- [ /@{@var{var_list}@}
+ [ /@{@var{var_list}@}
[ BY @{@var{var_list}@} [BY @{@var{var_list}@} [BY @{@var{var_list}@} @dots{} ]]] ]
[/CELLS = [MEAN] [COUNT] [STDDEV] [SEMEAN] [SUM] [MIN] [MAX] [RANGE]
- [VARIANCE] [KURT] [SEKURT]
- [SKEW] [SESKEW] [FIRST] [LAST]
- [HARMONIC] [GEOMETRIC]
+ [VARIANCE] [KURT] [SEKURT]
+ [SKEW] [SESKEW] [FIRST] [LAST]
+ [HARMONIC] [GEOMETRIC]
[DEFAULT]
[ALL]
[NONE] ]
[/MISSING = [INCLUDE] [DEPENDENT]]
-@end display
+@end display
You can use the @cmd{MEANS} command to calculate the arithmetic mean and similar
statistics, either for the dataset as a whole or for categories of data.
@end itemize
-More than one @dfn{table} can be specified in a single command.
+More than one @dfn{table} can be specified in a single command.
Each table is separated by a @samp{/}. For
example
@example
has three tables (the @samp{TABLE =} is optional).
The first table has three dependent variables @var{c}, @var{d} and @var{e}
and a single categorical variable @var{x}.
-The second table has two dependent variables @var{a} and @var{b},
+The second table has two dependent variables @var{a} and @var{b},
and two categorical variables @var{x} and @var{y}.
The third table has a single dependent variables @var{f}
and a categorical variable formed by the combination of @var{y} and @var{z}.
By default values are omitted from the analysis only if missing values
(either system missing or user missing)
-for any of the variables directly involved in their calculation are
+for any of the variables directly involved in their calculation are
encountered.
This behaviour can be modified with the @subcmd{/MISSING} subcommand.
Three options are possible: @subcmd{TABLE}, @subcmd{INCLUDE} and @subcmd{DEPENDENT}.
value, and not excluded.
@subcmd{/MISSING = DEPENDENT} says that user missing values, in the dependent
-variables should be taken at their face value, however cases which
-have user missing values for the categorical variables should be omitted
+variables should be taken at their face value, however cases which
+have user missing values for the categorical variables should be omitted
from the calculation.
@node NPAR TESTS
@vindex NPAR TESTS
@cindex nonparametric tests
-@display
+@display
NPAR TESTS
-
+
nonparametric test subcommands
.
.
.
-
+
[ /STATISTICS=@{DESCRIPTIVES@} ]
[ /MISSING=@{ANALYSIS, LISTWISE@} @{INCLUDE, EXCLUDE@} ]
[ /METHOD=EXACT [ TIMER [(@var{n})] ] ]
@end display
-@cmd{NPAR TESTS} performs nonparametric tests.
-Non parametric tests make very few assumptions about the distribution of the
+@cmd{NPAR TESTS} performs nonparametric tests.
+Non parametric tests make very few assumptions about the distribution of the
data.
One or more tests may be specified by using the corresponding subcommand.
-If the @subcmd{/STATISTICS} subcommand is also specified, then summary statistics are
+If the @subcmd{/STATISTICS} subcommand is also specified, then summary statistics are
produces for each variable that is the subject of any test.
Certain tests may take a long time to execute, if an exact figure is required.
Therefore, by default asymptotic approximations are used unless the
-subcommand @subcmd{/METHOD=EXACT} is specified.
-Exact tests give more accurate results, but may take an unacceptably long
+subcommand @subcmd{/METHOD=EXACT} is specified.
+Exact tests give more accurate results, but may take an unacceptably long
time to perform. If the @subcmd{TIMER} keyword is used, it sets a maximum time,
after which the test will be abandoned, and a warning message printed.
The time, in minutes, should be specified in parentheses after the @subcmd{TIMER} keyword.
-If the @subcmd{TIMER} keyword is given without this figure, then a default value of 5 minutes
+If the @subcmd{TIMER} keyword is given without this figure, then a default value of 5 minutes
is used.
@vindex BINOMIAL
@cindex binomial test
-@display
+@display
[ /BINOMIAL[(@var{p})]=@var{var_list}[(@var{value1}[, @var{value2})] ] ]
-@end display
+@end display
-The @subcmd{/BINOMIAL} subcommand compares the observed distribution of a dichotomous
+The @subcmd{/BINOMIAL} subcommand compares the observed distribution of a dichotomous
variable with that of a binomial distribution.
-The variable @var{p} specifies the test proportion of the binomial
-distribution.
+The variable @var{p} specifies the test proportion of the binomial
+distribution.
The default value of 0.5 is assumed if @var{p} is omitted.
If a single value appears after the variable list, then that value is
used as the threshold to partition the observed values. Values less
than or equal to the threshold value form the first category. Values
-greater than the threshold form the second category.
+greater than the threshold form the second category.
If two values appear after the variable list, then they will be used
as the values which a variable must take to be in the respective
-category.
-Cases for which a variable takes a value equal to neither of the specified
+category.
+Cases for which a variable takes a value equal to neither of the specified
values, take no part in the test for that variable.
If no values appear, then the variable must assume dichotomous
If the test proportion is equal to 0.5, then a two tailed test is
reported. For any other test proportion, a one tailed test is
-reported.
+reported.
For one tailed tests, if the test proportion is less than
or equal to the observed proportion, then the significance of
observing the observed proportion or more is reported.
If the test proportion is more than the observed proportion, then the
significance of observing the observed proportion or less is reported.
That is to say, the test is always performed in the observed
-direction.
+direction.
@pspp{} uses a very precise approximation to the gamma function to
compute the binomial significance. Thus, exact results are reported
@display
[ /CHISQUARE=@var{var_list}[(@var{lo},@var{hi})] [/EXPECTED=@{EQUAL|@var{f1}, @var{f2} @dots{} @var{fn}@}] ]
-@end display
+@end display
-The @subcmd{/CHISQUARE} subcommand produces a chi-square statistic for the differences
-between the expected and observed frequencies of the categories of a variable.
-Optionally, a range of values may appear after the variable list.
+The @subcmd{/CHISQUARE} subcommand produces a chi-square statistic for the differences
+between the expected and observed frequencies of the categories of a variable.
+Optionally, a range of values may appear after the variable list.
If a range is given, then non integer values are truncated, and values
outside the specified range are excluded from the analysis.
The @subcmd{/EXPECTED} subcommand specifies the expected values of each
-category.
+category.
There must be exactly one non-zero expected value, for each observed
category, or the @subcmd{EQUAL} keyword must be specified.
You may use the notation @subcmd{@var{n}*@var{f}} to specify @var{n}
@end display
The Cochran Q test is used to test for differences between three or more groups.
-The data for @var{var_list} in all cases must assume exactly two distinct values (other than missing values).
+The data for @var{var_list} in all cases must assume exactly two distinct values (other than missing values).
The value of Q will be displayed and its Asymptotic significance based on a chi-square distribution.
[ /KENDALL = @var{var_list} ]
@end display
-The Kendall test investigates whether an arbitrary number of related samples come from the
+The Kendall test investigates whether an arbitrary number of related samples come from the
same population.
It is identical to the Friedman test except that the additional statistic W, Kendall's Coefficient of Concordance is printed.
It has the range [0,1] --- a value of zero indicates no agreement between the samples whereas a value of
[ /KRUSKAL-WALLIS = @var{var_list} BY var (@var{lower}, @var{upper}) ]
@end display
-The Kruskal-Wallis test is used to compare data from an
+The Kruskal-Wallis test is used to compare data from an
arbitrary number of populations. It does not assume normality.
The data to be compared are specified by @var{var_list}.
The categorical variable determining the groups to which the
[ /MEDIAN [(@var{value})] = @var{var_list} BY @var{variable} (@var{value1}, @var{value2}) ]
@end display
-The median test is used to test whether independent samples come from
+The median test is used to test whether independent samples come from
populations with a common median.
The median of the populations against which the samples are to be tested
-may be given in parentheses immediately after the
-@subcmd{/MEDIAN} subcommand. If it is not given, the median will be imputed from the
+may be given in parentheses immediately after the
+@subcmd{/MEDIAN} subcommand. If it is not given, the median will be imputed from the
union of all the samples.
The variables of the samples to be tested should immediately follow the @samp{=} sign. The
@vindex RUNS
@cindex runs test
-@display
+@display
[ /RUNS (@{MEAN, MEDIAN, MODE, @var{value}@}) = @var{var_list} ]
@end display
The @subcmd{/RUNS} subcommand tests whether a data sequence is randomly ordered.
-It works by examining the number of times a variable's value crosses a given threshold.
+It works by examining the number of times a variable's value crosses a given threshold.
The desired threshold must be specified within parentheses.
It may either be specified as a number or as one of @subcmd{MEAN}, @subcmd{MEDIAN} or @subcmd{MODE}.
Following the threshold specification comes the list of variables whose values are to be
[ /SIGN @var{var_list} [ WITH @var{var_list} [ (PAIRED) ]]]
@end display
-The @subcmd{/SIGN} subcommand tests for differences between medians of the
+The @subcmd{/SIGN} subcommand tests for differences between medians of the
variables listed.
The test does not make any assumptions about the
distribution of the data.
[ /WILCOXON @var{var_list} [ WITH @var{var_list} [ (PAIRED) ]]]
@end display
-The @subcmd{/WILCOXON} subcommand tests for differences between medians of the
+The @subcmd{/WILCOXON} subcommand tests for differences between medians of the
variables listed.
The test does not make any assumptions about the variances of the samples.
It does however assume that the distribution is symmetrical.
@end display
-The @cmd{T-TEST} procedure outputs tables used in testing hypotheses about
-means.
+The @cmd{T-TEST} procedure outputs tables used in testing hypotheses about
+means.
It operates in one of three modes:
@itemize
@item One Sample mode.
The @cmd{MISSING} subcommand determines the handling of missing
-variables.
+variables.
If @subcmd{INCLUDE} is set, then user-missing values are included in the
calculations, but system-missing values are not.
If @subcmd{EXCLUDE} is set, which is the default, user-missing
-values are excluded as well as system-missing values.
+values are excluded as well as system-missing values.
This is the default.
If @subcmd{LISTWISE} is set, then the entire case is excluded from analysis
-whenever any variable specified in the @subcmd{/VARIABLES}, @subcmd{/PAIRS} or
-@subcmd{/GROUPS} subcommands contains a missing value.
+whenever any variable specified in the @subcmd{/VARIABLES}, @subcmd{/PAIRS} or
+@subcmd{/GROUPS} subcommands contains a missing value.
If @subcmd{ANALYSIS} is set, then missing values are excluded only in the analysis for
which they would be needed. This is the default.
The @subcmd{TESTVAL} subcommand invokes the One Sample mode.
This mode is used to test a population mean against a hypothesized
-mean.
+mean.
The value given to the @subcmd{TESTVAL} subcommand is the value against
which you wish to test.
In this mode, you must also use the @subcmd{/VARIABLES} subcommand to
@subsection Independent Samples Mode
The @subcmd{GROUPS} subcommand invokes Independent Samples mode or
-`Groups' mode.
+`Groups' mode.
This mode is used to test whether two groups of values have the
same population mean.
In this mode, you must also use the @subcmd{/VARIABLES} subcommand to
variable which determines to which group the samples belong.
The values in parentheses are the specific values of the independent
variable for each group.
-If the parentheses are omitted and no values are given, the default values
+If the parentheses are omitted and no values are given, the default values
of 1.0 and 2.0 are assumed.
-If the independent variable is numeric,
+If the independent variable is numeric,
it is acceptable to specify only one value inside the parentheses.
If you do this, cases where the independent variable is
greater than or equal to this value belong to the first group, and cases
samples.
If the @subcmd{WITH} keyword is omitted, then tables for all
combinations of variables given in the @cmd{PAIRS} subcommand are
-generated.
+generated.
If the @subcmd{WITH} keyword is given, and the @subcmd{(PAIRED)} keyword
is also given, then the number of variables preceding @subcmd{WITH}
must be the same as the number following it.
The @cmd{ONEWAY} procedure performs a one-way analysis of variance of
variables factored by a single independent variable.
It is used to compare the means of a population
-divided into more than two groups.
+divided into more than two groups.
The dependent variables to be analysed should be given in the @subcmd{VARIABLES}
-subcommand.
+subcommand.
The list of variables must be followed by the @subcmd{BY} keyword and
the name of the independent (or factor) variable.
The @subcmd{CONTRAST} subcommand may be given up to 10 times in order
to specify different contrast tests.
The @subcmd{MISSING} subcommand defines how missing values are handled.
-If @subcmd{LISTWISE} is specified then cases which have missing values for
+If @subcmd{LISTWISE} is specified then cases which have missing values for
the independent variable or any dependent variable will be ignored.
If @subcmd{ANALYSIS} is specified, then cases will be ignored if the independent
-variable is missing or if the dependent variable currently being
+variable is missing or if the dependent variable currently being
analysed is missing. The default is @subcmd{ANALYSIS}.
A setting of @subcmd{EXCLUDE} means that variables whose values are
user-missing are to be excluded from the analysis. A setting of
The subcommand @subcmd{/CRITERIA=CONVERGE(@var{epsilon})} is used
to set the convergence criterion. The value of convergence criterion is @var{epsilon}
times the minimum distance between the @emph{initial} cluster centers. Iteration stops when
-the mean cluster distance between one iteration and the next
+the mean cluster distance between one iteration and the next
is less than the convergence criterion. The default value of @var{epsilon} is zero.
-The @subcmd{MISSING} subcommand determines the handling of missing variables.
+The @subcmd{MISSING} subcommand determines the handling of missing variables.
If @subcmd{INCLUDE} is set, then user-missing values are considered at their face
value and not as missing values.
If @subcmd{EXCLUDE} is set, which is the default, user-missing
-values are excluded as well as system-missing values.
+values are excluded as well as system-missing values.
If @subcmd{LISTWISE} is set, then the entire case is excluded from the analysis
-whenever any of the clustering variables contains a missing value.
+whenever any of the clustering variables contains a missing value.
If @subcmd{PAIRWISE} is set, then a case is considered missing only if all the
clustering variables contain missing values. Otherwise it is clustered
on the basis of the non-missing values.
@end display
The @cmd{RANK} command ranks variables and stores the results into new
-variables.
+variables.
The @subcmd{VARIABLES} subcommand, which is mandatory, specifies one or
-more variables whose values are to be ranked.
+more variables whose values are to be ranked.
After each variable, @samp{A} or @samp{D} may appear, indicating that
the variable is to be ranked in ascending or descending order.
Ascending is the default.
If a @subcmd{BY} keyword appears, it should be followed by a list of variables
-which are to serve as group variables.
+which are to serve as group variables.
In this case, the cases are gathered into groups, and ranks calculated
for each group.
@cindex Cronbach's Alpha
The @cmd{RELIABILITY} command performs reliability analysis on the data.
-The @subcmd{VARIABLES} subcommand is required. It determines the set of variables
+The @subcmd{VARIABLES} subcommand is required. It determines the set of variables
upon which analysis is to be performed.
-The @subcmd{SCALE} subcommand determines which variables reliability is to be
+The @subcmd{SCALE} subcommand determines which variables reliability is to be
calculated for. If it is omitted, then analysis for all variables named
in the @subcmd{VARIABLES} subcommand will be used.
-Optionally, the @var{name} parameter may be specified to set a string name
+Optionally, the @var{name} parameter may be specified to set a string name
for the scale.
-The @subcmd{MODEL} subcommand determines the type of analysis. If @subcmd{ALPHA} is specified,
-then Cronbach's Alpha is calculated for the scale. If the model is @subcmd{SPLIT},
-then the variables are divided into 2 subsets. An optional parameter
+The @subcmd{MODEL} subcommand determines the type of analysis. If @subcmd{ALPHA} is specified,
+then Cronbach's Alpha is calculated for the scale. If the model is @subcmd{SPLIT},
+then the variables are divided into 2 subsets. An optional parameter
@var{n} may be given, to specify how many variables to be in the first subset.
-If @var{n} is omitted, then it defaults to one half of the variables in the
+If @var{n} is omitted, then it defaults to one half of the variables in the
scale, or one half minus one if there are an odd number of variables.
The default model is @subcmd{ALPHA}.
-By default, any cases with user missing, or system missing values for
-any variables given
+By default, any cases with user missing, or system missing values for
+any variables given
in the @subcmd{VARIABLES} subcommand will be omitted from analysis.
-The @subcmd{MISSING} subcommand determines whether user missing values are to
+The @subcmd{MISSING} subcommand determines whether user missing values are to
be included or excluded in the analysis.
The @subcmd{SUMMARY} subcommand determines the type of summary analysis to be performed.
@end display
-The @cmd{ROC} command is used to plot the receiver operating characteristic curve
+The @cmd{ROC} command is used to plot the receiver operating characteristic curve
of a dataset, and to estimate the area under the curve.
This is useful for analysing the efficacy of a variable as a predictor of a state of nature.
The mandatory @var{var_list} is the list of predictor variables.
-The variable @var{state_var} is the variable whose values represent the actual states,
+The variable @var{state_var} is the variable whose values represent the actual states,
and @var{state_value} is the value of this variable which represents the positive state.
The optional subcommand @subcmd{PLOT} is used to determine if and how the @subcmd{ROC} curve is drawn.
By default, the curve is drawn with no reference line.
The optional subcommand @subcmd{PRINT} determines which additional tables should be printed.
-Two additional tables are available.
+Two additional tables are available.
The @subcmd{SE} keyword says that standard error of the area under the curve should be printed as well as
the area itself.
In addition, a p-value under the null hypothesis that the area under the curve equals 0.5 will be
The @subcmd{CRITERIA} subcommand has four optional parameters:
@itemize @bullet
@item The @subcmd{TESTPOS} parameter may be @subcmd{LARGE} or @subcmd{SMALL}.
-@subcmd{LARGE} is the default, and says that larger values in the predictor variables are to be
+@subcmd{LARGE} is the default, and says that larger values in the predictor variables are to be
considered positive. @subcmd{SMALL} indicates that smaller values should be considered positive.
@item The @subcmd{CI} parameter specifies the confidence interval that should be printed.
It has no effect if the @subcmd{SE} keyword in the @subcmd{PRINT} subcommand has not been given.
@item The @subcmd{DISTRIBUTION} parameter determines the method to be used when estimating the area
-under the curve.
+under the curve.
There are two possibilities, @i{viz}: @subcmd{FREE} and @subcmd{NEGEXPO}.
-The @subcmd{FREE} method uses a non-parametric estimate, and the @subcmd{NEGEXPO} method a bi-negative
+The @subcmd{FREE} method uses a non-parametric estimate, and the @subcmd{NEGEXPO} method a bi-negative
exponential distribution estimate.
The @subcmd{NEGEXPO} method should only be used when the number of positive actual states is
equal to the number of negative actual states.
@item The @subcmd{CUTOFF} parameter is for compatibility and is ignored.
@end itemize
-The @subcmd{MISSING} subcommand determines whether user missing values are to
+The @subcmd{MISSING} subcommand determines whether user missing values are to
be included or excluded in the analysis. The default behaviour is to
exclude them.
-Cases are excluded on a listwise basis; if any of the variables in @var{var_list}
-or if the variable @var{state_var} is missing, then the entire case will be
+Cases are excluded on a listwise basis; if any of the variables in @var{var_list}
+or if the variable @var{state_var} is missing, then the entire case will be
excluded.
@c LocalWords: subcmd subcommand
projects / pspp / blobdiff