* NPAR TESTS:: Nonparametric tests.
* T-TEST:: Test hypotheses about means.
* ONEWAY:: One way analysis of variance.
+* QUICK CLUSTER:: K-Means clustering.
* RANK:: Compute rank scores.
* REGRESSION:: Linear regression.
* RELIABILITY:: Reliability analysis.
@{A,D@}
@end display
-The @cmd{DESCRIPTIVES} procedure reads the active file and outputs
+The @cmd{DESCRIPTIVES} procedure reads the active dataset and outputs
descriptive
statistics requested by the user. In addition, it can optionally
compute Z-scores.
@menu
* BINOMIAL:: Binomial Test
* CHISQUARE:: Chisquare Test
-* WILCOXON:: Wilcoxon Signed Ranks Test
+* COCHRAN:: Cochran Q Test
+* FRIEDMAN:: Friedman Test
+* KENDALL:: Kendall's W Test
+* KRUSKAL-WALLIS:: Kruskal-Wallis Test
+* MANN-WHITNEY:: Mann Whitney U Test
+* MCNEMAR:: McNemar Test
+* RUNS:: Runs Test
* SIGN:: The Sign Test
+* WILCOXON:: Wilcoxon Signed Ranks Test
@end menu
If no /EXPECTED subcommand is given, then then equal frequencies
are expected.
-@node WILCOXON
-@subsection Wilcoxon Matched Pairs Signed Ranks Test
-@comment node-name, next, previous, up
-@vindex WILCOXON
-@cindex wilcoxon matched pairs signed ranks test
+
+@node COCHRAN
+@subsection Cochran Q Test
+@vindex Cochran
+@cindex Cochran Q test
+@cindex Q, Cochran Q
@display
- [ /WILCOXON varlist [ WITH varlist [ (PAIRED) ]]]
+ [ /COCHRAN = varlist ]
@end display
-The /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 symetrical.
+The Cochran Q test is used to test for differences between three or more groups.
+The data for @var{varlist} 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.
+
+@node FRIEDMAN
+@subsection Friedman Test
+@vindex FRIEDMAN
+@cindex Friedman test
+
+@display
+ [ /FRIEDMAN = varlist ]
+@end display
+
+The Friedman test is used to test for differences between repeated measures when there is no indication that the distributions are normally distributed.
+
+A list of variables which contain the measured data must be given. The procedure prints the sum of ranks for each variable, the test statistic and its significance.
+
+@node KENDALL
+@subsection Kendall's W Test
+@vindex KENDALL
+@cindex Kendall's W test
+@cindex coefficient of concordance
+
+@display
+ [ /KENDALL = varlist ]
+@end display
+
+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
+unity indicates complete agreement.
+
+
+@node KRUSKAL-WALLIS
+@subsection Kruskal-Wallis Test
+@vindex KRUSKAL-WALLIS
+@vindex K-W
+@cindex Kruskal-Wallis test
+
+@display
+ [ /KRUSKAL-WALLIS = varlist BY var (lower, upper) ]
+@end display
+
+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{varlist}.
+The categorical variable determining the groups to which the
+data belongs is given by @var{var}. The limits @var{lower} and
+@var{upper} specify the valid range of @var{var}. Any cases for
+which @var{var} falls outside [@var{lower}, @var{upper}] will be
+ignored.
+
+The mean rank of each group as well as the chi-squared value and significance
+of the test will be printed.
+The abbreviated subcommand K-W may be used in place of KRUSKAL-WALLIS.
+
+
+@node MANN-WHITNEY
+@subsection Mann-Whitney U Test
+@vindex MANN-WHITNEY
+@vindex M-W
+@cindex Mann-Whitney U test
+@cindex U, Mann-Whitney U
+
+@display
+ [ /MANN-WHITNEY = varlist BY var (group1, group2) ]
+@end display
+
+The Mann-Whitney subcommand is used to test whether two groups of data come from different populations.
+The variables to be tested should be specified in @var{varlist} and the grouping variable, that determines to which group the test variables belong, in @var{var}.
+@var{Var} may be either a string or an alpha variable.
+@var{Group1} and @var{group2} specify the
+two values of @var{var} which determine the groups of the test data.
+Cases for which the @var{var} value is neither @var{group1} or @var{group2} will be ignored.
+
+The value of the Mann-Whitney U statistic, the Wilcoxon W, and the significance will be printed.
+The abbreviated subcommand M-W may be used in place of MANN-WHITNEY.
+
+@node MCNEMAR
+@subsection McNemar Test
+@vindex MCNEMAR
+@cindex McNemar test
+
+@display
+ [ /MCNEMAR varlist [ WITH varlist [ (PAIRED) ]]]
+@end display
+
+Use McNemar's test to analyse the significance of the difference between
+pairs of correlated proportions.
If the @code{WITH} keyword is omitted, then tests for all
combinations of the listed variables are performed.
of variable preceding @code{WITH} against variable following
@code{WITH} are performed.
+The data in each variable must be dichotomous. If there are more
+than two distinct variables an error will occur and the test will
+not be run.
+
+@node RUNS
+@subsection Runs Test
+@vindex RUNS
+@cindex runs test
+
+@display
+ [ /RUNS (@{MEAN, MEDIAN, MODE, value@}) varlist ]
+@end display
+
+The /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.
+The desired threshold must be specified within parentheses.
+It may either be specified as a number or as one of MEAN, MEDIAN or MODE.
+Following the threshold specification comes the list of variables whose values are to be
+tested.
+
+The subcommand shows the number of runs, the asymptotic significance based on the
+length of the data.
@node SIGN
@subsection Sign Test
of variable preceding @code{WITH} against variable following
@code{WITH} are performed.
+@node WILCOXON
+@subsection Wilcoxon Matched Pairs Signed Ranks Test
+@comment node-name, next, previous, up
+@vindex WILCOXON
+@cindex wilcoxon matched pairs signed ranks test
+
+@display
+ [ /WILCOXON varlist [ WITH varlist [ (PAIRED) ]]]
+@end display
+
+The /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 symetrical.
+
+If the @code{WITH} keyword is omitted, then tests for all
+combinations of the listed variables are performed.
+If the @code{WITH} keyword is given, and the @code{(PAIRED)} keyword
+is also given, then the number of variables preceding @code{WITH}
+must be the same as the number following it.
+In this case, tests for each respective pair of variables are
+performed.
+If the @code{WITH} keyword is given, but the
+@code{(PAIRED)} keyword is omitted, then tests for each combination
+of variable preceding @code{WITH} against variable following
+@code{WITH} are performed.
+
@node T-TEST
@comment node-name, next, previous, up
@section T-TEST
/MISSING=@{ANALYSIS,LISTWISE@} @{EXCLUDE,INCLUDE@}
/CONTRAST= value1 [, value2] ... [,valueN]
/STATISTICS=@{DESCRIPTIVES,HOMOGENEITY@}
-
+ /POSTHOC=@{BONFERRONI, GH, LSD, SCHEFFE, SIDAK, TUKEY, ALPHA ([value])@}
@end display
The @cmd{ONEWAY} procedure performs a one-way analysis of variance of
It is used to compare the means of a population
divided into more than two groups.
-The variables to be analysed should be given in the @code{VARIABLES}
+The dependent variables to be analysed should be given in the @code{VARIABLES}
subcommand.
The list of variables must be followed by the @code{BY} keyword and
the name of the independent (or factor) variable.
display a warning, but will proceed with the analysis.
The @code{CONTRAST} subcommand may be given up to 10 times in order
to specify different contrast tests.
+The @code{MISSING} subcommand defines how missing values are handled.
+If LISTWISE is specified then cases which have missing values for
+the independent variable or any dependent variable will be ignored.
+If ANALYSIS is specified, then cases will be ignored if the independent
+variable is missing or if the dependent variable currently being
+analysed is missing. The default is ANALYSIS.
+A setting of EXCLUDE means that variables whose values are
+user-missing are to be excluded from the analysis. A setting of
+INCLUDE means they are to be included. The default is EXCLUDE.
+
+Using the @code{POSTHOC} subcommand you can perform multiple
+pairwise comparisons on the data. The following comparison methods
+are available:
+@itemize
+@item LSD
+Least Significant Difference.
+@item TUKEY
+Tukey Honestly Significant Difference.
+@item BONFERRONI
+Bonferroni test.
+@item SCHEFFE
+Scheff@'e's test.
+@item SIDAK
+Sidak test.
+@item GH
+The Games-Howell test.
+@end itemize
+
+@noindent
+The optional syntax @code{ALPHA(@var{value})} is used to indicate
+that @var{value} should be used as the
+confidence level for which the posthoc tests will be performed.
+The default is 0.05.
+
+@node QUICK CLUSTER
+@comment node-name, next, previous, up
+@section QUICK CLUSTER
+@vindex QUICK CLUSTER
+
+@cindex K-means clustering
+@cindex clustering
+
+@display
+QUICK CLUSTER var_list
+ [/CRITERIA=CLUSTERS(@var{k}) [MXITER(@var{max_iter})]]
+ [/MISSING=@{EXCLUDE,INCLUDE@} @{LISTWISE, PAIRWISE@}]
+@end display
+
+The @cmd{QUICK CLUSTER} command performs k-means clustering on the
+dataset. This is useful when you wish to allocate cases into clusters
+of similar values and you already know the number of clusters.
+
+The minimum specification is @samp{QUICK CLUSTER} followed by the names
+of the variables which contain the cluster data. Normally you will also
+want to specify @samp{/CRITERIA=CLUSTERS(@var{k})} where @var{k} is the
+number of clusters. If this is not given, then @var{k} defaults to 2.
+
+The command uses an iterative algorithm to determine the clusters for
+each case. It will continue iterating until convergence, or until @var{max_iter}
+iterations have been done. The default value of @var{max_iter} is 2.
+
+The @cmd{MISSING} subcommand determines the handling of missing variables.
+If INCLUDE is set, then user-missing values are considered at their face
+value and not as missing values.
+If EXCLUDE is set, which is the default, user-missing
+values are excluded as well as system-missing values.
+
+If LISTWISE is set, then the entire case is excluded from the analysis
+whenever any of the clustering variables contains a missing value.
+If 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.
+The default is LISTWISE.
+
@node RANK
@comment node-name, next, previous, up
@section RANK
+
@vindex RANK
@display
RANK