* ONEWAY:: One way analysis of variance.
* QUICK CLUSTER:: K-Means clustering.
* RANK:: Compute rank scores.
-* REGRESSION:: Linear regression.
* RELIABILITY:: Reliability analysis.
* ROC:: Receiver Operating Characteristic.
@end menu
[@t{SHOWSIG=}@{@t{NO} @math{|} @t{YES}@}]
@end display
-The @code{CTABLES} (aka ``custom tables'') command outputs
-multi-dimensional tables, offering many options for table
-summarization and formatting.
+The @code{CTABLES} (aka ``custom tables'') command produces
+multi-dimensional tables from categorical and scale data. It offers
+many options for data summarization and formatting.
-@code{TABLE}, the only required subcommand, specifies the variables to
-include on each dimension, using the syntax @t{/TABLE} @i{rows} @t{BY}
-@i{columns} @t{BY} @i{layers}, in which @i{rows}, @i{columns}, and
-@i{layers} is each empty or an @i{axis}. The simplest form of
-@i{axis} is just a variable name.
+This section's examples use data from the 2008 (USA) National Survey
+of Drinking and Driving Attitudes and Behaviors, a public domain data
+set from the (USA) National Highway Traffic Administration and
+available at @url{https://data.transportation.gov}. @pspp{} includes
+this data set, with a slightly modified dictionary, as
+@file{examples/nhtsa.sav}.
+@menu
+* CTABLES Basics::
+* CTABLES Data Summarization::
+@end menu
+
+@node CTABLES Basics
+@subsection Basics
+
+The only required subcommand is @code{TABLE}, which specifies the
+variables to include along each axis:
+@display
+@t{/TABLE} @i{rows} [@t{BY} @i{columns} [@t{BY} @i{layers}]]
+@end display
+@noindent
+In @code{TABLE}, each of @var{rows}, @var{columns}, and @var{layers}
+is either empty or an axis expression that specifies one or more
+variables. At least one must specify an axis expression.
+
+@menu
+* CTABLES Categorical Variable Basics::
+* CTABLES Scalar Variable Basics::
+* CTABLES Overriding Measurement Level::
+* CTABLES Multiple Response Sets::
+@end menu
+
+@node CTABLES Categorical Variable Basics
+@subsubsection Categorical Variables
+
+An axis expression that names a categorical variable divides the data
+into cells according to the values of that variable. When all the
+variables named on @code{TABLE} are categorical, by default each cell
+displays the number of cases that it contains, so specifying a single
+variable yields a frequency table:
+
+@example
+CTABLES /TABLE=AgeGroup.
+@end example
+@psppoutput {ctables1}
+
+@noindent
+Specifying a row and a column categorical variable yields a
+crosstabulation:
+
+@example
+CTABLES /TABLE=AgeGroup BY qns3a.
+@end example
+@psppoutput {ctables2}
+
+@noindent
+The @samp{>} ``nesting'' operator nests multiple variables on a single
+axis, e.g.:
+
+@example
+CTABLES /TABLE qn105ba BY AgeGroup > qns3a.
+@end example
+@psppoutput {ctables3}
+
+@noindent
+The @samp{+} ``stacking'' operator allows a single output table to
+include multiple data analyses. With @samp{+}, @code{CTABLES} divides
+the output table into multiple @dfn{sections}, each of which includes
+an analysis of the full data set. For example, the following command
+separately tabulates age group and driving frequency by gender:
+
+@example
+CTABLES /TABLE AgeGroup + qn1 BY qns3a.
+@end example
+@psppoutput {ctables4}
+
+@noindent
+If @samp{+} and @samp{>} are used together, @samp{>} binds more
+tightly. Use parentheses to override operator precedence. Thus:
+
+@example
+CTABLES /TABLE qn26 + qn27 > qns3a.
+CTABLES /TABLE (qn26 + qn27) > qns3a.
+@end example
+@psppoutput {ctables5}
+
+@node CTABLES Scalar Variable Basics
+@subsubsection Scalar Variables
+
+Categorical variables make @code{CTABLES} divide tables into cells.
+With scalar variables, @code{CTABLES} instead calculates a summary
+measure, by default the mean, of the values that fall into a cell.
+For example, if the only variable specified is a scalar variable, then
+the output is a single cell that holds the mean of all of the data:
+
+@example
+CTABLES /TABLE qnd1.
+@end example
+@psppoutput {ctables6}
+
+A scalar variable may nest with categorical variables. The following
+example shows the mean age of survey respondents across gender and
+language groups:
+
+@example
+CTABLES /TABLE qns3a > qnd1 BY region.
+@end example
+@psppoutput {ctables7}
+
+The order of nesting of scalar and categorical variables affects table
+labeling, but it does not affect the data displayed in the table. The
+following example shows how the output changes when the nesting order
+of the scalar and categorical variable are interchanged:
+
+@example
+CTABLES /TABLE qnd1 > qns3a BY region.
+@end example
+@psppoutput {ctables8}
+
+Only a single scalar variable may appear in each section; that is, a
+scalar variable may not nest inside a scalar variable directly or
+indirectly. Scalar variables may only appear on one axis within
+@code{TABLE}.
+
+@node CTABLES Overriding Measurement Level
+@subsubsection Overriding Measurement Level
+
+By default, @code{CTABLES} uses a variable's measurement level to
+decide whether to treat it as categorical or scalar. Variables
+assigned the nominal or ordinal measurement level are treated as
+categorical, and scalar variables are treated as scalar.
+
+Use the @code{VARIABLE LEVEL} command to change a variable's
+measurement level. To treat a variable as categorical or scalar only
+for one use on @code{CTABLES}, add @samp{[C]} or @samp{[S]},
+respectively, after the variable name. The following example shows
+how to analyze the scalar variable @code{qn20} as categorical:
+
+@example
+CTABLES /TABLE qn20 [C] BY qns3a.
+@end example
+@psppoutput {ctables9}
+
+@node CTABLES Multiple Response Sets
+@subsubheading Multiple Response Sets
+
+The @code{CTABLES} command does not yet support multiple response
+sets.
+
+@node CTABLES Data Summarization
+@subsection Data Summarization
+
+The @code{CTABLES} command allows the user to control how the data are
+summarized with summary specifications, which are enclosed in square
+brackets following a variable name on the @code{TABLE} subcommand.
+When all the variables are categorical, summary specifications can be
+given for the innermost nested variables on any one axis. When a
+scalar variable is present, only the scalar variable may have summary
+specifications. The following example includes a summary
+specification for column and row percentages for categorical
+variables, and mean and median for a scalar variable:
+
+@example
+CTABLES
+ /TABLE=qnd1 [MEAN, MEDIAN] BY qns3a
+ /TABLE=AgeGroup [COLPCT, ROWPCT] BY qns3a.
+@end example
+@psppoutput {ctables10}
+
+A summary specification may override the default label and format by
+appending a string or format specification or both (in that order) to
+the summary function name. For example:
+
+@example
+CTABLES /TABLE=AgeGroup [COLPCT 'Gender %' PCT5.0,
+ ROWPCT 'Age Group %' PCT5.0]
+ BY qns3a.
+@end example
+@psppoutput {ctables11}
+
+Parentheses provide a shorthand to apply summary specifications to
+multiple variables. For example, both of these commands:
+
+@example
+CTABLES /TABLE=AgeGroup[COLPCT] + qns1[COLPCT] BY qns3a.
+CTABLES /TABLE=(AgeGroup + qns1)[COLPCT] BY qns3a.
+@end example
+
+@noindent
+produce the same output shown below:
+
+@psppoutput {ctables12}
+
+The following section lists the available summary functions.
+
+@menu
+* CTABLES Summary Functions for Categorical and Scale Variables::
+@end menu
+
+@node CTABLES Summary Functions
+@subsubsection Summary Functions
+
+This section lists the summary functions that can be applied to cells
+in @code{CTABLES}. Many of these functions have an @var{area} in
+their names. The supported areas are:
+
+@itemize @bullet
+@item
+Areas that correspond to parts of @dfn{subtables}, whose contents are
+the cells that pair an innermost row variable and an innermost column
+variable:
+
+@table @code
+@item ROW
+A row within a subtable.
+
+@item COL
+A column within a subtable.
+
+@item SUBTABLE
+All the cells in a subtable
+@end table
+
+@item
+Areas that correspond to parts of @dfn{sections}, where stacked
+variables divide each section from another:
+
+@table @code
+@item TABLE
+An entire section.
+
+@item LAYER
+A layer within a section.
+
+@item LAYERROW
+A row in one layer within a section.
+
+@item LAYERCOL
+A column in one layer within a section.
+@end table
+@end itemize
+
+The following summary functions may be applied to any variable
+regardless of whether it is categorical or scalar. The default label
+for each function is listed in parentheses:
+
+@table @asis
+@item @code{COUNT} (``Count'')
+The sum of weights in a cell.
+
+@item @code{@i{area}PCT} or @code{@i{area}PCT.COUNT} (``@i{Area} %'')
+A percentage within the specified @var{area}.
+
+@item @code{@i{area}PCT.VALIDN} (``@i{Area} Valid N %'')
+A percentage of valid values within the specified @var{area}.
+
+@item @code{@i{area}PCT.TOTALN} (``@i{Area} Total N %'')
+A percentage of total values within the specified @var{area}.
+@end table
+
+The following summary functions apply only to scale variables:
+
+@table @asis
+@item @code{MAXIMUM} (``Maximum'')
+The largest value.
+
+@item @code{MEAN} (``Mean'')
+The mean.
+
+@item @code{MEDIAN} (``Median'')
+The median value.
+
+@item @code{MINIMUM} (``Minimum'')
+The smallest value.
+
+@item @code{MISSING} (``Missing'')
+Sum of weights of user- and system-missing values.
+
+@item @code{MODE} (``Mode'')
+The highest-frequency value. Ties are broken by taking the smallest mode.
+
+@item @code{@i{area}PCT.SUM} (``@i{Area} Sum %'')
+Percentage of the sum of the values across @var{area}.
+
+@item @code{PTILE} @i{n} (``Percentile @i{n}'')
+The @var{n}th percentile, where @math{0 @leq{} @var{n} @leq{} 100}.
+
+@item @code{RANGE} (``Range'')
+The maximum minus the minimum.
+
+@item @code{SEMEAN} (``Std Error of Mean'')
+The standard error of the mean.
+
+@item @code{STDDEV} (``Std Deviation'')
+The standard deviation.
+
+@item @code{SUM} (``Sum'')
+The sum.
+
+@item @code{TOTALN} (``Total N'')
+The sum of total count weights.
+
+@item @code{VALIDN} (``Valid N'')
+The sum of valid count weights.
+
+@item @code{VARIANCE} (``Variance'')
+The variance.
+@end table
+
+If the @code{WEIGHT} subcommand specified an adjustment weight
+variable, then the following summary functions use its value instead
+of the dictionary weight variable. Otherwise, they are equivalent to
+the summary function without the @samp{E}-prefix:
+
+@itemize @bullet
+@item
+@code{ECOUNT} (``Adjusted Count'')
+
+@item
+@code{ETOTALN} (``Adjusted Total N'')
+
+@item
+@code{EVALIDN} (``Adjusted Valid N'')
+@end itemize
+
+The following summary functions with a @samp{U}-prefix are equivalent
+to the same ones without the prefix, except that they use unweighted
+counts:
+
+@itemize @bullet
+@item
+@code{UCOUNT} (``Unweighted Count'')
+
+@item
+@code{U@i{area}PCT} or @code{U@i{area}PCT.COUNT} (``Unweighted @i{Area} %'')
+
+@item
+@code{U@i{area}PCT.VALIDN} (``Unweighted @i{Area} Valid N %'')
+
+@item
+@code{U@i{area}PCT.TOTALN} (``Unweighted @i{Area} Total N %'')
+
+@item
+@code{UMEAN} (``Unweighted Mean'')
+
+@item
+@code{UMEDIAN} (``Unweighted Median'')
+
+@item
+@code{UMISSING} (``Unweighted Missing'')
+
+@item
+@code{UMODE} (``Unweight Mode'')
+
+@item
+@code{U@i{area}PCT.SUM} (``Unweighted @i{Area} Sum %'')
+
+@item
+@code{UPTILE} @i{n} (``Unweighted Percentile @i{n}'')
+
+@item
+@code{USEMEAN} (``Unweighted Std Error of Mean'')
+
+@item
+@code{USTDDEV} (``Unweighted Std Deviation'')
+
+@item
+@code{USUM} (``Unweighted Sum'')
+
+@item
+@code{UTOTALN} (``Unweighted Total N'')
+
+@item
+@code{UVALIDN} (``Unweighted Valid N'')
+
+@item
+@code{UVARIANCE} (``Unweighted Variance'')
+@end itemize
@node FACTOR
@section FACTOR
projects / pspp / blobdiff