User Guide

Chapter
16
Crosstabs
The Crosstabs procedure forms two-way and multiway tables and provides a variety
of tests and
measures of association for two-way tables. The structure of the table and
whether categories are ordered determine what test or measure to use.
Crosstabs’ statistics and measures of association are computed for two-way
tables onl
y. If you specify a row, a column, and a layer factor (control variable),
the Crosstabs procedure forms one panel of associated statistics and measures for
each value of the layer factor (or a combination of values for two or more control
variables
). For example, if gender is a layer factor for a table of married (yes, no)
against life (is life exciting, routine, or dull), the results for a two-way table for the
females are computed separately from those for the males and printed as panels
followin
g one another.
Example. Are customers from small companies more likely to be profitable in sales of
services (for example, training and consulting) than those from larger companies?
From a cr
osstabulation, you might learn that the majority of small companies (fewer
than 500 employees) yield high service profits, while the majority of large companies
(more than 2,500 employees) yield low service profits.
Statist
ics and measures of association.
Pearson chi-square, likelihood-ratio chi-square,
linear-by-linear association test, Fisher’s exact test, Yates’ corrected chi-square,
Pearson’s r, Spearman’s rho, contingency coefficient, phi, Cramér’s V, symmetric
and asy
mmetric lambdas, Goodman and Kruskal’s tau, uncertainty coefficient,
gamma, Somers’ d, Kendall’s tau-b, Kendall’s tau-c, eta coefficient, Cohen’s kappa,
relative risk estimate, odds ratio, McNemar test, and Cochran’s and Mantel-Haenszel
stati
stics.
Data. To define the categories of each table variable, use values of a numeric or short
string (eight or fewer characters) variable. For example, for gender, you could code
the da
taas1and2orasmale and female.
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