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The FREQ procedure produces one-way to n-way frequency and contingency (crosstabulation) tables. For two-way tables, PROC FREQ computes tests and measures of association. For n-way tables, PROC FREQ provides stratified analysis by computing statistics across, as well as within, strata.
The FREQ Procedure......Page 4
Overview: FREQ Procedure......Page 5
Frequency Tables and Statistics......Page 7
Agreement Study......Page 14
Syntax: FREQ Procedure......Page 16
PROC FREQ Statement......Page 17
BY Statement......Page 19
EXACT Statement......Page 20
OUTPUT Statement......Page 23
TABLES Statement......Page 26
TEST Statement......Page 51
WEIGHT Statement......Page 52
Inputting Frequency Counts......Page 53
Grouping with Formats......Page 54
Missing Values......Page 55
Statistical Computations......Page 58
Computational Resources......Page 111
Output Data Sets......Page 112
Displayed Output......Page 115
ODS Table Names......Page 123
ODS Graphics......Page 126
Example 35.1: Output Data Set of Frequencies......Page 127
Example 35.2: Frequency Dot Plots......Page 130
Example 35.3: Chi-Square Goodness-of-Fit Tests......Page 133
Example 35.4: Binomial Proportions......Page 137
Example 35.5: Analysis of a 2x2 Contingency Table......Page 140
Example 35.6: Output Data Set of Chi-Square Statistics......Page 143
Example 35.7: Cochran-Mantel-Haenszel Statistics......Page 145
Example 35.8: Cochran-Armitage Trend Test......Page 146
Example 35.9: Friedman's Chi-Square Test......Page 150
Example 35.10: Cochran's Q Test......Page 152
References......Page 154
Subject Index......Page 160
Syntax Index......Page 164
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The LOGISTIC procedure fits linear logistic regression models for discrete response data by the method of maximum likelihood. It can also perform conditional logistic regression for binary response data and exact conditional logistic regression for binary and nominal response data.
The GENMOD procedure fits generalized linear models.
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The REG procedure is a general-purpose procedure for linear regression.
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