The FREQ Procedure

OUTPUT Statement

OUTPUT < OUT=SAS-data-set > output-options;

The OUTPUT statement creates a SAS data set that contains statistics that are computed by PROC FREQ. Table 40.7 lists the statistics that can be stored in the output data set. You identify which statistics to include by specifying output-options.

You must use a TABLES statement with the OUTPUT statement. The OUTPUT statement stores statistics for only one table request. If you use multiple TABLES statements, the contents of the output data set correspond to the last TABLES statement. If you use multiple table requests in a single TABLES statement, the contents of the output data set correspond to the last table request. Only one OUTPUT statement is allowed in a single invocation of the procedure.

For a one-way or two-way table, the output data set contains one observation that stores the requested statistics for the table. For a multiway table, the output data set contains an observation for each two-way table (stratum) of the multiway crosstabulation. If you request summary statistics for the multiway table, the output data set also contains an observation that stores the across-strata summary statistics. If you use a BY statement, the output data set contains an observation or set of observations for each BY group. For more information about the contents of the output data set, see the section Contents of the OUTPUT Statement Output Data Set.

The output data set that is created by the OUTPUT statement is not the same as the output data set that is created by the OUT= option in the TABLES statement. The OUTPUT statement creates a data set that contains statistics (such as the Pearson chi-square and its p-value), and the OUT= option in the TABLES statement creates a data set that contains frequency table counts and percentages. See the section Output Data Sets for more information.

As an alternative to the OUTPUT statement, you can use the Output Delivery System (ODS) to store statistics that PROC FREQ computes. ODS can create a SAS data set from any table that PROC FREQ produces. See the section ODS Table Names for more information.

You can specify the following options in the OUTPUT statement:

OUT=SAS-data-set

specifies the name of the output data set. When you use an OUTPUT statement but do not use the OUT= option, PROC FREQ creates a data set and names it by using the DATAn convention.

output-options

specify the statistics to include in the output data set. Table 40.7 lists the output-options that are available in the OUTPUT statement, together with the TABLES statement options that are required to produce the statistics. Descriptions of the output-options follow the table in alphabetical order.

You can specify output-options to request individual statistics, or you can request groups of statistics by using output-options that are identical to the group options in the TABLES statement (for example, the CHISQ , MEASURES , CMH , AGREE , and ALL options).

When you specify an output-option, the output data set includes statistics from the corresponding analysis. In addition to the estimate or test statistic, the output data set includes associated values such as standard errors, confidence limits, p-values, and degrees of freedom. See the section Contents of the OUTPUT Statement Output Data Set for details.

To store a statistic in the output data set, you must also request computation of that statistic with the appropriate TABLES , EXACT , or TEST statement option. For example, the PCHI output-option includes the Pearson chi-square in the output data set. You must also request computation of the Pearson chi-square by specifying the CHISQ option in the TABLES statement. Or, if you use only one TABLES statement, you can request computation of the Pearson chi-square by specifying the PCHI or CHISQ option in the EXACT statement. Table 40.7 lists the TABLES statement options that are required to produce the OUTPUT data set statistics.

Table 40.7: OUTPUT Statement Output Options

Output Option	Output Data Set Statistics	Required TABLES Statement Option
AGREE	McNemar’s test ( $2 \times 2$ tables), Bowker’s test,	AGREE
	simple and weighted kappas; for multiple strata,
	overall simple and weighted kappas, tests for equal
	kappas, and Cochran’s Q ( $h \times 2 \times 2$ tables)
AJCHI	Continuity-adjusted chi-square ( $2 \times 2$ tables)	CHISQ
ALL	CHISQ , MEASURES , and CMH statistics;	ALL
	N (number of nonmissing observations)
BDCHI	Breslow-Day test ( $h \times 2 \times 2$ tables)	CMH , CMH1 , or CMH2
BINOMIAL \| BIN	Binomial statistics (one-way tables)	BINOMIAL
CHISQ	For one-way tables, goodness-of-fit test;	CHISQ
	for two-way tables, Pearson, likelihood ratio,
	continuity-adjusted, and Mantel-Haenszel
	chi-squares, Fisher’s exact test ( $2 \times 2$ tables),
	phi and contingency coefficients, Cramér’s V
CMH	Cochran-Mantel-Haenszel (CMH) correlation,	CMH
	row mean scores (ANOVA), and general
	association statistics; for $2 \times 2$ tables, logit
	and Mantel-Haenszel common odds ratios
	and relative risks, Breslow-Day test
CMH1	CMH statistics, except row mean scores (ANOVA)	CMH or CMH1
	and general association statistics
CMH2	CMH statistics, except general association statistic	CMH or CMH2
CMHCOR	CMH correlation statistic	CMH , CMH1 , or CMH2
CMHGA	CMH general association statistic	CMH
CMHRMS	CMH row mean scores (ANOVA) statistic	CMH or CMH2
COCHQ	Cochran’s Q ( $h \times 2 \times 2$ tables)	AGREE
CONTGY	Contingency coefficient	CHISQ
CRAMV	Cramér’s V	CHISQ
EQKAP	Test for equal simple kappas	AGREE
EQOR \| ZELEN	Zelen’s test for equal odds ratios ( $h \times 2 \times 2$ tables)	CMH and EXACT EQOR
EQWKP	Test for equal weighted kappas	AGREE
FISHER	Fisher’s exact test	CHISQ or FISHER ^[a]
GAMMA	Gamma	MEASURES
GS \| GAILSIMON	Gail-Simon test	CMH(GAILSIMON)
JT	Jonckheere-Terpstra test	JT
KAPPA	Simple kappa coefficient	AGREE
KENTB \| TAUB	Kendall’s tau-b	MEASURES
LAMCR	Lambda asymmetric $(C\|R)$	MEASURES
LAMDAS	Lambda symmetric	MEASURES
LAMRC	Lambda asymmetric $(R\|C)$	MEASURES
LGOR	Logit common odds ratio	CMH , CMH1 , or CMH2
LGRRC1	Logit common relative risk, column 1	CMH , CMH1 , or CMH2
LGRRC2	Logit common relative risk, column 2	CMH , CMH1 , or CMH2
LRCHI	Likelihood ratio chi-square	CHISQ
MCNEM	McNemar’s test ( $2 \times 2$ tables)	AGREE
MEASURES	Gamma, Kendall’s tau-b, Stuart’s tau-c,	MEASURES
	Somers’ $D (C\|R)$ and $D (R\|C)$ , Pearson and
	Spearman correlations, lambda asymmetric
	$(C\|R)$ and $(R\|C)$ , lambda symmetric,
	uncertainty coefficients $(C\|R)$ and $(R\|C)$ ,
	symmetric uncertainty coefficient;
	odds ratio and relative risks ( $2 \times 2$ tables)
MHCHI	Mantel-Haenszel chi-square	CHISQ
MHOR \| COMOR	Mantel-Haenszel common odds ratio	CMH , CMH1 , or CMH2
MHRRC1	Mantel-Haenszel common relative risk, column 1	CMH , CMH1 , or CMH2
MHRRC2	Mantel-Haenszel common relative risk, column 2	CMH , CMH1 , or CMH2
N	Number of nonmissing observations
NMISS	Number of missing observations
OR \| ODDSRATIO	Odds ratio ( $2 \times 2$ tables)	MEASURES or RELRISK
PCHI	Chi-square goodness-of-fit test (one-way tables),	CHISQ
	Pearson chi-square (two-way tables)
PCORR	Pearson correlation coefficient	MEASURES
PHI	Phi coefficient	CHISQ
PLCORR	Polychoric correlation coefficient	PLCORR
RDIF1	Column 1 risk difference (row 1 – row 2)	RISKDIFF
RDIF2	Column 2 risk difference (row 1 – row 2)	RISKDIFF
RELRISK	Odds ratio and relative risks ( $2 \times 2$ tables)	MEASURES or RELRISK
RISKDIFF	Risks and risk differences ( $2 \times 2$ tables)	RISKDIFF
RISKDIFF1	Risks and risk difference, column 1	RISKDIFF
RISKDIFF2	Risks and risk difference, column 2	RISKDIFF
RRC1 \| RELRISK1	Relative risk, column 1	MEASURES or RELRISK
RRC2 \| RELRISK2	Relative risk, column 2	MEASURES or RELRISK
RSK1 \| RISK1	Column 1 overall risk	RISKDIFF
RSK11 \| RISK11	Column 1 risk for row 1	RISKDIFF
RSK12 \| RISK12	Column 2 risk for row 1	RISKDIFF
RSK2 \| RISK2	Column 2 overall risk	RISKDIFF
RSK21 \| RISK21	Column 1 risk for row 2	RISKDIFF
RSK22 \| RISK22	Column 2 risk for row 2	RISKDIFF
SCORR	Spearman correlation coefficient	MEASURES
SMDCR	Somers’ $D (C\|R)$	MEASURES
SMDRC	Somers’ $D (R\|C)$	MEASURES
STUTC \| TAUC	Stuart’s tau-c	MEASURES
TREND	Cochran-Armitage test for trend	TREND
TSYMM \| BOWKER	Bowker’s test of symmetry	AGREE
U	Symmetric uncertainty coefficient	MEASURES
UCR	Uncertainty coefficient $(C\|R)$	MEASURES
URC	Uncertainty coefficient $(R\|C)$	MEASURES
WTKAP \| WTKAPPA	Weighted kappa coefficient	AGREE
^[a]CHISQ computes Fisher’s exact test for $2 \times 2$ tables. Use the FISHER option to compute Fisher’s exact test for general $r \times c$ tables.

You can specify the following output-options in the OUTPUT statement.

AGREE

includes the following tests and measures of agreement in the output data set: McNemar’s test (for $2 \times 2$ tables), Bowker’s test of symmetry, the simple kappa coefficient, and the weighted kappa coefficient. For multiway tables, the AGREE option also includes the following statistics in the output data set: overall simple and weighted kappa coefficients, tests for equal simple and weighted kappa coefficients, and Cochran’s Q test.

The AGREE option in the TABLES statement requests computation of tests and measures of agreement. See the section Tests and Measures of Agreement for details about these statistics.

AGREE statistics are computed only for square tables, where the number of rows equals the number of columns. PROC FREQ provides Bowker’s test of symmetry and weighted kappa coefficients only for tables larger than $2 \times 2$ . (For $2 \times 2$ tables, Bowker’s test is identical to McNemar’s test, and the weighted kappa coefficient equals the simple kappa coefficient.) Cochran’s Q is available for multiway $2 \times 2$ tables.

AJCHI

includes the continuity-adjusted chi-square in the output data set. The continuity-adjusted chi-square is available for $2 \times 2$ tables and is provided by the CHISQ option in the TABLES statement. See the section Continuity-Adjusted Chi-Square Test for details.

ALL

includes all statistics that are requested by the CHISQ , MEASURES , and CMH output-options in the output data set. ALL also includes the number of nonmissing observations, which you can request individually by specifying the N output-option.

BDCHI

includes the Breslow-Day test in the output data set. The Breslow-Day test for homogeneity of odds ratios is computed for multiway $2 \times 2$ tables and is provided by the CMH , CMH1 , and CMH2 options in the TABLES statement. See the section Breslow-Day Test for Homogeneity of the Odds Ratios for details.

BINOMIAL BIN

includes the binomial proportion estimate, confidence limits, and tests in the output data set. The BINOMIAL option in the TABLES statement requests computation of binomial statistics, which are available for one-way tables. See the section Binomial Proportion for details.

CHISQ

includes the following chi-square tests and measures in the output data set for two-way tables: Pearson chi-square, likelihood ratio chi-square, Mantel-Haenszel chi-square, phi coefficient, contingency coefficient, and Cramér’s V. For $2 \times 2$ tables, CHISQ also includes Fisher’s exact test and the continuity-adjusted chi-square in the output data set. See the section Chi-Square Tests and Statistics for details. For one-way tables, CHISQ includes the chi-square goodness-of-fit test in the output data set. See the section Chi-Square Test for One-Way Tables for details. The CHISQ option in the TABLES statement requests computation of these statistics.

If you specify the CHISQ(WARN=OUTPUT) option in the TABLES statement, the CHISQ option also includes the variable WARN_PCHI in the output data set. This variable indicates the validity warning for the asymptotic Pearson chi-square test.

CMH

includes the following Cochran-Mantel-Haenszel statistics in the output data set: correlation, row mean scores (ANOVA), and general association. For $2 \times 2$ tables, the CMH option also includes the Mantel-Haenszel and logit estimates of the common odds ratio and relative risks. For multiway (stratified) $2 \times 2$ tables, the CMH option includes the Breslow-Day test for homogeneity of odds ratios. The CMH option in the TABLES statement requests computation of these statistics. See the section Cochran-Mantel-Haenszel Statistics for details.

If you specify the CMH(MF) option in the TABLES statement, the CMH option includes the Mantel-Fleiss analysis in the output data set. The variables MF_CMH and WARN_CMH contain the Mantel-Fleiss criterion and the warning indicator, respectively.

CMH1

includes the CMH statistics in the output data set, with the exception of the row mean scores (ANOVA) statistic and the general association statistic. The CMH1 option in the TABLES statement requests computation of these statistics. See the section Cochran-Mantel-Haenszel Statistics for details.

CMH2

includes the CMH statistics in the output data set, with the exception of the general association statistic. The CMH2 option in the TABLES statement requests computation of these statistics. See the section Cochran-Mantel-Haenszel Statistics for details.

CMHCOR

includes the Cochran-Mantel-Haenszel correlation statistic in the output data set. The CMH option in the TABLES statement requests computation of this statistic. See the section Correlation Statistic for details.

CMHGA

includes the Cochran-Mantel-Haenszel general association statistic in the output data set. The CMH option in the TABLES statement requests computation of this statistic. See the section General Association Statistic for details.

CMHRMS

includes the Cochran-Mantel-Haenszel row mean scores (ANOVA) statistic in the output data set. The CMH option in the TABLES statement requests computation of this statistic. See the section ANOVA (Row Mean Scores) Statistic for details.

COCHQ

includes Cochran’s Q test in the output data set. The AGREE option in the TABLES statement requests computation of this test, which is available for multiway $2 \times 2$ tables. See the section Cochran’s Q Test for details.

CONTGY

includes the contingency coefficient in the output data set. The CHISQ option in the TABLES statement requests computation of the contingency coefficient. See the section Contingency Coefficient for details.

CRAMV

includes Cramér’s V in the output data set. The CHISQ option in the TABLES statement requests computation of Cramér’s V. See the section Cramér’s V for details.

EQKAP

includes the test for equal simple kappa coefficients in the output data set. The AGREE option in the TABLES statement requests computation of this test, which is available for multiway, square ( $h \times r \times r$ ) tables. See the section Tests for Equal Kappa Coefficients for details.

EQOR ZELEN

includes Zelen’s exact test for equal odds ratios in the output data set. The EQOR option in the EXACT statement requests computation of this test, which is available for multiway $2 \times 2$ tables. See the section Zelen’s Exact Test for Equal Odds Ratios for details.

EQWKP

includes the test for equal weighted kappa coefficients in the output data set. The AGREE option in the TABLES statement requests computation of this test. The test for equal weighted kappas is available for multiway, square ( $h \times r \times r$ ) tables where r > 2. See the section Tests for Equal Kappa Coefficients for details.

FISHER

includes Fisher’s exact test in the output data set. For $2 \times 2$ tables, the CHISQ option in the TABLES statement provides Fisher’s exact test. For tables larger than $2 \times 2$ , the FISHER option in the EXACT statement provides Fisher’s exact test. See the section Fisher’s Exact Test for details.

GAMMA

includes the gamma statistic in the output data set. The MEASURES option in the TABLES statement requests computation of the gamma statistic. See the section Gamma for details.

GS GAILSIMON

includes the Gail-Simon test for qualitative interaction in the output data set. The CMH(GAILSIMON) option in the TABLES statement requests computation of this test. See the section Gail-Simon Test for Qualitative Interactions for details.

JT

includes the Jonckheere-Terpstra test in the output data set. The JT option in the TABLES statement requests the Jonckheere-Terpstra test. See the section Jonckheere-Terpstra Test for details.

KAPPA

includes the simple kappa coefficient in the output data set. The AGREE option in the TABLES statement requests computation of kappa, which is available for square tables (where the number of rows equals the number of columns). For multiway square tables, the KAPPA option also includes the overall kappa coefficient in the output data set. See the sections Simple Kappa Coefficient and Overall Kappa Coefficient for details.

KENTB TAUB

includes Kendall’s tau-b in the output data set. The MEASURES option in the TABLES statement requests computation of Kendall’s tau-b. See the section Kendall’s Tau-b for details.

LAMCR

includes the asymmetric lambda $\lambda (C|R)$ in the output data set. The MEASURES option in the TABLES statement requests computation of lambda. See the section Lambda (Asymmetric) for details.

LAMDAS

includes the symmetric lambda in the output data set. The MEASURES option in the TABLES statement requests computation of lambda. See the section Lambda (Symmetric) for details.

LAMRC

includes the asymmetric lambda $\lambda (R|C)$ in the output data set. The MEASURES option in the TABLES statement requests computation of lambda. See the section Lambda (Asymmetric) for details.

LGOR

includes the logit estimate of the common odds ratio in the output data set. The CMH option in the TABLES statement requests computation of this statistic, which is available for $2 \times 2$ tables. See the section Adjusted Odds Ratio and Relative Risk Estimates for details.

LGRRC1

includes the logit estimate of the common relative risk (column 1) in the output data set. The CMH option in the TABLES statement requests computation of this statistic, which is available for $2 \times 2$ tables. See the section Adjusted Odds Ratio and Relative Risk Estimates for details.

LGRRC2

includes the logit estimate of the common relative risk (column 2) in the output data set. The CMH option in the TABLES statement requests computation of this statistic, which is available for $2 \times 2$ tables. See the section Adjusted Odds Ratio and Relative Risk Estimates for details.

LRCHI

includes the likelihood ratio chi-square in the output data set. The CHISQ option in the TABLES statement requests computation of the likelihood ratio chi-square. See the section Likelihood Ratio Chi-Square Test for details.

MCNEM

includes McNemar’s test (for $2 \times 2$ tables) in the output data set. The AGREE option in the TABLES statement requests computation of McNemar’s test. See the section McNemar’s Test for details.

MEASURES

includes the following measures of association in the output data set: gamma, Kendall’s tau-b, Stuart’s tau-c, Somers’ $D (C|R)$ , Somers’ $D (R|C)$ , Pearson and Spearman correlation coefficients, lambda (symmetric and asymmetric), and uncertainty coefficients (symmetric and asymmetric). For $2 \times 2$ tables, the MEASURES option also includes the odds ratio, column 1 relative risk, and column 2 relative risk. The MEASURES option in the TABLES statement requests computation of these statistics. See the section Measures of Association for details.

MHCHI

includes the Mantel-Haenszel chi-square in the output data set. The CHISQ option in the TABLES statement requests computation of the Mantel-Haenszel chi-square. See the section Mantel-Haenszel Chi-Square Test for details.

MHOR COMOR

includes the Mantel-Haenszel estimate of the common odds ratio in the output data set. The CMH option in the TABLES statement requests computation of this statistic, which is available for $2 \times 2$ tables. See the section Adjusted Odds Ratio and Relative Risk Estimates for details.

MHRRC1

includes the Mantel-Haenszel estimate of the common relative risk (column 1) in the output data set. The CMH option in the TABLES statement requests computation of this statistic, which is available for $2 \times 2$ tables. See the section Adjusted Odds Ratio and Relative Risk Estimates for details.

MHRRC2

includes the Mantel-Haenszel estimate of the common relative risk (column 2) in the output data set. The CMH option in the TABLES statement requests computation of this statistic, which is available for $2 \times 2$ tables. See the section Adjusted Odds Ratio and Relative Risk Estimates for details.

N

includes the number of nonmissing observations in the output data set.

NMISS

includes the number of missing observations in the output data set. See the section Missing Values for details about how PROC FREQ handles missing values.

OR ODDSRATIO RROR

includes the odds ratio (for $2 \times 2$ tables) in the output data set. The MEASURES , OR(CL=) , and RELRISK options in the TABLES statement request this statistic. For more information, see the section Odds Ratio.

PCHI

includes the Pearson chi-square in the output data set for two-way tables. See the section Pearson Chi-Square Test for Two-Way Tables for details. For one-way tables, the PCHI option includes the chi-square goodness-of-fit test in the output data set. See the section Chi-Square Test for One-Way Tables for details. The CHISQ option in the TABLES statement requests computation of these statistics.

If you specify the CHISQ(WARN=OUTPUT) option in the TABLES statement, the PCHI option also includes the variable WARN_PCHI in the output data set. This variable indicates the validity warning for the asymptotic Pearson chi-square test.

PCORR

includes the Pearson correlation coefficient in the output data set. The MEASURES option in the TABLES statement requests computation of the Pearson correlation. See the section Pearson Correlation Coefficient for details.

PHI

includes the phi coefficient in the output data set. The CHISQ option in the TABLES statement requests computation of the phi coefficient. See the section Phi Coefficient for details.

PLCORR

includes the polychoric correlation coefficient in the output data set. For $2 \times 2$ tables, this statistic is known as the tetrachoric correlation coefficient. The PLCORR option in the TABLES statement requests computation of the polychoric correlation. See the section Polychoric Correlation for details.

RDIF1

includes the column 1 risk difference (row 1 – row 2) in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences, which are available for $2 \times 2$ tables. See the section Risks and Risk Differences for details.

RDIF2

includes the column 2 risk difference (row 1 – row 2) in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences, which are available for $2 \times 2$ tables. See the section Risks and Risk Differences for details.

RELRISK

includes the column 1 and column 2 relative risks (for $2 \times 2$ tables) in the output data set. The MEASURES and RELRISK options in the TABLES statement request these statistics. For more information, see the section Relative Risks.

RISKDIFF

includes risks (binomial proportions) and risk differences for $2 \times 2$ tables in the output data set. These statistics include the row 1 risk, row 2 risk, total (overall) risk, and risk difference (row 1 – row 2) for column 1 and column 2. The RISKDIFF option in the TABLES statement requests computation of these statistics. See the section Risks and Risk Differences for details.

RISKDIFF1

includes column 1 risks (binomial proportions) and risk differences for $2 \times 2$ tables in the output data set. These statistics include the row 1 risk, row 2 risk, total (overall) risk, and risk difference (row 1 – row 2). The RISKDIFF option in the TABLES statement requests computation of these statistics. See the section Risks and Risk Differences for details.

RISKDIFF2

includes column 2 risks (binomial proportions) and risk differences for $2 \times 2$ tables in the output data set. These statistics include the row 1 risk, row 2 risk, total (overall) risk, and risk difference (row 1 – row 2). The RISKDIFF option in the TABLES statement requests computation of these statistics. See the section Risks and Risk Differences for details.

RRC1 RELRISK1

includes the column 1 relative risk in the output data set. The MEASURES and RELRISK options in the TABLES statement request relative risks, which are available for $2 \times 2$ tables. See the section Odds Ratio and Relative Risks for 2 x 2 Tables for details.

RRC2 RELRISK2

includes the column 2 relative risk in the output data set. The MEASURES and RELRISK options in the TABLES statement request relative risks, which are available for $2 \times 2$ tables. See the section Odds Ratio and Relative Risks for 2 x 2 Tables for details.

RSK1 RISK1

includes the overall column 1 risk in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences, which are available for $2 \times 2$ tables. See the section Risks and Risk Differences for details.

RSK11 RISK11

includes the column 1 risk for row 1 in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences, which are available for $2 \times 2$ tables. See the section Risks and Risk Differences for details.

RSK12 RISK12

includes the column 2 risk for row 1 in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences, which are available for $2 \times 2$ tables. See the section Risks and Risk Differences for details.

RSK2 RISK2

includes the overall column 2 risk in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences. See the section Risks and Risk Differences for details.

RSK21 RISK21

includes the column 1 risk for row 2 in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences, which are available for $2 \times 2$ tables. See the section Risks and Risk Differences for details.

RSK22 RISK22

includes the column 2 risk for row 2 in the output data set. The RISKDIFF option in the TABLES statement requests computation of risks and risk differences, which are available for $2 \times 2$ tables. See the section Risks and Risk Differences for details.

SCORR

includes the Spearman correlation coefficient in the output data set. The MEASURES option in the TABLES statement requests computation of the Spearman correlation. See the section Spearman Rank Correlation Coefficient for details.

SMDCR

includes Somers’ $D (C|R)$ in the output data set. The MEASURES option in the TABLES statement requests computation of Somers’ D. See the section Somers’ D for details.

SMDRC

includes Somers’ $D (R|C)$ in the output data set. The MEASURES option in the TABLES statement requests computation of Somers’ D. See the section Somers’ D for details.

STUTC TAUC

includes Stuart’s tau-c in the output data set. The MEASURES option in the TABLES statement requests computation of tau-c. See the section Stuart’s Tau-c for details.

TREND

includes the Cochran-Armitage test for trend in the output data set. The TREND option in the TABLES statement requests computation of the trend test. This test is available for tables of dimension $2 \times C$ or $R \times 2$ . See the section Cochran-Armitage Test for Trend for details.

TSYMM BOWKER

includes Bowker’s test of symmetry in the output data set. The AGREE option in the TABLES statement requests computation of Bowker’s test. See the section Bowker’s Test of Symmetry for details.

U

includes the uncertainty coefficient (symmetric) in the output data set. The MEASURES option in the TABLES statement requests computation of the uncertainty coefficient. See the section Uncertainty Coefficient (Symmetric) for details.

UCR

includes the asymmetric uncertainty coefficient $U (C|R)$ in the output data set. The MEASURES option in the TABLES statement requests computation of the uncertainty coefficient. See the section Uncertainty Coefficients (Asymmetric) for details.

URC

includes the asymmetric uncertainty coefficient $U (R|C)$ in the output data set. The MEASURES option in the TABLES statement requests computation of the uncertainty coefficient. See the section Uncertainty Coefficients (Asymmetric) for details.

WTKAP WTKAPPA

includes the weighted kappa coefficient in the output data set. The AGREE option in the TABLES statement requests computation of weighted kappa, which is available for square tables larger than $2 \times 2$ . For multiway tables, the WTKAP option also includes the overall weighted kappa coefficient in the output data set. See the sections Weighted Kappa Coefficient and Overall Kappa Coefficient for details.