The FREQ Procedure

requests the AC1 agreement coefficient. For more information, see the section AC1 Agreement Coefficient.

controls the degrees of freedom for Bowker’s symmetry test. You can specify the value of the degrees of freedom (df), or you can specify DFSYM=ADJUST to adjust the degrees of freedom for empty table cells. The value of df must be a positive number. By default, df is , where R is the dimension of the two-way table.

When you specify DFSYM=ADJUST, the degrees of freedom are reduced by the number of off-diagonal table-cell pairs that have a total frequency of 0. By default, the degrees of freedom count all off-diagonal table-cell pairs. For more information, see the section Bowker’s Symmetry Test.

displays the "Kappa Details" table, which includes the following statistics for the simple kappa coefficient: observed agreement, chance-expected agreement, and maximum kappa. If the two-way table is , the "Kappa Details" table also includes the prevalence index and the bias index. For more information, see the section Simple Kappa Coefficient.

If the two-way table is larger than , this option also displays the "Weighted Kappa Details" table, which includes the observed agreement and chance-expected agreement components of the weighted kappa coefficient. For more information, see the section Weighted Kappa Coefficient.

specifies the null value of the ratio of discordant proportions for McNemar’s test. By default, MNULLRATIO=1. For more information, see the section McNemar’s Test.

requests the simple kappa coefficient test and specifies the null value for the test. The null value must be between –1 and 1. By default, NULLKAPPA=0. For more information, see the section Simple Kappa Coefficient.

This option is not available when you specify the KAPPA option in the EXACT statement, which requests an exact test for the kappa coefficient.

requests the weighted kappa coefficient test and specifies the null value for the test. The null value must be between –1 and 1. By default, NULLWTKAPPA=0. For more information, see the section Weighted Kappa Coefficient.

This option is not available when you specify the WTKAP option in the EXACT statement, which requests an exact test for the weighted kappa coefficient.

requests the prevalence-adjusted bias-adjusted kappa coefficient. For more information, see the section Prevalence-Adjusted Bias-Adjusted Kappa.

displays the agreement weights that PROC FREQ uses to compute the weighted kappa coefficient. Agreement weights reflect the relative agreement between pairs of variable levels. By default, PROC FREQ uses Cicchetti-Allison agreement weights. If you specify the WT=FC option, the procedure uses Fleiss-Cohen agreement weights. For more information, see the section Weighted Kappa Coefficient.

displays agreement tables (which are produced by the AGREE option) in factoid (label-value) format, which is the format of these tables in releases before SAS/STAT 14.2. Beginning in SAS/STAT 14.2, PROC FREQ displays agreement tables in tabular format (instead of factoid format) by default when you specify any of the following agree-options: AC1, KAPPADETAILS, NULLKAPPA=, NULLWTKAPPA=, PABAK, or WTKAPPADETAILS.

The TABLES=RESTORE agree-option applies to the following tables: "McNemar’s Test," "Symmetry Test," "Kappa Statistics," "Kappa Test," and "Weighted Kappa Test."

specifies Fleiss-Cohen agreement weights in the computation of the weighted kappa coefficient. Agreement weights reflect the relative agreement between pairs of variable levels. By default, PROC FREQ uses Cicchetti-Allison agreement weights to compute the weighted kappa coefficient. For more information, see the section Weighted Kappa Coefficient.

displays the "Weighted Kappa Details" table, which includes the observed agreement and chance-expected agreement components of the weighted kappa coefficient. This information is available for two-way tables that are larger than . For more information, see the section Weighted Kappa Coefficient.

requests confidence limits for the binomial proportion. You can specify one or more types of confidence limits. When you specify only one type, you can omit the parentheses around the request. PROC FREQ displays the confidence limits in the "Binomial Confidence Limits" table.

The ALPHA= option determines the level of the confidence limits that the CL= binomial-option provides. By default, ALPHA=0.05, which produces 95% confidence limits for the binomial proportion.

You can specify the CL= binomial-option with or without requests for binomial tests. The confidence limits that CL= produces do not depend on the tests that you request and do not use the value of the test margin (which you can specify in the MARGIN= binomial-option).

If you do not specify the CL= binomial-option, the BINOMIAL option displays Wald and exact (Clopper-Pearson) confidence limits in the "Binomial Proportion" table.

You can specify the following types:

includes a continuity correction in the Wald confidence limits, Wald tests, and Wilson confidence limits.

You can request continuity corrections individually for Wald or Wilson confidence limits by specifying the CL=WALD(CORRECT) or CL=WILSON(CORRECT) binomial-option, respectively.

requests a test of equivalence for the binomial proportion. For more information, see the section Equivalence Test. You can specify the equivalence test margins, the null proportion, and the variance type in the MARGIN=, P=, and VAR= binomial-options, respectively. To request an exact equivalence test, you can specify the BINOMIAL option in the EXACT statement.

specifies the variable level for the binomial proportion. You can specify the level-number, which is the order in which the level appears in the one-way frequency table. Or you can specify the level-value, which is the formatted value of the variable level. The level-number must be a positive integer. You must enclose the level-value in single quotes.

By default, PROC FREQ computes the binomial proportion for the first variable level that appears in the one-way frequency table.

specifies the margin for the noninferiority, superiority, and equivalence tests, which you can request by specifying the NONINF, SUP, and EQUIV binomial-options, respectively. By default, MARGIN=0.2.

For noninferiority and superiority tests, specify a single value in the MARGIN= option. The MARGIN= value must be a positive number. You can specify value as a number between 0 and 1. Or you can specify value in percentage form as a number between 1 and 100, and PROC FREQ converts that number to a proportion. PROC FREQ treats the value 1 as 1%.

For noninferiority and superiority tests, the test limits must be between 0 and 1. The limits are determined by the null proportion value (which you can specify in the P= binomial-option) and by the margin value. The noninferiority limit is the null proportion minus the margin. By default, the null proportion is 0.5 and the margin is 0.2, which produces a noninferiority limit of 0.3. The superiority limit is the null proportion plus the margin, which is 0.7 by default.

For an equivalence test, you can specify a single MARGIN= value, or you can specify both lower and upper values. If you specify a single MARGIN= value, it must be a positive number, as described previously. If you specify a single MARGIN= value for an equivalence test, PROC FREQ uses –value as the lower margin and value as the upper margin for the test. If you specify both lower and upper values for an equivalence test, you can specify them in proportion form as numbers between –1 and 1. Or you can specify them in percentage form as numbers between –100 and 100, and PROC FREQ converts the numbers to proportions. The value of lower must be less than the value of upper.

The equivalence limits must be between 0 and 1. The equivalence limits are determined by the null proportion value (which you can specify in the P= binomial-option) and by the margin values. The lower equivalence limit is the null proportion plus the lower margin. By default, the null proportion is 0.5 and the lower margin is –0.2, which produces a lower equivalence limit of 0.3. The upper equivalence limit is the null proportion plus the upper margin, which is 0.7 by default.

For more information, see the sections Noninferiority Test and Equivalence Test.

requests a test of noninferiority for the binomial proportion. For more information, see the section Noninferiority Test. You can specify the noninferiority test margin, the null proportion, and the variance type in the MARGIN=, P=, and VAR= binomial-options, respectively. To request an exact noninferiority test, you can specify the BINOMIAL option in the EXACT statement.

includes the variables LevelNumber and LevelValue in all ODS output data sets that PROC FREQ produces when you specify the BINOMIAL option in the TABLES statement. The OUTLEVEL option also includes the variables LevelNumber and LevelValue in the statistics output data set that PROC FREQ produces when you specify the BINOMIAL option in the OUTPUT statement.

The LevelNumber and LevelValue variables identify the analysis variable level for which PROC FREQ computes the binomial proportion. The value of LevelNumber is the order of the level in the one-way frequency table. The value of LevelValue is the formatted value of the level. You can specify the OUTLEVEL binomial-option with or without the LEVEL= binomial-option.

specifies the null hypothesis proportion for the binomial tests. The null proportion value must be a positive number. You can specify value as a number between 0 and 1. Or you can specify value in percentage form (as a number between 1 and 100), and PROC FREQ converts that number to a proportion. PROC FREQ treats the value 1 as 1%. By default, P=0.5.

requests a test of superiority for the binomial proportion. For more information, see the section Superiority Test. You can specify the superiority test margin, the null proportion, and the variance type in the MARGIN=, P=, and VAR= binomial-options, respectively. To request an exact superiority test, you can specify the BINOMIAL option in the EXACT statement.

specifies the type of variance to use in the Wald tests of noninferiority, superiority, and equivalence. If you specify VAR=SAMPLE, PROC FREQ computes the variance estimate by using the sample proportion. If you specify VAR=NULL, PROC FREQ computes a test-based variance by using the null hypothesis proportion (which you can specify in the P= binomial-option). For more information, see the sections Noninferiority Test and Equivalence Test. The default is VAR=SAMPLE.

specifies the degrees of freedom for the chi-square tests. The value of df must not be 0. If the value of df is positive, PROC FREQ uses df as the degrees of freedom for the chi-square tests. If the value of df is negative, PROC FREQ uses df to adjust the default degrees of freedom for the chi-square tests.

By default for one-way tables, the value of df is (n – 1), where n is the number of variable levels in the table. By default for two-way tables, the value of df is (r – 1) (c – 1), where r is the number of rows in the table and c is the number of columns. See the sections Chi-Square Test for One-Way Tables and Chi-Square Tests and Statistics for more information.

If you specify a negative value of df, PROC FREQ adjusts the default degrees of freedom by adding the (negative) value of df to the default value to produce the adjusted degrees of freedom. The adjusted degrees of freedom must be positive.

The DF= chisq-option specifies or adjusts the degrees of freedom for the following chi-square tests: the Pearson and likelihood ratio goodness-of-fit tests for one-way tables; and the Pearson, likelihood ratio, and Mantel-Haenszel chi-square tests for two-way tables.

requests the likelihood ratio goodness-of-fit test for one-way tables. See the section Likelihood Ratio Chi-Square Test for One-Way Tables for more information.

By default, this test is based on the null hypothesis of equal proportions. You can provide null hypothesis proportions or frequencies by specifying the TESTP= or TESTF= chisq-option, respectively. You can request an exact likelihood ratio goodness-of-fit test by specifying the LRCHI option in the EXACT statement.

specifies null hypothesis frequencies for the one-way chi-square goodness-of-fit tests. For more information, see the section Chi-Square Test for One-Way Tables. You can list the null frequencies as values in parentheses after TESTF=. Or you can provide the null frequencies in a secondary input data set by specifying TESTF=SAS-data-set. The TESTF=SAS-data-set cannot be the same data set that you specify in the DATA= option. You can specify only one TESTF= or TESTP= data set in a single invocation of the procedure.

If you list the null frequencies as values, you can separate the values with blanks or commas. The values must be positive numbers. The number of values must equal the number of variable levels in the one-way table. The sum of the values must equal the total frequency for the one-way table. Order the values to match the order in which the corresponding variable levels appear in the one-way frequency table.

If you provide the null frequencies in a secondary input data set (TESTF=SAS-data-set), the variable that contains the null frequencies should be named _TESTF_, TestFrequency, or Frequency. The null frequencies must be positive numbers. The number of frequencies must equal the number of levels in the one-way frequency table, and the sum of the frequencies must equal the total frequency for the one-way table. Order the null frequencies in the data set to match the order in which the corresponding variable levels appear in the one-way frequency table.

specifies null hypothesis proportions for the one-way chi-square goodness-of-fit tests. For more information, see the section Chi-Square Test for One-Way Tables. You can list the null proportions as values in parentheses after TESTP=. Or you can provide the null proportions in a secondary input data set by specifying TESTP=SAS-data-set. The TESTP=SAS-data-set cannot be the same data set that you specify in the DATA= option. You can specify only one TESTF= or TESTP= data set in a single invocation of the procedure.

If you list the null proportions as values, you can separate the values with blanks or commas. The values must be positive numbers. The number of values must equal the number of variable levels in the one-way table. Order the values to match the order in which the corresponding variable levels appear in the one-way frequency table. You can specify values in probability form as numbers between 0 and 1, where the proportions sum to 1. Or you can specify values in percentage form as numbers between 0 and 100, where the percentages sum to 100.

If you provide the null proportions in a secondary input data set (TESTP=SAS-data-set), the variable that contains the null proportions should be named _TESTP_, TestPercent, or Percent. The null proportions must be positive numbers. The number of proportions must equal the number of levels in the one-way frequency table. You can provide the proportions in probability form as numbers between 0 and 1, where the proportions sum to 1. Or you can provide the proportions in percentage form as numbers between 0 and 100, where the percentages sum to 100. Order the null proportions in the data set to match the order in which the corresponding variable levels appear in the one-way frequency table.

controls the warning message for the validity of the asymptotic Pearson chi-square test. By default, PROC FREQ displays a warning message when more than 20% of the table cells have expected frequencies that are less than 5. If you specify the NOPRINT option in the PROC FREQ statement, the procedure displays the warning in the log; otherwise, the procedure displays the warning as a footnote in the chi-square table. You can use the WARN= option to suppress the warning and to include a warning indicator in the output data set.

You can specify one or more of the following types in the WARN= option. If you specify more than one type value, enclose the values in parentheses after WARN=. For example, warn = (output noprint).

If you specify the WARN=OUTPUT option, the ODS output data set ChiSq contains a variable named Warning that equals 1 for the Pearson chi-square observation when more than 20% of the table cells have expected frequencies that are less than 5 and equals 0 otherwise. If you specify WARN=OUTPUT and also specify the CHISQ option in the OUTPUT statement, the statistics output data set contains a variable named WARN_PCHI that indicates the warning.

The WARN=NOLOG option has the same effect as the NOWARN option in the TABLES statement.

requests Tarone’s adjustment in the Breslow-Day test for homogeneity of odds ratios. For more information, see the section Breslow-Day Test for Homogeneity of the Odds Ratios.

requests the Gail-Simon test for qualitative interaction, which applies to stratified tables. For more information, see the section Gail-Simon Test for Qualitative Interactions.

The COLUMN= option specifies the column of the risk differences to use in computing the Gail-Simon test. By default, PROC FREQ uses column 1 risk differences. If you specify COLUMN=2, PROC FREQ uses column 2 risk differences.

The GAILSIMON cmh-option has the same effect as the GAILSIMON option in the TABLES statement.

requests the Mantel-Fleiss criterion for the Mantel-Haenszel statistic for stratified tables. For more information, see the section Mantel-Fleiss Criterion.

displays the standardized residuals of the table cells in the CROSSLIST table. The standardized residual is the ratio of (frequency – expected) to its standard error, where frequency is the table cell frequency (count) and expected is the expected table cell frequency, which is computed under the null hypothesis that the row and column variables are independent. For more information, see the section Standardized Residuals. You can display the expected values and deviations by specifying the EXPECTED and DEVIATION options, respectively.

displays the Pearson residuals of the table cells in the CROSSLIST table. The Pearson residual is the square root of the table cell’s contribution to the Pearson chi-square statistic. The Pearson residual is computed as , where frequency is the table cell frequency (count) and expected is the expected table cell frequency, which is computed under the null hypothesis that the row and column variables are independent. For more information, see the section Pearson Chi-Square Test for Two-Way Tables. You can display the expected values, deviations, and cell chi-squares by specifying the EXPECTED, DEVIATION, and CELLCHI2 options, respectively.

displays exact confidence limits for the odds ratio in the "Confidence Limits for the Odds Ratio" table. (By default, PROC FREQ displays the exact confidence limits in a separate table.) You must also request computation of the exact confidence limits by specifying the OR option in the EXACT statement. For more information, see the subsection "Exact Confidence Limits" in the section Confidence Limits for the Odds Ratio.

requests likelihood ratio confidence limits for the odds ratio. For more information, see the subsection "Likelihood Ratio Confidence Limits" in the section Confidence Limits for the Odds Ratio.

requests exact mid-p confidence limits for the odds ratio. For more information, see the subsection "Exact Mid-p Confidence Limits" in the section Confidence Limits for the Odds Ratio.

requests score confidence limits for the odds ratio. For more information, see the subsection "Score Confidence Limits" in the section Confidence Limits for the Odds Ratio. If you specify CORRECT=NO, PROC FREQ provides the uncorrected form of the score confidence limits.

requests asymptotic Wald confidence limits, which are based on a log transformation of the odds ratio. For more information, see the subsection "Wald Confidence Limits" in the section Confidence Limits for the Odds Ratio.

requests Wald modified confidence limits for the odds ratio. For more information, see the subsection "Wald Modified Confidence Limits" in the section Confidence Limits for the Odds Ratio.

specifies the convergence criterion for computing the polychoric correlation. The convergence criterion value must be a positive number. By default, CONVERGE=0.0001. Iterative computation of the polychoric correlation stops when the convergence measure falls below value or when the number of iterations exceeds the MAXITER= number, whichever happens first. For parameter values that are less than 0.01, PROC FREQ evaluates convergence by using the absolute difference instead of the relative difference. For more information, see the section Polychoric Correlation.

specifies the maximum number of iterations for computing the polychoric correlation. The value of number must be a positive integer. By default, MAXITER=20. Iterative computation of the polychoric correlation stops when the number of iterations exceeds the maximum number or when the convergence measure falls below the CONVERGE= value, whichever happens first. For more information, see the section Polychoric Correlation.

requests an agreement plot (Bangdiwala and Bryan 1987), An agreement plot displays the strength of agreement in a two-way table, where the row and column variables represent two independent ratings of n subjects. For information about agreement plots, see Bangdiwala (1988), Bangdiwala et al. (2008), and Friendly (2000, Section 3.7.2).

To produce an agreement plot, you must also specify the AGREE option in the TABLES statement. Agreement statistics and plots are available for two-way square tables, where the number of rows equals the number of columns.

Table 3.12 lists the plot-options that are available for agreement plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

If you specify the STATS plot-option, the agreement plot displays the values of the kappa coefficient, the weighted kappa coefficient, the measure (Bangdiwala and Bryan 1987), and the sample size. PROC FREQ stores these statistics in an ODS table named BnMeasure, which is not displayed. For more information, see the section ODS Table Names.

requests all plots that are associated with the specified analyses. Table 3.11 lists the available plot-requests and the corresponding analysis options. If you specify the PLOTS=ALL option, PROC FREQ produces the frequency, cumulative frequency, and mosaic plots that are associated with the tables that you request. (These plots are not produced by default when ODS Graphics is enabled.)

requests a plot of cumulative frequencies. Cumulative frequency plots are available for one-way frequency tables.

To produce a cumulative frequency plot, you must specify the CUMFREQPLOT plot-request in the PLOTS= option, or you must specify the PLOTS=ALL option. PROC FREQ does not produce cumulative frequency plots by default when ODS Graphics is enabled.

Table 3.13 lists the plot-options that are available for cumulative frequency plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

requests a plot of relative deviations from expected frequencies. Deviation plots are available for chi-square analysis of one-way frequency tables. To produce a deviation plot, you must also specify the CHISQ option in the TABLES statement for a one-way frequency table.

Table 3.14 lists the plot-options that are available for deviation plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

requests a frequency plot. Frequency plots are available for frequency and crosstabulation tables. For multiway crosstabulation tables, PROC FREQ provides a two-way frequency plot for each stratum (two-way table).

To produce a frequency plot, you must specify the FREQPLOT plot-request in the PLOTS= option, or you must specify the PLOTS=ALL option. PROC FREQ does not produce frequency plots by default when ODS Graphics is enabled.

Table 3.15 lists the plot-options that are available for frequency plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

You can specify the following plot-options for all frequency plots: ORIENT=, SCALE=, and TYPE=. You can specify the following plot-options for frequency plots of two-way (and multiway) tables: GROUPBY=, NPANELPOS=, and TWOWAY=. The NPANELPOS= plot-option is not available with the TWOWAY=CLUSTER or TWOWAY=STACKED layout, which is always displayed in a single panel.

By default, PROC FREQ displays frequency plots as bar charts. To display frequency plots as dot plots, specify TYPE=DOTPLOT. To plot percentages instead of frequencies, specify SCALE=PERCENT. For two-way tables, there are four frequency plot layouts available, which you can request by specifying the TWOWAY= plot-option. For more information, see the subsection "Plot Options" in this section.

By default, graph cells in a two-way layout are first grouped by column variable levels; row variable levels are then displayed within the column variable levels. To group first by row variable levels, specify GROUPBY=ROW.

requests a plot of kappa statistics along with confidence limits. Kappa plots are available for multiway square tables and display the kappa statistic (with confidence limits) for each two-way table (stratum). Kappa plots also display the overall kappa statistic unless you specify the COMMON=NO plot-option. To produce a kappa plot, you must specify the AGREE option in the TABLES statement to compute kappa statistics.

Table 3.16 lists the plot-options that are available for kappa plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

requests a mosaic plot. Mosaic plots are available for two-way and multiway crosstabulation tables; for multiway tables, PROC FREQ provides a mosaic plot for each two-way table (stratum).

To produce a mosaic plot, you must specify the MOSAICPLOT plot-request in the PLOTS= option, or you must specify the PLOTS=ALL option. PROC FREQ does not produce mosaic plots by default when ODS Graphics is enabled.

Mosaic plots display tiles that correspond to the crosstabulation table cells. The areas of the tiles are proportional to the frequencies of the table cells. The column variable is displayed on the X axis, and the tile widths are proportional to the relative frequencies of the column variable levels. The row variable is displayed on the Y axis, and the tile heights are proportional to the relative frequencies of the row levels within column levels. For more information, see Friendly (2000).

By default, the colors of the tiles correspond to the row variable levels. If you specify the COLORSTAT= plot-option, the tiles are colored according to the values of the Pearson or standardized residuals.

You can specify the following plot-options:

suppresses all plots.

requests a plot of odds ratios along with confidence limits. Odds ratio plots are available for multiway tables and display the odds ratio (with confidence limits) for each table (stratum). To produce an odds ratio plot, you must also specify the MEASURES, OR, or RELRISK option in the TABLES statement to compute the odds ratios.

Table 3.17 lists the plot-options that are available for odds ratio plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

You can specify one of the following confidence limit types for the odds ratio plot: exact (CL=EXACT), likelihood ratio (CL=LR), exact mid-p (CL=MIDP), score (CL=SCORE), Wald (CL=WALD), or Wald modified (CL=WALDMODIFIED). By default, the odds ratio plot displays Wald confidence limits. For more information, see the descriptions of the CL= plot-option and the OR(CL=) option.

To display exact confidence limits in the odds ratio plot, you must also request their computation by specifying the OR option in the EXACT statement.

When CL=WALD or CL=EXACT, the odds ratio plot displays the common odds ratio by default when it is available. To compute the common odds ratio along with Wald confidence limits, specify the CMH option in the TABLES statement. To compute the common odds ratio along with exact confidence limits, specify the COMOR option in the EXACT statement. To suppress display of the common odds ratio, specify COMMON=NO.

requests a plot of relative risks along with confidence limits. Relative risk plots are available for multiway tables and display the relative risk (with confidence limits) for each table (stratum). To produce a relative risk plot, you must also specify the MEASURES or RELRISK option in the TABLES statement to compute relative risks.

Table 3.17 lists the plot-options that are available for relative risk plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

You can specify one of the following confidence limit types for the relative risk plot: exact (CL=EXACT), likelihood ratio (CL=LR), score (CL=SCORE), Wald (CL=WALD), or Wald modified (CL=WALDMODIFIED). By default, the relative risk plot displays Wald confidence limits. For more information, see the descriptions of the CL= plot-option and the RELRISK(CL=) option.

To display exact confidence limits in the relative risk plot, you must also request their computation by specifying the RELRISK option in the EXACT statement. The risk column that you specify for the confidence limits must match the risk column that you specify for the plot.

The relative risk plot displays the common relative risk by default when you specify CL=WALD and the CMH option in the TABLES statement. To suppress display of the common relative risk, specify COMMON=NO.

requests a plot of risk (proportion) differences along with confidence limits. Risk difference plots are available for multiway tables and display the risk difference (with confidence limits) for each table (stratum). To produce a risk difference plot, you must also specify the RISKDIFF option in the TABLES statement to compute risk differences.

Table 3.17 lists the plot-options that are available for risk difference plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

You can specify one of the following confidence limit types for the risk difference plot: Agresti-Caffo (CL=AC), exact (CL=EXACT), Hauck-Anderson (CL=HA), Miettinen-Nurminen (score) (CL=MN), Newcombe (CL=NEWCOMBE), and Wald (CL=WALD). By default, the plot displays Wald confidence limits for the risk difference. For more information, see the descriptions of the CL= plot-option and the RISKDIFF(CL=) option.

To display exact confidence limits in the risk difference plot, you must also request their computation by specifying the RISKDIFF option in the EXACT statement. The risk column that you specify for the confidence limits must match the risk column that you specify for the plot.

By default, the risk difference plot displays the common risk difference when you specify the RISKDIFF(COMMON) option and one of the following confidence limit types in the CL= plot-option: Miettinen-Nurminen (score) (CL=MN), Newcombe (CL=NEWCOMBE), or Wald (CL=WALD). To suppress display of the common risk difference, specify COMMON=NO.

requests a plot of weighted kappa coefficients along with confidence limits. Weighted kappa plots are available for multiway square tables and display the weighted kappa coefficient (with confidence limits) for each two-way table (stratum). Weighted kappa plots also display the overall weighted kappa coefficient unless you specify the COMMON=NO plot-option.

To produce a weighted kappa plot, you must specify the AGREE option in the TABLES statement to compute weighted kappa coefficients, and the table dimension must be greater than 1.

Table 3.16 lists the plot-options that are available for weighted kappa plots. For descriptions of the plot-options, see the subsection "Plot Options" in this section.

suppresses the default plots and requests only the plots that are specified as plot-requests.

specifies the type of confidence limits to display. You can specify the CL= plot-option when you specify any of the following plot-requests: ODDSRATIOPLOT, RELRISKPLOT, and RISKDIFFPLOT.

For odds ratio plots (ODDSRATIOPLOT), the available confidence limit types include the following: exact (CL=EXACT), likelihood ratio (CL=LR), exact mid-p (CL=MIDP), score (CL=SCORE), Wald (CL=WALD), and Wald modified (CL=WALDMODIFIED). For more information, see the description of the OR(CL=) option and the section Confidence Limits for the Odds Ratio. By default, CL=WALD. When you specify CL=EXACT to display exact confidence limits, you must also request computation of exact confidence limits by specifying the OR option in the EXACT statement.

For relative risk plots (RELRISKPLOT), the available confidence limit types include the following: exact (CL=EXACT), likelihood ratio (CL=LR), score (CL=SCORE), Wald (CL=WALD), and Wald modified (CL=WALDMODIFIED). For more information, see the description of the RELRISK(CL=) option and the section Confidence Limits for the Relative Risk. By default, CL=WALD. When you specify CL=EXACT to display exact confidence limits, you must also request computation of exact confidence limits by specifying the RELRISK option in the EXACT statement.

For risk difference plots (RISKDIFFPLOT), the available confidence limit types include the following: Agresti-Caffo (CL=AC), exact (CL=EXACT), Hauck-Anderson (CL=HA), Miettinen-Nurminen (score) (CL=MN), Newcombe (CL=NEWCOMBE), and Wald (CL=WALD). For more information, see the description of the RISKDIFF(CL=) option and the section Confidence Limits for the Risk Difference. By default, CL=WALD. When you specify CL=EXACT to display exact confidence limits in the plot, you must also request computation of exact confidence limits by specifying the RISKDIFF option in the EXACT statement.

controls the appearance of the confidence limit error bars. You can specify the CLDISPLAY= plot-option when you specify the following plot-requests: KAPPAPLOT, ODDSRATIOPLOT, RELRISKPLOT, RISKDIFFPLOT, and WTKAPPAPLOT.

The default is CLDISPLAY=SERIF, which displays the confidence limits as lines with serifs. CLDISPLAY=LINE displays the confidence limits as plain lines without serifs. The CLDISPLAY=SERIFARROW and CLDISPLAY=LINEARROW plot-options display arrowheads on any error bars that are clipped by the RANGE= plot-option; if an entire error bar is cut from the plot, the plot displays an arrowhead that points toward the statistic.

CLDISPLAY=BAR displays the confidence limits as bars. By default, the width of the bars equals the size of the marker for the estimate. You can control the width of the bars and the size of the marker by specifying the value of width as a percentage of the distance between bars, . The bar might disappear when the value of width is very small.

specifies the table column to use to compute the risks (proportion) for the relative risk plot (RELRISKPLOT) and the risk difference plot (RISKDIFFPLOT). If you specify COLUMN=1, the plot displays the column 1 relative risks or the column 1 risk differences. Similarly, if you specify COLUMN=2, the plot displays the column 2 relative risks or risk differences.

For relative risk plots, the default is COLUMN=1. For risk difference plots, the default is COLUMN=1 if you request computation of both column 1 and column 2 risk differences by specifying the RISKDIFF option. If you request computation of only the column 1 (or column 2) risk differences by specifying the RISKDIFF(COLUMN=1) (or RISKDIFF(COLUMN=2)) option, by default the risk difference plot displays the risk differences for the column that you specify.

controls the display of the common (overall) statistic in plots that display stratum (two-way table) statistics for multiway tables. You can specify the COMMON= plot-option when you specify the following plot-requests: KAPPAPLOT, ODDSRATIOPLOT, RELRISKPLOT, RISKDIFFPLOT, and WTKAPPAPLOT.

COMMON=NO suppresses display of the common statistic and its confidence limits. By default, COMMON=YES, which displays the common statistic and its confidence limits when these values are available. For more information, see the descriptions of the plot-requests.

requests display of exact confidence limits instead of asymptotic confidence limits. You can specify the EXACT plot-option when you specify the following plot-requests: ODDSRATIOPLOT, RELRISKPLOT, and RISKDIFFPLOT. The EXACT plot-option is equivalent to the CL=EXACT plot-option.

When you specify the EXACT plot-option, you must also request computation of exact confidence limits by specifying the appropriate statistic-option in the EXACT statement.

specifies the primary grouping for two-way frequency plots, which you can request by specifying the FREQPLOT plot=request. The default is GROUPBY=COLUMN, which groups graph cells first by column variable and displays row variable levels within column variable levels. You can specify GROUPBY=ROW to group first by row variable. In two-way and multiway table requests, the column variable is the last variable specified and forms the columns of the crosstabulation table. The row variable is the next-to-last variable specified and forms the rows of the table.

By default for a bar chart that is displayed in the TWOWAY=STACKED layout, bars correspond to the column variable levels, and row levels are displayed (stacked) within each column bar. By default for a bar chart that is displayed in the TWOWAY=CLUSTER layout, bars are first grouped by column variable levels, and row levels are displayed as adjacent bars within each column-level group. You can reverse the default row and column variable grouping by specifying GROUPBY=ROW.

applies to the odds ratio plot (ODDSRATIOPLOT) and the relative risk plot (RELRISKPLOT). This plot-option displays the odds ratio or relative risk axis on the log scale that you specify.

applies to the agreement plot (AGREEPLOT). LEGEND=NO suppresses the legend that identifies the areas of exact and partial agreement. The default is LEGEND=YES.

applies to the deviation plot (DEVIATIONPLOT). NOSTAT suppresses the chi-square p-value that deviation plot displays by default.

divides the plot into multiple panels that display at most statistics or sections.

If n is positive, the number of statistics or sections per panel is balanced; if n is negative, the number of statistics per panel is not balanced. For example, suppose you want to display 21 odds ratios. NPANELPOS=20 displays two panels, the first with 11 odds ratios and the second with 10 odds ratios; NPANELPOS=–20 displays 20 odds ratios in the first panel but only 1 odds ratio in the second panel. This plot-option is available for all plots except mosaic plots and one-way weighted frequency plots.

For two-way frequency plots (FREQPLOT), NPANELPOS=n requests that panels display at most sections, where sections correspond to row or column variable levels, depending on the type of plot and the grouping. By default, n=4 and each panel includes at most four sections. This plot-option applies to two-way plots that are displayed in the TWOWAY=GROUPVERTICAL or TWOWAY=GROUPHORIZONTAL layout. The NPANELPOS= plot-option does not apply to the TWOWAY=CLUSTER and TWOWAY=STACKED layouts, which are always displayed in a single panel.

For plots that display statistics along with confidence limits, NPANELPOS=n requests that panels display at most statistics. By default, n=0 and all statistics are displayed in a single panel. This plot-option applies to the following plots: KAPPAPLOT, ODDSRATIOPLOT, RELRISKPLOT, RISKDIFFPLOT, and WTKAPPAPLOT.

displays the two-way table (strata) statistics in order of the statistic value. You can specify the ORDER= plot-option when you specify the following plot-requests: KAPPAPLOT, ODDSRATIOPLOT, RELRISKPLOT, RISKDIFFPLOT, and WTKAPPAPLOT.

If you specify ORDER=ASCENDING or ORDER=DESCENDING, the plot displays the statistics in ascending or descending order, respectively. By default, the order of the statistics in the plot matches the order that the two-way table strata appear in the multiway table display.

controls the orientation of the plot. You can specify the ORIENT= plot-option when you specify the following plot-requests: CUMFREQPLOT, DEVIATIONPLOT, and FREQPLOT.

ORIENT=HORIZONTAL places the variable levels on the Y axis and the frequencies, percentages, or statistic values on the X axis. ORIENT=VERTICAL places the variable levels on the X axis. The default orientation is ORIENT=VERTICAL for bar charts (TYPE=BARCHART) and ORIENT=HORIZONTAL for dot plots (TYPE=DOTPLOT).

controls the display of partial agreement in the agreement plot (AGREEPLOT). PARTIAL=NO suppresses the display of partial agreement. When you specify PARTIAL=NO, the agreement plot displays only exact agreement. Exact agreement includes the diagonal cells of the square table, where the row and column variable levels are the same. Partial agreement includes the adjacent off-diagonal table cells, where the row and column values are within one level of exact agreement. The default is PARTIAL=YES.

specifies the range of values to display. You can specify the RANGE= plot-option when you specify the following plot-requests: KAPPAPLOT, ODDSRATIOPLOT, RELRISKPLOT, RISKDIFFPLOT, and WTKAPPAPLOT.

If you specify RANGE=CLIP, the confidence limits are clipped and the display range is determined by the minimum and maximum values of the statistics. By default, the display range includes all confidence limits.

specifies the scale of the frequencies to display. This plot-option is available for frequency plots (FREQPLOT) and cumulative frequency plots (CUMFREQPLOT).

The default is SCALE=FREQ, which displays unscaled frequencies. SCALE=PERCENT displays percentages (relative frequencies) of the total frequency. SCALE=LOG displays log (base 10) frequencies. SCALE=SQRT displays square roots of the frequencies, producing a plot known as a rootogram.

SCALE=GROUPPERCENT is available for two-way frequency plots. This option displays the row or column percentages instead of the overall percentages (of the table frequency). By default (or when you specify the GROUPBY=COLUMN plot-option), SCALE=GROUPPERCENT displays the column percentages. If you specify the GROUPBY=ROW plot-option, the primary grouping of graph cells is by row variable level and the plot displays row percentages. For more information, see the description of the GROUPBY= plot-option.

controls the display of the cumulative frequency scale on the right side of the agreement plot (AGREEPLOT). SHOWSCALE=NO suppresses the display of the scale. The default is SHOWSCALE=YES.

displays statistic values in the plot. For the following plot-requests, the STATS plot-option displays the statistics and their confidence limits on the right side of the plot: KAPPAPLOT, ODDSRATIOPLOT, RELRISKPLOT, RISKDIFFPLOT, and WTKAPPAPLOT.

For the agreement plot (AGREEPLOT), the STATS plot-option displays the values of the kappa statistic, the weighted kappa statistic, the measure (Bangdiwala and Bryan 1987), and the sample size. PROC FREQ stores these statistics in an ODS table named BnMeasure, which is not displayed. For more information, see the section ODS Table Names.

If you do not request the STATS plot-option, these plots do not display the statistic values.

specifies the layout for two-way frequency plots.

All TWOWAY= layouts are available for bar charts (TYPE=BARCHART). All TWOWAY= layouts except TWOWAY=CLUSTER are available for dot plots (TYPE=DOTPLOT). The ORIENT= and GROUPBY= plot-options are available for all TWOWAY= layouts.

The default two-way layout is TWOWAY=GROUPVERTICAL, which produces a grouped plot that has a vertical common baseline. By default for bar charts (TYPE=BARCHART, ORIENT=VERTICAL), the X axis displays column variable levels, and the Y axis displays frequencies. The plot includes a vertical (Y-axis) block for each row variable level. The relative positions of the graph cells in this plot layout are the same as the relative positions of the table cells in the crosstabulation table. You can reverse the default row and column grouping by specifying the GROUPBY=ROW plot-option.

The TWOWAY=GROUPHORIZONTAL layout produces a grouped plot that has a horizontal common baseline. By default (GROUPBY=COLUMN), the plot displays a block on the X axis for each column variable level. Within each column-level block, the plot displays row variable levels.

The TWOWAY=STACKED layout produces stacked displays of frequencies. By default (GROUPBY=COLUMN) in a stacked bar chart, the bars correspond to column variable levels, and row levels are stacked within each column level. By default in a stacked dot plot, the dotted lines correspond to column levels, and cell frequencies are plotted as data dots on the corresponding column line. The dot color identifies the row level.

The TWOWAY=CLUSTER layout, which is available only for bar charts, displays groups of adjacent bars. By default, the primary grouping is by column variable level, and row levels are displayed within each column level.

You can reverse the default row and column grouping in any layout by specifying the GROUPBY=ROW plot-option. The default is GROUPBY=COLUMN, which groups first by column variable.

specifies the plot type (format) of the frequency (FREQPLOT), cumulative frequency (CUMFREQPLOT), and deviation plots (DEVIATIONPLOT). TYPE=BARCHART produces a bar chart and TYPE=DOTPLOT produces a dot plot. The default is TYPE=BARCHART.

specifies confidence limit types for the relative risk. You can specify one or more types of confidence limits. When you specify only one type, you can omit the parentheses around the request. When you specify the CL= relrisk-option, PROC FREQ displays the confidence limits in the "Confidence Limits for the Relative Risk" table.

The ALPHA= option determines the level of the confidence limits that the CL= relrisk-option provides. By default, ALPHA=0.05, which produces 95% confidence limits for the relative risk.

You can specify the following types:

specifies the table column for which to compute the relative risk confidence limits (which you request by specifying the CL= relrisk-option) and the relative risk tests (EQUAL, EQUIV, NONINF, and SUP). By default, COLUMN=1.

This option has no effect on the "Odds Ratio and Relative Risks" table, which displays both column 1 and column 2 relative risks.

requests an equality test for the relative risk. For more information, see the subsection "Equality Test" in the section Relative Risk Tests. You can specify the test in the METHOD= relrisk-option, and you can specify the null hypothesis value of the relative risk in the NULL= option. The null value must be a positive number. By default, METHOD=WALD and NULL=1.

requests an equivalence test for the relative risk. For more information, see the subsection "Equivalence Test" in the section Relative Risk Tests. You can specify the test method in the METHOD= relrisk-option, and you can specify the test margins in the MARGIN= relrisk-option. By default, METHOD=WALD and MARGIN=(0.8,1.25).

specifies the margin for the noninferiority, superiority, and equivalence tests, which you request by specifying the NONINF, SUP, and EQUIV relrisk-options, respectively. By default, MARGIN=0.8 for noninferiority tests, MARGIN=1.25 for superiority tests, and MARGIN=(0.8,1.25) for equivalence tests.

For noninferiority and superiority tests, specify a single value in the MARGIN= option. The value must be a positive number. For a noninferiority test, the value should be less than 1; for a superiority test, the value should be greater than 1.

For an equivalence test, you can specify a single MARGIN= value, or you can specify both lower and upper values. All values must be positive numbers. If you specify a single value, PROC FREQ uses value as the lower margin and the inverse of value as the upper margin. If you specify both lower and upper values, the value of lower must be less than the value of upper.

specifies the method to be used for the equality, equivalence, noninferiority, and superiority tests, which you request by specifying the EQUAL, EQUIV, NONINF, and SUP relrisk-options, respectively. By default, METHOD=WALD.

You can specify one of the following methods:

requests a noninferiority test for the relative risk. For more information, see the subsection "Noninferiority Test" in the section Relative Risk Tests. You can specify the test method in the METHOD= relrisk-option, and you can specify the margin in the MARGIN= relrisk-option. By default, METHOD=WALD and MARGIN=0.8.

displays the "Odds Ratio and Relative Risks" table when you request tests or additional confidence limits by specifying relrisk-options. By default, PROC FREQ does not display this table when you request tests or additional confidence limits for the relative risk.

requests a superiority test for the relative risk. For more information, see the subsection "Superiority Test" in the section Relative Risk Tests. You can specify the test method in the METHOD= relrisk-option, and you can specify the margin in the MARGIN= relrisk-option. By default, METHOD=WALD and MARGIN=1.25.

requests confidence limits for the risk difference. You can specify one or more types of confidence limits. When you specify only one type, you can omit the parentheses around the request. PROC FREQ displays the confidence limits in the "Confidence Limits for the Proportion (Risk) Difference" table.

The ALPHA= option determines the level of the confidence limits. By default, ALPHA=0.05, which produces 95% confidence limits for the risk difference.

You can specify the CL= riskdiff-option with or without requests for risk difference tests. The confidence limits that CL= produces do not depend on the tests that you request and do not use the value of the test margin (which you can specify in the MARGIN= riskdiff-option).

You can control the risk column for the confidence limits by specifying the COLUMN= riskdiff-option. If you do not specify COLUMN=, by default PROC FREQ provides confidence limits for the column 1 risk difference.

You can specify the following types:

specifies the table column for which to compute the risk difference tests (EQUAL, EQUIV, NONINF, and SUP) and the risk difference confidence limits (which you request by specifying the CL= riskdiff-option). By default, COLUMN=1.

This option has no effect on the "Risk Estimates" table, which is produced for both column 1 and column 2. You can suppress the "Risk Estimates" table by specifying the NORISKS riskdiff-option.

requests estimates of the common (overall) risk difference for multiway tables. PROC FREQ produces Mantel-Haenszel and summary score estimates for the common risk difference, together with their confidence limits. For more information, see the section Common Risk Difference. If you specify the RISKDIFF(CL=NEWCOMBE) option, PROC FREQ also provides Newcombe confidence limits for the common risk difference. For more information, see the section Common Risk Difference.

If you do not specify the COLUMN= riskdiff-option, PROC FREQ provides the common risk difference for column 1 by default. If you specify COLUMN=2, PROC FREQ provides the common risk difference for column 2. COLUMN=BOTH does not apply to the common risk difference.

includes a continuity correction in the Wald confidence limits, Wald tests, and Newcombe confidence limits. For more information, see the section Risks and Risk Differences.

requests an equality test for the risk difference. For more information, see the section Equality Tests. You can specify the test method in the METHOD= riskdiff-option, and you can specify the null hypothesis value of the risk difference in the NULL= option. By default, METHOD=WALD and NULL=0. You can specify the null value in proportion form as a number between –1 and 1, or you can specify the null value in percentage form as a number between –100 and 100. When the value is between –100 and –1 or between 1 and 100, PROC FREQ converts the number to a proportion. PROC FREQ treats the values –1 and 1 as percentages.

requests an equivalence test for the risk difference. For more information, see the section Equivalence Test. You can specify the test method in the METHOD= riskdiff-option, and you can specify the margins in the MARGIN= riskdiff-option. By default, METHOD=WALD and MARGIN=0.2.

specifies the margin for the noninferiority, superiority, and equivalence tests, which you request by specifying the NONINF, SUP, and EQUIV riskdiff-options, respectively. By default, MARGIN=0.2.

For noninferiority and superiority tests, specify a single value in the MARGIN= option. The value must be a positive number. You can specify value as a number between 0 and 1. Or you can specify value in percentage form as a number between 1 and 100, and PROC FREQ converts that number to a proportion. PROC FREQ treats the value 1 as 1%.

For an equivalence test, you can specify a single MARGIN= value, or you can specify both lower and upper values. If you specify a single value, it must be a positive number, as described previously. If you specify a single value for an equivalence test, PROC FREQ uses –value as the lower margin and value as the upper margin for the test. If you specify both lower and upper values for an equivalence test, you can specify them in proportion form as numbers between –1 and 1. Or you can specify them in percentage form as numbers between –100 and 100, and PROC FREQ converts the numbers to proportions. The value of lower must be less than the value of upper.

specifies the method to be used for the equality, equivalence, noninferiority, and superiority tests, which you request by specifying the EQUAL, EQUIV, NONINF, and SUP riskdiff-options, respectively. By default, METHOD=WALD.

You can specify the following methods:

requests a noninferiority test for the risk difference. For more information, see the section Noninferiority Tests. You can specify the test method in the METHOD= riskdiff-option, and you can specify the margin in the MARGIN= riskdiff-option. By default, METHOD=WALD and MARGIN=0.2.

suppresses display of the "Risk Estimates" tables, which the RISKDIFF option produces by default for column 1 and column 2. The "Risk Estimates" tables contain the risks and risk differences, together with their asymptotic standard errors, Wald confidence limits, and exact confidence limits.

requests a superiority test for the risk difference. For more information, see the section Superiority Test. You can specify the test method in the METHOD= riskdiff-option, and you can specify the margin in the MARGIN= riskdiff-option. By default, METHOD=WALD and MARGIN=0.2.

specifies the type of variance to use in the Wald tests of equality, equivalence, noninferiority, and superiority. If you specify VAR=SAMPLE, PROC FREQ uses the sample variance. If you specify VAR=NULL, PROC FREQ uses a test-based variance that is computed by using the null hypothesis value of the risk difference. For more information, see the sections Equality Tests and Noninferiority Tests. The default is VAR=SAMPLE.