![]() This example shows the three ways that PROC FREQ can handle missing values of TABLES variables. Displays missing levels in frequency and crosstabulation tables and includes them in computations of percentages and statistics. Treats missing values as a valid nonmissing level for all TABLES variables. Descriptions follow in alphabetical order. Table 3.4 lists the options available in the PROC FREQ statement. ![]() By default, the procedure uses the most recently created SAS data set. The following options change the way in which PROC FREQ handles missing values of TABLES variables: MISSPRINTÄisplays missing value frequencies in frequency or crosstabulation tables but does not include them in computations of percentages or statistics. The PROC FREQ statement invokes the procedure and optionally identifies the input data set. The NMISS option in the OUTPUT statement provides an output data set variable that contains the missing value frequency. If there are cases with missing values for. ![]() Each frequency table contains four columns of summary measures. The TABLES statement OUT= data set includes an observation that contains the missing value frequency. PROC FREQ creates one frequency table per variable. PROC FREQ also displays the Equivalence Limits and the test-based Confidence Limits. PROC FREQ also reports the number of missing values in output data sets. PROC FREQ displays a two one-sided test (TOST) for equivalence, which includes test statistics (Z) and probability values for the Lower and Upper tests, together with the Overall probability value. The procedure displays the number of missing observations below each table. Also by default, PROC FREQ does not include observations with missing values in the computation of percentages and statistics. If an observation has a missing value for a variable in a TABLES request, by default PROC FREQ does not include that observation in the frequency or crosstabulation table. The missing values form a separate BY group. PROC FREQ treats missing BY variable values like any other BY variable value. ![]() When the value of the WEIGHT variable is missing, PROC FREQ does not include that observation in the analysis. ![]()
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