If you use the NOPRINT option in the PROC SURVEYIMPUTE statement, the procedure does not display any output. Otherwise, PROC SURVEYIMPUTE displays results of the imputation in a collection of tables, which are described in the following subsections.
If you use a CLASS statement, PROC SURVEYIMPUTE displays a "Class Level Information" table, which lists the categories of every CLASS variable that is used in the imputation. The ODS name of the "Class Level Information" table is ClassLevelInfo.
If you specify METHOD=FEFI or METHOD=FHDI, PROC SURVEYIMPUTE displays a "Convergence Status" table, which shows the convergence status of the EM optimization routine. If the optimization routine converges, then the Status is set to 0; otherwise, the Status is set to 1. The ODS name of the "Convergence Status" table is ConvergenceStatus.
If you use a STRATA or CLUSTER statement, PROC SURVEYIMPUTE displays a "Design Summary" table, which provides information about the sample design. The table displays the total number of strata that are read and used, and the total number of clusters that are read and used. The ODS name of the "Design Summary" table is DesignSummary.
If you specify METHOD=FEFI or METHOD=FHDI, PROC SURVEYIMPUTE displays a "Donor Count" table, which shows the number of donor cells in the first-stage FEFI and the number of recipient units that use those donor cells. The ODS name of the "Donor Count" table is DonorCount.
If you specify the PRINTH method-option for VARMETHOD=BRR, PROC SURVEYIMPUTE displays the Hadamard matrix that is used to construct replicates for BRR variance estimation. If you provide a Hadamard matrix by using the HADAMARD= method-option for VARMETHOD=BRR but the procedure does not use the entire matrix, the procedure displays only the rows and columns that are actually used to construct replicates. The ODS name of the "Hadamard Matrix" table is HadamardMatrix.
By default, PROC SURVEYIMPUTE displays an "Imputation Information" table, which provides information about the imputation method. The table displays the two-level name of the input data set, the name and label of the WEIGHT variable, the name and label of each STRATA variable, the name and label of each CLUSTER variable, the name of the imputation method used, the random number generator seed, the name of the replication method, and the number of replicates. The ODS name of the "Imputation Information" table is ImputationInfo.
By default, PROC SURVEYIMPUTE displays an "Imputation Summary" table, which provides summary information about the imputation. The table displays the number of observations and the sum of weights for the following:
Nonmissing observations – all variables specified in the VAR statement have nonmissing values
Missing – at least one variable specified in the VAR statement has a missing value
Missing, Imputed – all missing values have been imputed
Missing, Not Imputed – no missing values are imputed
Missing, Partially Imputed – missing values in some variables are imputed, but missing values in some other variables are not imputed
The ODS name of the "Imputation Summary" table is ImputationSummary.
If you specify METHOD=FEFI or METHOD=FHDI, PROC SURVEYIMPUTE displays an "Iteration History" table, which provides information about the iteration history for the EM algorithm. The table displays iteration numbers, maximum absolute differences, and maximum relative absolute differences for the fractional weights over all the observations. The ODS name of the "Iteration History" table is IterationHistory.
By default, PROC SURVEYIMPUTE displays a "Missing Data Patterns" table, which provides information about the missing data patterns. The table displays the missing data pattern groups, "X" if the variable is observed in the group, and "." if the variable is missing in that group. In addition, it displays observation frequencies, the sum of weights, unweighted percentages, and weighted percentages for each group. The ODS name of the "Missing Data Patterns" table is MissPattern.
By default, PROC SURVEYIMPUTE displays a "Number of Observations" table, which shows the number of observations that are read and used, and the sum of weights that are read and used in the imputation. The ODS name of the "Number of Observations" table is NObs.
If you specify the LIST option in the STRATA statement, PROC SURVEYIMPUTE displays a "Stratum Information" table. This table provides the following information for each stratum:
Stratum Index, which is a sequential stratum identification number
STRATA variables, which list the levels of STRATA variables for the stratum
Number of Observations, which is the number of observations used in the stratum
Number of Clusters, which is the number of clusters in the stratum, if you specify a CLUSTER statement
Sum of Weights, which is the sum of the weights for observations in the stratum
Sampling Rate for the stratum, if you specify the TOTAL= or RATE= option
The ODS name of the "Stratum Information" table is StrataInfo.
If you specify METHOD=FHDI(DISP=MEAN) or METHOD=FHDI(DISP=SSCP), PROC SURVEYIMPUTE displays a "Weighted Moments" table, which shows the weighted means and weighted mean-squared deviations from both two-stage FEFI and FHDI for the variables that are specified in the VAR statement but not in the CLASS statement. The weighted moments for two-stage FEFI are computed by using imputation-adjusted weights from two-stage FEFI, and the weighted moments for FHDI are computed by using imputation-adjusted weights from FHDI. The ODS name of the "Weighted Moments" table is ContMean.
If you specify METHOD=FHDI(DISP=SSCP), PROC SURVEYIMPUTE displays a "Weighted Mean SSCP for FEFI" table, which shows the weighted mean SSCP from two-stage FEFI for the variables that are specified in the VAR statement but not in the CLASS statement. The weighted mean SSCP matrix is computed by using imputation-adjusted weights from two-stage FEFI. The ODS name of the "Weighted Mean SSCP for FEFI" table is ContMSFEFI.
If you specify METHOD=FHDI(DISP=SSCP), PROC SURVEYIMPUTE displays a "Weighted Mean SSCP for FHDI" table, which shows the weighted mean SSCP from FHDI for the variables that are specified in the VAR statement but not in the CLASS statement. The weighted mean SSCP matrix is computed by using imputation-adjusted weights from FHDI. The ODS name of the "Weighted Mean SSCP for FHDI" table is ContMSFHDI.