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The MIANALYZE Procedure

Overview
Getting Started
Syntax
PROC MIANALYZE Statement BY Statement CLASS Statement MODELEFFECTS Statement STDERR Statement TEST Statement
Details
Input Data Sets Combining Inferences from Imputed Data Sets Multiple Imputation Efficiency Multivariate Inferences Testing Linear Hypotheses about the Parameters Examples of the Complete-Data Inferences ODS Table Names
Examples
Reading Means and Standard Errors from a DATA= Data Set Reading Means and Covariance Matrices from a DATA= COV Data Set Reading Regression Results from a DATA= EST Data Set Reading Mixed Model Results from PARMS= and COVB= Data Sets Reading Generalized Linear Model Results Reading GLM Results from PARMS= and XPXI= Data Sets Reading Logistic Model Results from a PARMS= Data Set Reading Mixed Model Results with Classification Covariates Reading Nominal Logistic Model Results Using a TEST statement Combining Correlation Coefficients Sensitivity Analysis with Control-Based Pattern Imputation Sensitivity Analysis with the Tipping-Point Approach
References

Details: MIANALYZE Procedure

Subsections:

Input Data Sets
Combining Inferences from Imputed Data Sets
Multiple Imputation Efficiency
Multivariate Inferences
Testing Linear Hypotheses about the Parameters
Examples of the Complete-Data Inferences
ODS Table Names

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