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Is it possible for me to perform multiple imputation for 3-level dataset using STAT-JR?gorilla tag For your information, my data have missing values at level-1 only, no missing values was found at level-2 and level-3. Thanks.

You can find information about support for missing data in Stat-JR on the following page:

Imputation for Multilevel Models with Missing Data Using Stat-JR

STAT-JR is a software package that allows you to perform various statistical analyses, including multilevel models and multiple imputation. STAT-JR has two approaches for handling missing data in multilevel models: 2LevelImpute and NLevelImpute

2LevelImpute is a procedure that uses multiple imputation based on multilevel models to handle missing data in two-level data, such as repeated measures on individuals who are clustered within larger units. 2LevelImpute can also be extended to handle three-level data by using dummy indicators for the third level units

NLevelImpute is a procedure that uses multiple imputation based on multilevel models to handle missing data in N-level data, where N can be any positive integer. NLevelImpute can handle three-level data without using dummy indicators, and it can also handle missing data at any level

Therefore, it is possible for you to perform multiple imputation for 3-level dataset using STAT-JR, either by using 2LevelImpute with dummy indicators, or by using NLevelImpute without dummy indicators. You can find more details and examples on how to use these procedures in the following documents:

• Imputation for Multilevel Models with Missing Data Using Stat-JR

• Evaluation of approaches for multiple imputation of three-level data

• Imputation for Multilevel Models with Missing Data Using Stat-JR

I hope this helps you to perform multiple imputation for 3-level dataset using STAT-JR.