You are given a dataset with several missing values that are missing at random. You decided to use multiple imputation. What steps will you follow in applying this method?
- Create several imputed datasets, analyze separately, then average results
- Create several imputed datasets, analyze them together, then interpret results
- Impute only once, then analyze
- Impute several times using different methods, then analyze
The correct approach for multiple imputation is to create several imputed datasets, analyze them separately, and then combine the results. This accounts for the uncertainty around the missing values and results in valid statistical inferences.
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