What Is The Pooling Rule In Multiple Imputation?

Описание: Multiple imputation is a powerful technique for handling missing data, but understanding how to combine the results from multiple imputed datasets can be a bit tricky. This video from The Friendly Statistician breaks down the crucial 'pooling rule' in multiple imputation, explaining its purpose and application.

In this insightful video, you'll learn:
► What multiple imputation is and why it's used to address missing data.
► The fundamental concept behind the pooling rule and why it's essential for valid inference.
► How results from individually imputed datasets are combined to provide overall estimates.
► Practical considerations and common pitfalls to avoid when applying the pooling rule.
► The statistical principles that underpin the effective use of multiple imputation.


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