Analytic Resources

Missing Data

Mia: Missing Data Assumptions (MCAR, MAR, MNAR)- 11:00

Mia: How to Handle Missing Data: Complete cases & Imputation (8:59)

Mia: Little's test for Missing Completely At Random (MCAR)- 11:44

Mia: Visualizing Missing Values in R- 6:21

Quant Psych: Missing Data Analysis: Multiple Imputation and Maximum Likelihood Methods (22:47)

The prevention and handling of the missing dataEven in a well-designed and controlled study, missing data occurs in almost all research. Missing data can reduce the statistical power of a study and can produce biased estimates, leading to invalid conclusions. This manuscript reviews the problems and ...

Kang (2013): The prevention and handling of the missing data

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