How does the choice of model in a model-based method impact the imputation process?
- The choice of model can cause overfitting
- The choice of model can influence the accuracy of the imputations
- The choice of model can introduce unnecessary complexity
- The choice of model has no impact
The choice of model in a model-based method can significantly influence the accuracy of the imputations. If the chosen model closely matches the actual data generation process, then the imputations will be accurate. However, if the model is a poor fit, the imputed values may be far from the true values, leading to biased results.
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