Should you impute dependent variable?

Should you impute dependent variable?

Always include the dependent variable in your imputation model. Whether you should use imputed values of the dependent variable in your analysis model is unclear, but always impute them.

How do you impute missing data in SPSS?

Analyze > Multiple Imputation > Impute Missing Data Values…

1. Select at least two variables in the imputation model.
2. Specify the number of imputations to compute.
3. Specify a dataset or IBM® SPSS® Statistics-format data file to which imputed data should be written.

How do you impute missing data?

The following are common methods:

1. Mean imputation. Simply calculate the mean of the observed values for that variable for all individuals who are non-missing.
2. Substitution.
3. Hot deck imputation.
4. Cold deck imputation.
5. Regression imputation.
6. Stochastic regression imputation.
7. Interpolation and extrapolation.

How does mean imputation preserve the relationships among variables?

Problem #1: Mean imputation does not preserve the relationships among variables. True, imputing the mean preserves the mean of the observed data. So if the data are missing completely at random, the estimate of the mean remains unbiased. That’s a good thing.

Are there any problems with mean imputation for missing data?

First, a definition: mean imputation is the replacement of a missing observation with the mean of the non-missing observations for that variable. Problem #1: Mean imputation does not preserve the relationships among variables. True, imputing the mean preserves the mean of the observed data.

How to perform multiple imputation using predictive mean?

The mice function will detect which variables is the data set have missing information. The default method of imputation in the MICE package is PMM and the default number of imputations is 5. If you would like to change the default number you can supply a second argument which we demonstrate below.

Can a statistic be imputed without standard error?

A second reason is applies to any type of single imputation. Any statistic that uses the imputed data will have a standard error that’s too low. In other words, yes, you get the same mean from mean-imputed data that you would have gotten without the imputations. And yes, there are circumstances where that mean is unbiased.