I am doing multiple imputation using chained equations in Stata to deal with item-missing data. One of the variables on which I did imputation was income. However after I did imputation, the imputed values of income contain negative values though the mean and standard deviation of income after imputation are almost similar to those before imputation. I used linear regression to impute income (though the distribution of income in the study population is not normal). While using other options of imputing income such as predictive mean matching, truncated regression, Poisson regression and negative binomial regression, the imputation model fails to converge. How should I deal with such negative imputed values? May I just ignore this and continue with further analysis of my multiple-imputed data?
Solved – Negative imputed values
multiple-imputation
Best Answer
I think you just continue with your analysis. For one thing, negative income is not impossible. If you lose money (e.g. on investments) and don't make any, that would be negative income.