A Multivariate Technique for Multiply Imputing Missing Values Using a Sequence of Regression Models

Archived Abstract of Former PSC Researcher

Raghunathan, Trivellore, James M. Lepkowski, John Van Hoewyk, and Peter W. Solenberger. 2001. "A Multivariate Technique for Multiply Imputing Missing Values Using a Sequence of Regression Models." Survey Methodology, 27(2): 85-96.

This article describes and evaluates a procedure for imputing missing values for a relatively complex data structure when the data are missing at random. The imputations are obtained by fitting a sequence of regression models and drawing values from the corresponding predictive distributions. The types of regression models used are linear, logistic, Poisson, generalized logit or a mixture of these depending on the type of variable being imputed. Two additional common features in the imputation process are incorporated: restriction to a relevant subpopulation for some variables and logical bounds or constraints for the imputed values. The restrictions involve subsetting the sample individuals that satisfy certain criteria while fitting the regression models. The bounds involve drawing values from a truncated predictive distribution. The development of this method was partly motivated by the analysis of two data sets which are used as illustrations. The sequential regression procedure is applied to perform multiple imputation analysis for the two applied problems. The sampling properties of inferences from multiply imputed data sets created using the sequential regression method areevaluated through simulated data sets.

Keywords:
Item nonresponse; Missing at random; Multiple imputation; Nonignorable missing mechanism; Regression; Sampling properties and simulations.

Browse | Search | Next

PSC In The News

RSS Feed icon

Shaefer comments on the Cares Act impact in negating hardship during COVID-19 pandemic

Heller comments on lasting safety benefit of youth employment programs

More News

Highlights

Dean Yang's Combatting COVID-19 in Mozambique study releases Round 1 summary report

Help Establish Standard Data Collection Protocols for COVID-19 Research

More Highlights


Connect with PSC follow PSC on Twitter Like PSC on Facebook