Estimating Nonlinear Models With Multiply Imputed Data

Written By: Catherine Phillips Montalto and Yoonkyung Yuh

Repeated-imputation inference (RII) techniques for estimating nonlinear models with multiply imputeddata are described. RII techniques are used to estimate a logit model using the 1995 Survey ofConsumer Finances. RII techniques use all information available in multiply imputed data andincorporate estimates of imputation error. The advantage of RII techniques for analysis of multiplyimputed data is that RII techniques produce more efficient estimates and provide a basis for morevalid inference. Researchers who do not use RII techniques when estimating nonlinear models onmultiply imputed data may incorrectly conclude that some independent variables have statisticallysignificant effects.Key Words: Logit, Probit, Repeated-imputation inference (RII), Survey of Consumer Finances, Tobit

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