Imputation of Non-Response in Height and Weight in the Mexican Health and Aging Study.

Abstract

The way missing data in population surveys are treated can influence research results. Therefore, the aim of this paper is to explain the reasons and procedure for imputing anthropometric data such as height and weight self-reported by individuals in the first four waves of the Mexican Health & Aging Study (MHAS). We highlight the effect of the imputation versus the exclusion of the cases with missing data, by comparing the distribution of these values and their associated effects on the Body Mass Index using a regression model. We conclude that the incorporation of imputed data offers more solid results compared with elimination the cases with missing data. Hence the importance of applying these statistical procedures, with appropriate treatment of the data, making the methodology and the imputed data available to the users by the same source of information, as offered in the MHAS.