Detecting Covariates with Non-Random Missing Values in a Survey of Primary Education in Madagascar
J. K. Lindsey, Patrick J. Lindsey
Abstract
J. K. Lindsey, Patrick J. Lindsey
Abstract
Summary A major survey of the determinants of access to primary education in Madagascar was carried out in 1994. The probability of enrolment, probability of admission, delay before beginning school, probability of repeating a year and probability of dropping out were studied. The results of the survey are briefly described. In the analysis, one major problem was non-random missing values in the covariates. Some simple methods were developed for detecting whether a response variable depends on the missingness of a given covariate and whether eliminating the missing values would distort the resulting model. A way of incorporating covariates with randomly missing values was used such that the individuals having the missing values did not need to be eliminated. These methods are described and examples are given on how they were applied for one of the key covariates that had a large number of non-random missing values and for one for which the values appear to be randomly missing.
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Summary A major survey of the determinants of access to primary education in Madagascar was carried out in 1994. The probability of enrolment, probability of admission, delay before beginning school, probability of repeating a year and probability of dropping out were studied. The results of the survey are briefly described. In the analysis, one major problem was non-random missing values in the covariates. Some simple methods were developed for detecting whether a response variable depends on the missingness of a given covariate and whether eliminating the missing values would distort the resulting model. A way of incorporating covariates with randomly missing values was used such that the individuals having the missing values did not need to be eliminated. These methods are described and examples are given on how they were applied for one of the key covariates that had a large number of non-random missing values and for one for which the values appear to be randomly missing.
Key concepts: Covariate, Missing data, Statistics, Mathematics, Econometrics