This paper considers the problem of parameter estimation in a model for a continuous response variable y when an important ordinal explanatory variable x is missing for a large proportion of the sample. Non-missingness of x, or sample selection, is correlated with the response variable and/or with the unobserved values the ordinal explanatory variable takes when missing. We suggest solving the endogenous selection, or 'not missing at random' (NMAR), problem by modelling the informative selection mechanism, the ordinal explanatory variable, and the response variable together. The use of the method is illustrated by re-examining the problem of the ethnic gap in school achievement at age 16 in England using linked data from the National Pupil ...
Consider a data set with several polytomous variables that measure the same underlying trait. Assume...
Much research has been devoted to modelling strategies for longitudinal data with missingness, recen...
Missing values in covariates of regression models are a pervasive problem in empirical research. Pop...
This paper considers the problem of parameter estimation in a model for a continuous response variab...
Sample selection arises when the outcome of interest is partially observed in a study. Although soph...
This dissertation is composed of three papers which address the problem of variable selection for mo...
Missing data are exceedingly common across a variety of disciplines, such as educational, social, an...
We consider the variable selection problem for a class of statistical models with missing data, incl...
In this dissertation, we propose methodology to account for missing data as well as a strategy to ac...
In this article, we study the estimation of mean response and regression coefficient in semiparametr...
Missing values are a major problem in all econometric applications based on survey data. A standard ...
Includes bibliographical references (p. 175-178).Response partial missingness is a problem in studie...
Missing values in covariates of regression models are a pervasive problem in empirical research. Pop...
Missing data usually present special problems for statistical analyses, especially when the data are...
A joint model for multivariate mixed ordinal and continuous outcomes with potentially non-random mis...
Consider a data set with several polytomous variables that measure the same underlying trait. Assume...
Much research has been devoted to modelling strategies for longitudinal data with missingness, recen...
Missing values in covariates of regression models are a pervasive problem in empirical research. Pop...
This paper considers the problem of parameter estimation in a model for a continuous response variab...
Sample selection arises when the outcome of interest is partially observed in a study. Although soph...
This dissertation is composed of three papers which address the problem of variable selection for mo...
Missing data are exceedingly common across a variety of disciplines, such as educational, social, an...
We consider the variable selection problem for a class of statistical models with missing data, incl...
In this dissertation, we propose methodology to account for missing data as well as a strategy to ac...
In this article, we study the estimation of mean response and regression coefficient in semiparametr...
Missing values are a major problem in all econometric applications based on survey data. A standard ...
Includes bibliographical references (p. 175-178).Response partial missingness is a problem in studie...
Missing values in covariates of regression models are a pervasive problem in empirical research. Pop...
Missing data usually present special problems for statistical analyses, especially when the data are...
A joint model for multivariate mixed ordinal and continuous outcomes with potentially non-random mis...
Consider a data set with several polytomous variables that measure the same underlying trait. Assume...
Much research has been devoted to modelling strategies for longitudinal data with missingness, recen...
Missing values in covariates of regression models are a pervasive problem in empirical research. Pop...