Efficiency Comparisons in Multivariate Multiple Regression with Missing Outcomes

Efficiency Comparisons in Multivariate Multiple Regression with Missing Outcomes

We consider a follow-up study in which an outcome variable is to be measured at fixed time points and covariate values are measured prior to start of follow-up. We assume that the conditional mean of the outcome given the covariates is a linear function of the covariates and is indexed by occasion-specific regression parameters. In this paper we study the asymptotic properties of several freque...

Missing Data in Regression Models for Non-commensurate Multiple Outcomes.

Biomedical research often involves the measurement of multiple outcomes in different scales (continuous, binary and ordinal). A common approach for the analysis of such data is to ignore the potential correlation among the outcomes and model each outcome separately. This can lead not only to loss of efficiency but also to biased estimates in the presence of missing data. We address the problem ...

Regression Analysis in Longitudinal Studies with Non-ignorable Missing Outcomes

Efficiency transfer for regression models with responses missing at random

We consider independent observations on a random pair (X,Y ), where the response Y is allowed to be missing at random but the covariate vector X is always observed. We demonstrate that characteristics of the conditional distribution of Y given X can be estimated efficiently using complete case analysis, i.e., one can simply omit incomplete cases and work with an appropriate efficient estimator ...

Outcomes of High-Risk Pregnancies in Northern Iran: Multivariate Logistic Regression Model

Abstract Background and purpose: High-risk pregnancy is referred to a situation in which mother, fetus or neonate are in higher risk of morbidity or mortality. Because of adverse outcomes of high-risk pregnancies, this study aims to determine these outcomes in the North of Iran.  Materials and Methods: We recruited 803 urban and rural pregnant women in this crosssectional ...