Subscription or Fee Access
How To Deal With Missing Covariates In Logistic Regression? A Bayesian Approach
Logistic regression is an analytical tool widely used in medical and epidemiological researches. In many studies, we face data sets in which some parts of the data are not reported or in other words are missing. The simplest way of dealing with such data is just to ignore the subjects with missing observations, and analyze with the complete cases which is obviously inefficient. We consider methods for analyzing data with logistic regression models when some covariates (Z) are completely observed but other covariates (X) are missing for some subjects. When data on X are missing at random(MAR), we present a likelihood approach for the observed data that allows an analysis similar to the case as if the data were complete. Following this approach, the parameters estimation is carried out using both Maximum likelihood and Bayesian methods through the Markov Chain Monte Carlo numerical computation scheme, and the results are compared . The illustrative example considered in this article involves Lung Auscultation of a Cross Sectional study data set taken from a Health Survey in Tehran.
Missing covariates, Missing at random, Markov Chain Monte Carlo, Logistic Regression, Lung Auscultation, Likelihood
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.