CUTTING-EDGE RESEARCH BY FACULTY OF IIM BANGALORE

Faculty members at IIM Bangalore generate knowledge through cutting-edge research in all functional areas of management that would benefit public and private sector companies, and government and society in general. The knowledge generated by IIMB faculty appears in leading academic journals with high citation index and impact factor. Many textbooks and working papers are written on a regular basis. Research carried out by IIMB is used to augment new courses and executive education programmes.

Journal of the Royal Statistical Society: Series A

Paper Title: Bayesian estimation of long-term health consequences for obese and normal-weight elderly people.

Abstract

Obesity is a rapidly growing public health problem even among the elderly. Understanding the disabling consequences of obesity in the elderly will help us to design better effective intervention management guidelines for the elderly obese. To examine the long-term health consequences of the obese elderly, we present a joint model consisting of two bivariate ordered responses observed at successive time points. The bivariate ordered response model corresponds to the subject’s self-reporting health status outcomes including self-rated health and functional status. Although the joint model that we propose is generally suited for use in health and disease research, where the ordered value responses are observed at successive time points, we further extend it by addressing some of the challenges by incorporating the semiparametric features in the ordinal logistic model, by modelling the underlying latent states of health that are associated with self-rated health, by jointly modelling the bivariate ordinal out-comes to mitigate the variability of the single response and by accounting for the non-ignorable missing data due to different reasons through a multinomial logit model. The motivating data were obtained from the Second Longitudinal Study of Aging, which are longitudinal survey data from 1994–2000 providing various useful information on the health status of elderly people. Parameter estimation of our joint model was performed in a Bayesian framework via Markov chain Monte Carlo methods. Analytical results demonstrate the difference in longitudinal pat- terns of the health outcomes between the two weight groups, validating our hypothesis that different management strategies for the obese elderly should be employed.

Journal of the Royal Statistical Society blog.png

Journal of the Royal Statistical Society

Written by

Pulak Ghosh, Decision Sciences and Information Systems, Indian Institute of Management Bangalore

Read More @ Journal of the Royal Statistical Society: Series A

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s