Biomedical subjects

Malay Naskar

Publications and source records attributed to Malay Naskar.

3 recordsLinked to original sources

PubMed2007

Effectiveness of tibolone on the reduction of menopausal problems--a Bayesian semi-parametric interpretation.

Two major physiological problems women experience at the time of menopause are hot flush and vaginal dryness. Exploratory investigations reveal that these two binary outcomes are very much dependent as both of them have predominant oestrogenic effects. A primary interest is to investigate how the bivariate association and the marginal univariate risks are affected by repeated measurements on each woman over several months. To achieve this we propose a very general class of bivariate binary models. Parametric inference is drawn on the basis of full non-parametric Bayesian approach under Dirichlet process mixture. Study addresses some more interesting phenomena on the effectiveness of tibolone treatment in reducing menopausal problems. A simulation study further strengthens the proposed methodology.

Adult↗

PubMed2006

Semiparametric analysis of two-level bivariate binary data.

In medical studies, paired binary responses are often observed for each study subject over timepoints or clusters. A primary interest is to investigate how the bivariate association and marginal univariate risks are affected by repeated measurements on each subject. To achieve this we propose a very general class of semiparametric bivariate binary models. The subject-specific effects involved in the bivariate log odds ratio and the univariate logit components are assumed to follow a nonparametric Dirichlet process (DP). We propose a hybrid method to draw model-based inferences. In the framework of the proposed hybrid method, estimation of parameters is done by implementing the Monte Carlo expectation-maximization algorithm. The proposed methodology is illustrated through a study on the effectiveness of tibolone for reducing menopausal problems experienced by Indian women. A simulation study is also conducted to evaluate the efficiency of the new methodology.

Algorithms↗

PubMed2005

A semiparametric mixture model for analyzing clustered competing risks data.

A very general class of multivariate life distributions is considered for analyzing failure time clustered data that are subject to censoring and multiple modes of failure. Conditional on cluster-specific quantities, the joint distribution of the failure time and event indicator can be expressed as a mixture of the distribution of time to failure due to a certain type (or specific cause), and the failure type distribution. We assume here the marginal probabilities of various failure types are logistic functions of some covariates. The cluster-specific quantities are subject to some unknown distribution that causes frailty. The unknown frailty distribution is modeled nonparametrically using a Dirichlet process. In such a semiparametric setup, a hybrid method of estimation is proposed based on the i.i.d. Weighted Chinese Restaurant algorithm that helps us generate observations from the predictive distribution of the frailty. The Monte Carlo ECM algorithm plays a vital role for obtaining the estimates of the parameters that assess the extent of the effects of the causal factors for failures of a certain type. A simulation study is conducted to study the consistency of our methodology. The proposed methodology is used to analyze a real data set on HIV infection of a cohort of female prostitutes in Senegal.

AIDS Vaccines↗