Showing papers by "Pranab Kumar Sen published in 2004"

Weighted estimating equations for semiparametric transformation models with censored data from a case‐cohort design

Abstract: SUMMARY In a case-cohort design introduced by Prentice (1986), covariates are assembled only for a subcohort randomly selected from the entire cohort, and any additional cases outside the subcohort. Semiparametric transformation models are considered here for failure time data from the case-cohort design. Weighted estimating equations are proposed for esti mation of the regression parameters. The estimation procedure of survival probability at given covariate levels is also provided. Asymptotic properties are derived for the estimators using finite population sampling theory, U-statistics theory and martingale convergence results. The finite-sample properties of the proposed estimators, as well as the efficiency relative to the full cohort estimators, are assessed via simulation studies. A case-cohort dataset from the Atherosclerosis Risk in Communities study is used to illustrate the estimating procedure.

On two results in multiple testing

Abstract: Two known results in multiple testing, one relating to the directional error control of augmented step-down procedure proved by Shaffer (1980) and the other on the monotonicity of the critical values of step-up procedure proved by Dalai and Mallows (1992), are revisited and given alternative proofs in this article.

Quality-Adjusted Survival Estimation with Periodic Observations: A Multistate Survival Analysis Approach

Abstract: Quality-adjusted survival is a composite measure that combines quality-of-life and survival data. Analyzing quality-adjusted survival with data collected at periodic intervals can be difficult because of incomplete information resulting from dropouts or missing visits. Dropouts could be purely random or caused by treatments or the illness itself. In a multistate model, dropout information can be incorporated into analysis by including the “dropout” state as a state of the patient's health. Under a Markovian assumption on patients' health status, we applied a multistate survival analysis approach that extends Chen and Sen's study [Chen, P.-L., Sen, P. K. (2001). Quality adjusted survival estimation with periodic observation. Biometrics 57:868–874] which estimated the mean quality-adjusted survival where the transition probability between health states and patients' expected survival time can be estimated simultaneously. Here we show that the estimator is asymptotically normal with simple variance ...

HRQoL and Concomitant Adjusted Mean Residual Life Analysis

Abstract: For aging properties of life-time distributions in reliability and survival analysis, the DMRL property plays a vital role. Generally, there are multiple auxiliary or explanatory variables, and in HRQoL studies, QAL perspectives are nonignorable. These factors introduce complications in parametric modeling of MRL; for QLAMRL functions it is anticipated, though not yet established, that semiparametrics may suit well. As an alternative approach, matrix-valued counting processes for repeated measurement data models, involving clusters of random sizes, nonexchangeable within-cluster dependence, and QAL adjustments, are appraised.

Robust M-procedures in univariate nonlinear regression models

Abstract: In univariate nonlinear regression models, estimator and test statistics based on (generalized) least squares and maximum likelihood meth- ods are usually nonrobust; M-procedures are better in this respect. Our proposed M-estimators, and M-tests are formulated along the lines of gener- alized least squares procedures and their (asymptotic) properties are studied. Computational algorithms are also considered along with.

Environmental burden of disease: HRQoL and statistical perspectives

Abstract: Environmental toxicity and pollution mingled with substandard sanitation and public health practice can lead to serious health problems. Some of these toxics can be identified and subjected to preventive measures but together with some other major factors they form the environmental burden of disease, more seriously in developing countries. As a result, in health related quality of life risk assessments, especially relating to cancer of various types, as well as chronic and intestinal diseases, we need to incorporate toxicology as well as environmental epidemiology. Statistical perspectives in this challenging task are appraised with special attention to the arsenite contamination of the groundwater problem.

Making inferences about projected completors in longitudinal studies

Abstract: In this article, we present methodology for making inferences about projected completors in the presence of attrition. The approach is motivated by a clinical trial that investigates a treatment for disability among individuals who sustain severe head injuries. Although most studies attempt to make inferences about the entire study population, our application poses important scientific questions targeting individuals who are likely to complete the study or to remain on protocol for a specified time period. We propose using measures of each individual's dropout inclination to identify projected completors and then building a stratified response model based on projected completion status. We present several prediction measures along with procedures for evaluating accuracy with respect to observed dropout. Estimation of model parameters proceeds using maximum likelihood and restricted maximum likelihood methods. We illustrate the utility of our proposed analysis by using the motivating disability da...