Title of Document: A MIXTURE RASCH MODEL WITH A COVARIATE: A SIMULATION STUDY VIA BAYESIAN MARKOV CHAIN MONTE CARLO ESTIMATION Yunyun Dai, Doctor of Philosophy, 2009 Directed By: Professor, Robert J. Mislevy, Department of Measurement, Statistics and Evaluation Mixtures of item response theory models have been proposed as a technique to explore response patterns in test data related to cognitiv...

In this paper, we study Bayesian asymptotic properties of the proportional hazards model where link function is modeled by generalized additive model. As standard is, a useful tool in finding nonlinearity covariate effects to survival times. We develop data-dependent sieve prior for and use bootstrap baseline hazard function. prove that posterior contraction rate minimax optimal up logn term wh...

The definition of vectors of dependent random probability measures is a topic of interest in applications to Bayesian statistics. They, indeed, represent dependent nonparametric prior distributions that are useful for modelling observables for which specific covariate values are known. In this paper we propose a vector of two-parameter Poisson-Dirichlet processes. It is well-known that each com...

BACKGROUND The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide impo...

Background and Purpose—Diabetes increases stroke risk, but whether diabetes status immediately before stroke improves prediction and whether duration is important are less clear. We hypothesized that diabetes duration independently predicts ischemic stroke. Methods—Among 3298 stroke-free participants in the Northern Manhattan Study, baseline diabetes and age at diagnosis were determined. Incide...

The appropriateness of normalizing data, as one method to reduce the effects of a covariate on a dependent variable, should be evaluated. Using ratio, 0.67-nonlinear, and fitted normalizations, the aim of this study was to investigate the relationship between ground reaction force variables and body mass (BM). Ground reaction forces were recorded for 40 female subjects running at 3.7 +/- 0.18 m...

The odds ratio is a measure commonly used for expressing the association between an exposure and a binary outcome. A feature of the odds ratio is that its value depends on the choice of the distribution over which the probabilities in the odds ratio are evaluated. In particular, this means that an odds ratio conditional on a covariate may have a different value from an odds ratio marginal on th...

Marginal structural models (MSMs) are becoming increasingly popular as a tool to make causal inference from longitudinal data. Unlike standard regression models, MSMs can adjust for time-dependent observed confounders while avoiding the bias due to the adjustment for covariates affected by the treatment. Despite their theoretical appeal, a main practical difficulty of MSMs is the required estim...

Murray and Tsiatis (1996) described a weighted survival estimate that incorporates prognostic time-dependent covariate information to increase the efficiency of estimation. We propose a test statistic based on the statistic of Pepe and Fleming (1989, 1991) that incorporates these weighted survival estimates. As in Pepe and Fleming, the test is an integrated weighted difference of two estimated ...

The case series model for estimating the association between an age-dependent exposure and an outcome event requires information only on cases and implicitly adjusts for all age-independent multiplicative confounders, while allowing for an age-dependent baseline incidence. In this paper the model is presented in greater generality than hitherto, including more general discussion of its derivati...