Browsing by Title
Now showing items 436-455 of 4624
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Baumol’s cost disease and physician shortages: an analysis of rising healthcare expenditures from the supply side.
(2019-04-09)Over the last two decades, the U.S. experienced a stagnant supply of physicians, as well as rapidly rising healthcare expenditures. Based on a novel version of Baumol’s unbalanced growth model, this paper addresses the ... -
Bayesian adaptive designs for non-inferiority and dose selection trials.
(2006-07-31)The process of conducting a pharmaceutical clinical trial often produces information in a way that can be used as the trial progresses. Bayesian methods offer a highly flexible means of using such information yielding ... -
Bayesian adjustment for misclassification bias and prior elicitation for dependent parameters.
(2019-11-25)This research is motivated by problems in biopharmaceutical research. Prior elicitation is defined as formulating an expert's beliefs about one or more uncertain quantities into a joint probability distribution, and is ... -
Bayesian and likelihood-based interval estimation for the risk ratio using double sampling with misclassified binomial data.
(2011-01-05)We consider the problem of point and interval estimation for the risk ratio using double sampling with two-sample misclassified binary data. For such data, it is well-known that the actual data model is unidentifiable. To ... -
Bayesian and maximum likelihood methods for some two-segment generalized linear models.
(2008-10-14)The change-point (CP) problem, wherein parameters of a model change abruptly at an unknown covariate value, is common in many fields, such as process control, epidemiology, and ecology. CP problems using two-segment ... -
Bayesian and pseudo-likelihood interval estimation for comparing two Poisson rate parameters using under-reported data.
(2009-04-01)We present interval estimation methods for comparing Poisson rate parameters from two independent populations with under-reported data for the rate difference and the rate ratio. In addition, we apply the Bayesian paradigm ... -
Bayesian approach to inference and variable selection for misclassified and under-reported response models.
(2009-07-01)Response partial missingness is a problem in studies conducted in a variety of disciplines. We investigate the impact ignoring response partial missingness has on determining a subset of significant covariates in non-linear ... -
Bayesian approach to partially validated binary regression with response and exposure misclassification.
(2018-06-09)Misclassification of epidemiological and observational data is a problem that commonly arises and can have adverse ramifications on the validity of results if not properly handled. Considerable research has been conducted ... -
Bayesian approaches for design of psychometric studies with underreporting and misclassification.
(, 2013-05-15)Measurement error problems in binary regression are of considerable interest among researchers, especially in epidemiological studies. Misclassification can be considered a special case of measurement error specifically ... -
Bayesian approaches for survival data in pharmaceutical research.
(2020-09-15)In this research, we consider Bayesian methodologies to address problems in biopharmaceutical research, most of which are motivated by real-world problems in network meta-analysis, prior elicitation, and adaptive designs. ... -
Bayesian approaches to correcting bias in epidemiological data.
(2011-05-12)Bias in parameter estimation of count data is a common concern. The concern is even greater when all counts are not recorded. Failing to adjust for underreported data can lead to incorrect parameter estimates. A Bayesian ... -
Bayesian approaches to parameter estimation and variable selection for misclassified binary data.
(2009-08-26)Binary misclassification is a common occurrence in statistical studies that, when ignored, induces bias in parameter estimates. The development of statistical methods to adjust for misclassification is necessary to allow ... -
Bayesian approaches to problems in drug safety and adaptive clinical trial designs.
(2008-06-10)The efficacy, safety, and cost of pharmaceutical products are critical issues in society today. Motivated both financially and ethically by these concerns, the pharmaceutical industry has continually worked to develop ... -
Bayesian evaluation and adaptive trial design for surrogate time-to-event endpoints in clinical trials.
(2011-05-12)Surrogate endpoints are desirable in clinical trials when primary endpoints are costly to obtain, difficult to measure, or require lengthy follow-up to observe. Despite legitimate concerns, evaluation of potentially ... -
Bayesian evaluation of surrogate endpoints.
(2006-07-29)To save time and reduce the size and cost of clinical trials, surrogate endpoints are frequently measured instead of true endpoints. The proportion of the treatment effect explained by surrogate endpoints (PTE) is a widely ... -
Bayesian inference for bivariate Poisson data with zero-inflation.
(2017-07-27)Multivariate count data with zero-inflation is common throughout pure and applied science. Such count data often includes excess zeros. Zero-inflated Poisson regression models have been used in several applications to model ... -
Bayesian inference for correlated binary data with an application to diabetes complication progression.
(2006-10-26)Correlated binary measurements can occur in a variety of practical contexts and afford interesting statistical modeling challenges. In order to model the separate probabilities for each measurement we must somehow account ... -
Bayesian inference for vaccine efficacy and prediction of survival probability in prime-boost vaccination regimes.
(2019-11-08)This dissertation consists of two major topics on applying Bayesian statistical methods in vaccine development. Chapter two concerns the estimation of vaccine efficacy from validation samples with selection bias. Since ... -
Bayesian methods for hurdle models.
(2015-02-09)Hurdle models are often presented as an alternative to zero-inflated models for count data with excess zeros. They consist of two parts: a binary model indicating a positive response (the “hurdle”) and a zero-truncated ... -
Bayesian methods in non-clinical pharmaceutical statistics.
(2017-03-17)This dissertation is composed of three research papers investigating the application of Bayesian methods to pharmaceutical non-clinical statistics. In the first paper, we present an application of Bayesian assurance and ...