This work provides descriptions, explanations and examples of the Bayesian approach to statistics, demonstrating the utility of Bayesian methods for analyzing real-world problems in the health sciences. The work considers the individual components of Bayesian analysis.;College or university bookstores may order five or more copies at a special student price, available on request from Marcel Dekker, Inc.
This work provides descriptions, explanations and examples of the Bayesian approach to statistics, demonstrating the utility of Bayesian methods for analyzing real-world problems in the health sciences. The work considers the individual components of Bayesian analysis.;College or university bookstores may order five or more copies at a special student price, available on request from Marcel Dekker, Inc.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Part 1 General overview: Bayesian methods in health-related research; Bayesian approaches to randomized trials; Bayesian epidemiology. Part 2 Assessing probabilities: elicitation of prior distributions; priors for the design and analysis of clinical trials. Part 3 Decision problems: a Weibull model for survival data - using prediction to decide when to stop a clinical trial; decision models in clinical recommendations development - the stroke prevention policy model; dose-response analysis of toxic chemicals; expected utility as a policy making tool - an environmental health example. Part 4 Design: Bayesian hypothesis testing - interim analysis of a clinical trial evaluating phenytoin for the prophylaxis of early post-traumatic seizures in children; inference and design strategies for a hierarchical logistic regression model. Part 5 Model selection: model selection for generalized linear models via GLIB - application to nutrition and breast cancer. Part 6 Hierarchical models: Bayesian analysis of population pharmacokinetic and instantaneous pharmacodynamic relationships; Bayesian and frequentist analysis of an in vivo experiment in tumor hemodynamics; Bayesian meta-analysis of randomized trials using graphical models for assessing the effect of extreme cold weather on schizophrenic births; fitting and checking a two-level Poisson model - modelling patient mortality rates in heart transplant patients. Part 7 Other topics: analyzing rodent tumorigencitiy experiments using expert knowledge; assessing drug interactions - tamoxifen and cyclophosphamide; Bayesian subset analysis of a clinical trial for the treatment of HIV infections; Bayesian modelling of binary repeated measures data with application to crossover trials; a comparative study of perinatal mortality using a two-component mixture model; change-point analysis of a randomized trial on the effects of calcium supplementation on blood pressure; Bayesian predictive inference for a binary random variable - survey
Part 1 General overview: Bayesian methods in health-related research; Bayesian approaches to randomized trials; Bayesian epidemiology. Part 2 Assessing probabilities: elicitation of prior distributions; priors for the design and analysis of clinical trials. Part 3 Decision problems: a Weibull model for survival data - using prediction to decide when to stop a clinical trial; decision models in clinical recommendations development - the stroke prevention policy model; dose-response analysis of toxic chemicals; expected utility as a policy making tool - an environmental health example. Part 4 Design: Bayesian hypothesis testing - interim analysis of a clinical trial evaluating phenytoin for the prophylaxis of early post-traumatic seizures in children; inference and design strategies for a hierarchical logistic regression model. Part 5 Model selection: model selection for generalized linear models via GLIB - application to nutrition and breast cancer. Part 6 Hierarchical models: Bayesian analysis of population pharmacokinetic and instantaneous pharmacodynamic relationships; Bayesian and frequentist analysis of an in vivo experiment in tumor hemodynamics; Bayesian meta-analysis of randomized trials using graphical models for assessing the effect of extreme cold weather on schizophrenic births; fitting and checking a two-level Poisson model - modelling patient mortality rates in heart transplant patients. Part 7 Other topics: analyzing rodent tumorigencitiy experiments using expert knowledge; assessing drug interactions - tamoxifen and cyclophosphamide; Bayesian subset analysis of a clinical trial for the treatment of HIV infections; Bayesian modelling of binary repeated measures data with application to crossover trials; a comparative study of perinatal mortality using a two-component mixture model; change-point analysis of a randomized trial on the effects of calcium supplementation on blood pressure; Bayesian predictive inference for a binary random variable - survey
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