Public Health

Bayesian Item Response Modeling: Theory and Applications by Jean-Paul Fox

By Jean-Paul Fox

This e-book provides an intensive remedy and unified insurance of Bayesian merchandise reaction modeling with functions in a number of disciplines, together with schooling, drugs, psychology, and sociology. Breakthroughs in computing expertise have made the Bayesian method quite precious for plenty of reaction modeling difficulties. unfastened from computational constraints, sensible and state of the art latent variable reaction types are thought of for advanced overview and survey information to unravel real-world difficulties. The Bayesian framework defined offers a unified method for modeling and inference, facing (nondata) previous details and data throughout a number of info resources. The publication discusses tools for interpreting merchandise reaction facts and the advanced relationships normally linked to human reaction habit and lines • Self-contained creation to Bayesian merchandise reaction modeling and a assurance of extending general types to deal with complicated evaluate facts • an intensive evaluate of Bayesian estimation and checking out equipment for merchandise reaction versions, the place MCMC equipment are emphasised • various examples that hide quite a lot of software components, together with schooling, medication, psychology, and sociology • Datasets and software program (S+, R, and WinBUGS code) of the versions and strategies awarded within the e-book can be found on Bayesian merchandise reaction Modeling is a superb booklet for study execs, together with utilized statisticians, psychometricians, and social scientists who research merchandise reaction facts from a Bayesian point of view. it's a advisor to the turning out to be region of Bayesian reaction modeling for researchers and graduate scholars, and also will serve them as a superb reference. Jean-Paul Fox is affiliate Professor of size and information research, collage of Twente, The Netherlands. His major learn actions are in different components of Bayesian reaction modeling. Dr. Fox has released quite a few articles within the components of Bayesian merchandise reaction research, statistical equipment for studying multivariate specific reaction facts, and nonlinear combined results models.

Show description

Read Online or Download Bayesian Item Response Modeling: Theory and Applications PDF

Best public health books

Environmental and Health Risk Assessment and Management: Principles and Practices

"This ebook is ready the criminal, reasonable, and functional evaluation and administration of dicy actions bobbing up from regimen, catastrophic environmental and occupational exposures to damaging brokers. It starts off the place emission and publicity research ends via offering estimates or predictions of deleterious exposures.

Dompaminergic Neuron Transplantation in the Weaver Mouse Model of Parkinson's Disease (Neuroscience Intelligence Unit)

This ebook is the end result of fifteen years of study at the transplantation of dopaminergic neurons within the striatum of the weaver mouse (wv/wv), a neurological mutant characterised by way of genetically-determined degeneration of midbrain dopamine neurons. This mutant constitutes the single on hand laboratory version with a prolonged illness that mimics Parkinson's ailment.

The New Profile of Drug-Resistant Tuberculosis in Russia: A Global and Local Perspective (Summary of a Joint Workshop)

An predicted 2 billion humans, one 3rd of the worldwide inhabitants, are contaminated with Mycobacterium tuberculosis, the bacterium that explanations tuberculosis. unfold during the air, this infectious affliction killed 1. 7 million in 2009, and is the prime killer of individuals with HIV. Tuberculosis (TB) can also be a affliction of poverty--the overwhelming majority of tuberculosis deaths take place within the constructing global.

Creating a Healthy School Using the Healthy School Report Card

Winning scholars are usually not merely an expert but in addition emotionally and bodily fit, encouraged, civically engaged, ready for paintings and monetary self-sufficiency, and prepared for the realm past their very own borders. to assist scholars meet this general, a faculty needs to use a coordinated, evidence-based process that helps studying, educating and scholar progress briefly, the varsity needs to create a fit university neighborhood.

Additional resources for Bayesian Item Response Modeling: Theory and Applications

Sample text

A proper noninformative prior is specified with µ0 = (1, 0)t , ν = 2, a scale matrix Σ0 that is a minimally informative prior guess of Σξ , and K0 a small number. The hierarchical prior accounts for within-item dependencies and for uncertainty of the prior’s parameters. The mean and variance of the normal prior for the item parameters are modeled at a higher prior level and need to be estimated from the data. As a result, the hierarchical prior gives rise to shrinkage estimates of the item parameters, where the amount of shrinkage is inferred from the data.

The posterior standard deviation and quantiles provide information about the spread of the posterior. 5% quantiles of each marginal posterior are reported. The reported posterior means (expected a posteriori) are usually used as point estimates of the parameters. It follows that item five discriminates poorly and item one highly discriminates examinees of different ability. 90, which is slightly smaller than the prior mean. The quantiles show that the posterior densities are nonsymmetric and positively skewed (right tails are longer), which follows from the positivity restriction on the discrimination parameter.

5 Computation and Software For the well-known item response models, various commercial and noncommercial programs are available. It is to the credit of the pioneering work of the researchers involved that today so many popular IRT programs are available. To give a short overview, BILOG-MG (Zimowski, Muraki, Mislevy and Bock, 1996) allows the estimation of IRT parameters for multiple groups and 3 In WinBUGS, the variance parameter of a normal distribution is parameterized in terms of the inverse variance (precision) such that, in the second case, the precision parameter is modeled by a gamma prior.

Download PDF sample

Rated 4.01 of 5 – based on 12 votes