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Handbook of Item Response Theory Modeling

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Assumption testing
automatic-update
B01=Dennis A. Revicki
B01=Steven P. Reise
Bayesian inference
Bifactor
Bifactor item response theory
Bifactor model
Category functioning
Category1=Non-Fiction
Category=JMA
Category=JMBT
Category=JNKD
Category=JNT
Category=MBNS
Category=MMJT
Change
Computerized adaptive tests
Conceptual framework
Confirmatory factor analysis
Content validity
Contingency table
COP=United Kingdom
Davidian curves
DCS Model
Delivery_Delivery within 10-20 working days
Depression Short Form
DETECT
differential item functioning
EAP Score
EM
EM algorithm
eq_bestseller
eq_isMigrated=0
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Estimation
Explanatory item response models
Exploratory data analyses
Factor analysis
factor analysis methods
Fit
Generalized linear mixed models
Goodness-of-fit statistics
GPCM.
Graded-response model
Growth
Hawaiian High Schools
Health outcome assessments
Health Outcomes Assessment
Inhibition
IRT
IRT Application
IRT assumptions
IRT Model
Item Bank
Item banks
Item bias
Item characteristic curve
Item factor analysis
Item information
Item information curve
Item Parameters
Item response theory
Item Response Theory Modeling
Language_English
Latent Traits
Latent variable modeling
Latent variables
Likelihood ratio test
Likelihood-based indices
Limited information statistics
Local item dependence
Local item dependency
Log-logistic
M2 index
Marginal model
Marginal reliability
Markov chain Monte Carlo
Measurement invariance
MIRT
MIRT Model
Missing data
Model comparisons
Model Data Fit
model fit evaluation
Model selection
Mokken models
Mplus
Multidimensional
Multidimensional IRT
multidimensional IRT for health research
Multidimensional IRT Model
Multidimensional item response models
Multidimensional item response theory
Multidimensionality
Multiple imputation
Nominal response model
Non-normal latent distribution
noncognitive assessment
Nonparametric IRT Model
Nonparametric IRT models
Nonparametric item response theory
PA=Available
Patient Reported Outcome Measurement Information System
patient-reported outcomes
PDSQ
Person response curve
Person scores
Person-fit
Personality measurement
Piecewise assessment of fit
Polytomous IRT Model
Polytomous IRT models
Polytomous Items
Price_€100 and above
Procrustean Transformations
PS=Active
psychological measurement
Qualitative research
Ramsay-curves
Reliability
Residual indices
Response biases
Responsiveness
Second-order model
softlaunch
Stochastic approximation
Test development
Test score linking
Test validity
Testgraph
Testlet
Two-parameter model
Two-tier
Two-tier models
Typical performance data
Unidimensional IRT Model
Unidimensional Model
Unidimensionality
Unipolar item response model
Validity
Van Der Ark
Verbal aggression
Wald test
Weibull

Product details

  • ISBN 9781138787858
  • Weight: 852g
  • Dimensions: 178 x 254mm
  • Publication Date: 12 Dec 2014
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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Description

Item response theory (IRT) has moved beyond the confines of educational measurement into assessment domains such as personality, psychopathology, and patient-reported outcomes. Classic and emerging IRT methods and applications that are revolutionizing psychological measurement, particularly for health assessments used to demonstrate treatment effectiveness, are reviewed in this new volume. World renowned contributors present the latest research and methodologies about these models along with their applications and related challenges. Examples using real data, some from NIH-PROMIS, show how to apply these models in actual research situations. Chapters review fundamental issues of IRT, modern estimation methods, testing assumptions, evaluating fit, item banking, scoring in multidimensional models, and advanced IRT methods. New multidimensional models are provided along with suggestions for deciding among the family of IRT models available. Each chapter provides an introduction, describes state-of-the art research methods, demonstrates an application, and provides a summary. The book addresses the most critical IRT conceptual and statistical issues confronting researchers and advanced students in psychology, education, and medicine today. Although the chapters highlight health outcomes data the issues addressed are relevant to any content domain.

The book addresses:

IRT models applied to non-educational data especially patient reported outcomes

Differences between cognitive and non-cognitive constructs and the challenges these bring to modeling.

The application of multidimensional IRT models designed to capture typical performance data.

Cutting-edge methods for deriving a single latent dimension from multidimensional data

A new model designed for the measurement of constructs that are defined on one end of a continuum such as substance abuse

Scoring individuals under different multidimensional IRT models and item banking for patient-reported health outcomes

How to evaluate measurement invariance, diagnose problems with response categories, and assess growth and change.

Part 1 reviews fundamental topics such as assumption testing, parameter estimation, and the assessment of model and person fit. New, emerging, and classic IRT models including modeling multidimensional data and the use of new IRT models in typical performance measurement contexts are examined in Part 2. Part 3 reviews the major applications of IRT models such as scoring, item banking for patient-reported health outcomes, evaluating measurement invariance, linking scales to a common metric, and measuring growth and change. The book concludes with a look at future IRT applications in health outcomes measurement. The book summarizes the latest advances and critiques foundational topics such a multidimensionality, assessment of fit, handling non-normality, as well as applied topics such as differential item functioning and multidimensional linking.

Intended for researchers, advanced students, and practitioners in psychology, education, and medicine interested in applying IRT methods, this book also serves as a text in advanced graduate courses on IRT or measurement. Familiarity with factor analysis, latent variables, IRT, and basic measurement theory is assumed.

About
Steven P. Reise is a full professor in Quantitative Psychology at UCLA. Dennis A. Revicki is Senior Vice President of health outcomes research at Evidera and an adjunct professor at the University of North Carolina, University of Florida, and Georgetown University.