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A Course in Rasch Measurement Theory Measuring in the Educational, Social and Health Sciences
Author
Title
A Course in Rasch Measurement Theory [electronic resource] : Measuring in the Educational, Social and Health Sciences / by David Andrich, Ida Marais.
ISBN
9789811374968
Edition
1st ed. 2019.
Publication
Singapore : Springer Singapore : Imprint: Springer, 2019.
Physical Description
1 online resource (XIX, 482 p.) 134 illus., 61 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book applies Rasch measurement theory to the fields of education, psychology, sociology, marketing and health outcomes in order to measure various social constructs. The chief focus is on first principles of both the theory and its applications. Because software is readily available to carry out analyses of real data, numerous small examples are provided in the book. The software used in these examples, and which is helpful in working through the text, is RUMM2030 (Rasch unidimensional models for measurement). The book’s main goals are to equip researchers with the confidence they need in order to be in control of the analysis and interpretation of data, and to make professional rather than primarily statistical decisions mechanically. Because statistical principles are necessarily involved, reviews of the requisite statistics are provided in the Appendix. The content is based on courses that have been taught both online and in intensive form for over two decades. Although first principles are emphasised, much of the book is based on research conducted by the two authors and their colleagues.
Variant and related titles
Springer ENIN.
Other formats
Printed edition:
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
July 18, 2019
Series
Springer Texts in Education,
Contents
PART A: General principles and the dichotomous Rasch model
Chapter 1: The idea of measurement
Chapter 2: Constructing instruments to achieve measurement
Chapter 3: Classical test theory (CTT)
Chapter 4: Reliability and validity in CTT
Chapter 5: The Guttman structure and analysis of responses
Chapter 6: The dichotomous Rasch model - The simplest modern test theory model
Chapter 7: Invariance of comparisons - Separation of person and item parameters
Chapter 8: Sufficiency - The significance of total scores
Chapter 9: Estimating item difficulty
Chapter 10: Estimating person proficiency and person separation
Chapter 11: Equating - Linking instruments through common items
Chapter 12: Comparisons and contrasts between CTT and Rasch measurement theory (RMT)
PART B: The dichotomous Rasch model: Fit of responses to the model
Chapter 13: Fit of responses to the model I - Item characteristic curve and Chi-square tests of fit
Chapter 14: Violations of the assumption of independence I - Multidimensionality and response dependence
Chapter 15: Fit of responses to the model II - Analysis of residuals and general principles
Chapter 16: Fit of responses to the model III - Differential item functioning
Chapter 17: Fit of responses to the model IV - Guessing
Chapter 18: Other models of modern test theory for dichotomous responses
Chapter 19: Comparisons and contrasts between item response theory (IRT) and RMT
PART C: Extending the dichotomous Rasch model: The polytomous Rasch model
Chapter 20: The polytomous Rasch model I
Chapter 21: The polytomous Rasch model II
Chapter 21: The polytomous Rasch model II
Chapter 21: The polytomous Rasch model II
Chapter 24: Violations of the assumption of independence II – The polytomous Rasch model
Part D: Theoretical justifications and further elaborations
Chapter 25: Derivation of CTT equations and coefficient α
Chapter 26: Analysis of more than two facets and repeated measures
Chapter 27: Derivation of the threshold form of the polytomous Rasch model
Chapter 28: Non-Rasch measurement models for ordered response categories
Chapter 29: Review of principles of test analysis using Rasch measurement theory
Part E: RUMM2030 Exercises
Exercise 1: Interpretation of RUMM2030 printout
Exercise 2: Basic analysis of dichotomous and polytomous responses
Exercise 3: Advanced analysis of dichotomous responses
Exercise 4: Advanced analysis of polytomous responses
Exercise 5: Analysis of data with differential item functioning
Exercise 6: Analysis of data with dependence
Exercise 7: Analysis of more than two facets and repeated measurements
Exercise 8: Writing up a Rasch model analysis
Part F: Statistics Reviews
Statistics Review 1: Sigma notation, mean, and variance
Statistics Review 2: Normal distribution
Statistics Review 3: Covariance and the variance of the sum of two variables
Statistics Review 4: Regression and correlation
Statistics Review 5: Probability
Statistics Review 6: Indices
Statistics Review 7: Logarithms
Statistics Review 8: Conditional probability
Statistics Review 9: Independence
Statistics Review 10: Bernoulli and Binomial variables
Statistics Review 11: The Chi-square distribution and test
Statistics Review 12: Analysis of variance (ANOVA)
Statistics Review 13: Distribution theory
Statistics Review 14: Basic distributions for tests of fit
Statistics Review 15: Odds and ratios.
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