RMT 26:1 Notes and Quotes

Rasch and Distributions

Question: What assumptions are made about distributions by the Rasch model?

Answer: The Rasch model makes no assumptions about the distributions of the parameters. Maximum Likelihood Estimation (MLE) assumes that the randomness in the data is normally distributed. Some estimation methods, such as Marginal Maximum Likelihood (MMLE), assume that the incidental parameters (usually persons) conform to a well-behaved distribution (usually normal).

In the realm of scientific creativity ...

"Quality is a probabilistic function of quantity."

Simonton, D. (2003), Scientific Creativity as Constrained Stochastic Behavior: The Integration of Product, Person and Process Perspectives. Psychological Bulletin, 129(4), 475-494.

ConQuest 3.0

ACER ConQuest 3.0 is software for fitting unidimensional and multidimensional item response and latent regression models. It provides data analysis based on item response models (IRM), allowing examination of the properties of performance assessments, traditional assessments and rating scales. ConQuest 3.0 offers analysis procedures based on multifaceted item response models, multidimensional item response models, latent regression models and drawing plausible values.

New Features include:

• Bradley-Terry-Luce (BTL) model for pairwise comparisons
  
• Marginal maximum likelihood or joint maximum likelihood estimation
  
• Fitting of multidimensional and multifaceted forms of Bock's nominal response, two parameter logistic (2PL) and generalized partial credit models.
  
• Direct reading of SPSS system files
  
• Output of results to SPSS or EXCEL files
  
• A wide array of graphical outputs, including Wright maps and Wright predicted probability maps
  
• Person fit and residuals
  
• Latent variable path modeling
  
• Mantel-Haenszel DIF estimates

Ray Adams, Margaret Wu and Mark Wilson

conquest-sales.acer.edu.au

ORVOMS: Ohio River Valley Objective Measurement Seminar

The 2nd Annual Ohio River Valley Objective Measurement Seminar (ORVOMS) was held on May 18th, 2012 at the University of Kentucky. It was hosted by Dr. Kelly Bradley of the Department of Educational Policy Studies & Evaluation and co-sponsored by Dr. Arne Bathke of the Applied Statistics Laboratory. The keynote speaker was Dr. Richard Smith from Data Recognition Corporation. In addition to the regional attendees some participants traveled from as far away as Florida, Michigan, and Minnesota.

Presentations included:

• Using Rasch measurement to inform policy and practice through comparisons of theoretical and empirical hierarchies
  
• Equivalence of Angoff Ratings and Calibrations
  
• An External Validation Study of a Classification of Mixed Connective Tissue Disease and Systemic Lupus Erythematosus Patients
  
• Using the Rasch Rating Scale Model to Measure Job Satisfaction among Kentucky Head Principals
• An Exploration of Data Driven Decision Making Among College Admission Professionals
• When does Guessing Begin?

We thank everyone who participated and presented this year - it was an interesting and collegial meeting. We look forward to next year's seminar and hope that you will be able to participate. For information about upcoming events or to be placed on our mailing list please contact:

Melanie Lybarger
Psychometric Research Associate
The American Board of Family Medicine
mlybarger ~ theabfm.org

6th Annual UK Rasch Users Group Meeting
20th March 2012, Weetwood Hall, Leeds, UK

• Svend Kreiner. University of Copenhagen. Is the foundation under PISA solid? A critical look at the scaling model underlying international comparisons of student attainment.
• Christine Merrell , Peter Tymms and Irene Styles. Universities of Durham, and Western Australia. Cross-country Comparisons of Inattentive, Hyperactive and Impulsive Behaviour in School-Based Samples of Young Children.
• Maria Pampaka, The University of Manchester. Measuring Pedagogies in Mathematics with the Rasch Model: from Secondary School to University and across countries.
• Fabio Camargo, Brian Henson. University of Leeds. Rasch Theory in Product Design Applications
• Bryan. Moreton. University of Nottingham. Rasch Analysis of the Intermittent and Constant Osteoarthritis Pain Questionnaire.
• Ashworth, F., Bauch, E., Bateman, A. Oliver Zangwill Centre for Neuropsychological Rehabilitation. Forms of Self-Criticism, Self-attacking and Self Reassurance Scale in an ABI population using Rasch Analysis
• Tracey Young, John Brazier, Donna Rowen, Brendan Mulhern, Ifigeneia Mavranezouli. ScHARR, University of Sheffield and University College London. Deriving preference-based utility measures from existing measures: How Health Economists Make Use of Rasch Analysis
• Bateman, A. Sun, L . Oliver Zangwill Centre for Neuropsychological Rehabilitation and University of Cambridge. Analysis of Responses to the Ekman 60 Faces: Perception of Emotion Testing in 194 patients who have suffered from brain injury.
• Panayiotis Panayides . Lyceum of Polemidia. Is Aberrant Response Behaviour an Inherent Characteristic of Students Taking Classroom Maths Tests?
• Twiss J, Crawford SR, McKenna SP. Galen Research, Manchester. Co-Calibrating Scores from Two Dermatology-Specific Patient Reported Outcome Measures.

UK Rasch User Group, /www.rasch.org.uk

Journal of Applied Measurement Vol. 13, No. 1, 2012

• Formulating Latent Growth Using an Explanatory Item Response Model Approach. Mark Wilson, Xiaohui Zheng, and Leah McGuire. 1-22
• Using the Mixed Rasch Model to Analyze Data from the Beliefs and Attitudes About Memory Survey. Everett V. Smith, Jr., Yuping Ying, and Scott W. Brown, 23-40
• An Examination of Personality Characteristics Related to Acquiescence. Christine DiStefano, Grant B. Morgan, and Robert W. Motl, 41-56
• Construction and Validation of Two Parent-Report Scales for the Evaluation of Early Intervention Programs. William P. Fisher, Jr., Batya Elbaum, and W. Alan Coulter, 57-76
• Multi-Factor Scale Consolidation When Theory is Weak. Nikolaus Bezruczko and Kyle Perkins, 77-96
• Understanding Rasch Measurement: Developing an Emotional Distress Item Bank for Cancer Patients. Allen W. Heinemann, Rita K. Bode, Sarah Rosenbloom, and David Cella, 97-113.

Richard M. Smith, Editor, www.jampress.org

Notes and Quotes, Rasch Measurement Transactions, 2012, 26:1, passim

Rasch Publications
Rasch Measurement Transactions (free, online)	Rasch Measurement research papers (free, online)	Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch	Applying the Rasch Model 3rd. Ed., Bond & Fox	Best Test Design, Wright & Stone
Rating Scale Analysis, Wright & Masters	Introduction to Rasch Measurement, E. Smith & R. Smith	Introduction to Many-Facet Rasch Measurement, Thomas Eckes	Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr.	Statistical Analyses for Language Testers, Rita Green
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar	Journal of Applied Measurement	Rasch models for measurement, David Andrich	Constructing Measures, Mark Wilson	Rasch Analysis in the Human Sciences, Boone, Stave, Yale
in Spanish:	Análisis de Rasch para todos, Agustín Tristán		Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez

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