scholarly journals Visualizing Items and Measures: An Overview and Demonstration of the Kernel Smoothing Item Response Theory Technique

2020 ◽  
Author(s):  
Gordana Rajlic
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Kernel Smoothing ◽  
Classical Test Theory ◽  
Well Being ◽  
R Package ◽  
Test Theory ◽  
Response Theory ◽  
Irt Models ◽  
Exploratory Data

Motivated by a renewed interest in exploratory data analysis and data visualization in psychology and social sciences, the current demonstration was conducted to familiarize a broader audience of applied researchers with the benefits of an exploratory psychometric technique – kernel smoothing item response theory (KSIRT). A data-driven, nonparametric KSIRT provides a visual representation of the characteristics of the items in a measure (scale or test) and offers convenient preliminary feedback about functioning of the items and the measure in a particular research context. The technique could be a useful addition to the analytical toolkit of applied researchers that work with a range of measures, within the classical test theory or IRT framework, and is suitable for use with a smaller number of items or respondents compared to parametric IRT models. KSIRT is described and its use is demonstrated with a set of items from a psychological well-being measure. A recently developed, easy to use R package was utilized to perform the analyses and the R code is included in the manuscript.

scholarly journals Mokken Scale Analysis: Between the Guttman Scale and Parametric Item Response Theory

2003 ◽  
Vol 11 (2) ◽  
pp. 139-163 ◽  
Author(s):  
Wijbrandt H. van Schuur
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Classical Test Theory ◽  
Test Theory ◽  
Scale Analysis ◽  
Guttman Scale ◽  
Response Theory ◽  
Mokken Scale Analysis ◽  
Irt Models ◽  
The One

This article introduces a model of ordinal unidimensional measurement known as Mokken scale analysis. Mokken scaling is based on principles of Item Response Theory (IRT) that originated in the Guttman scale. I compare the Mokken model with both Classical Test Theory (reliability or factor analysis) and parametric IRT models (especially with the one-parameter logistic model known as the Rasch model). Two nonparametric probabilistic versions of the Mokken model are described: the model of Monotone Homogeneity and the model of Double Monotonicity. I give procedures for dealing with both dichotomous and polytomous data, along with two scale analyses of data from the World Values Study that demonstrate the usefulness of the Mokken model.

scholarly journals Using Item Response Theory to Identify Responders to Treatment: Examples with the Patient-Reported Outcomes Measurement Information System (PROMIS®) Physical Function Scale and Emotional Distress Composite

Psychometrika ◽  
2021 ◽  
Author(s):  
Ron D. Hays ◽  
Karen L. Spritzer ◽  
Steven P. Reise
Keyword(s):  
Item Response Theory ◽  
Physical Function ◽  
Item Response ◽  
Emotional Distress ◽  
Classical Test Theory ◽  
Test Theory ◽  
Measurement Information ◽  
Response Theory ◽  
Reliable Change ◽  
Patient Reported

AbstractThe reliable change index has been used to evaluate the significance of individual change in health-related quality of life. We estimate reliable change for two measures (physical function and emotional distress) in the Patient-Reported Outcomes Measurement Information System (PROMIS®) 29-item health-related quality of life measure (PROMIS-29 v2.1). Using two waves of data collected 3 months apart in a longitudinal observational study of chronic low back pain and chronic neck pain patients receiving chiropractic care, and simulations, we compare estimates of reliable change from classical test theory fixed standard errors with item response theory standard errors from the graded response model. We find that unless true change in the PROMIS physical function and emotional distress scales is substantial, classical test theory estimates of significant individual change are much more optimistic than estimates of change based on item response theory.

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