An Elaboration of Guttman Scaling with Rasch Models for Measurement

1985 ◽  
Vol 15 ◽  
pp. 33 ◽  
Author(s):  
David Andrich
Keyword(s):  
Rasch Models ◽  
Guttman Scaling

Review of Rasch Models for Measurement.

1989 ◽  
Vol 34 (3) ◽  
pp. 297-297
Author(s):  
No authorship indicated
Keyword(s):  
Rasch Models

Right-Wing Authoritarians Aren't Very Funny: RWA, Personality, and Creative Humor Production

2020 ◽  
Author(s):  
Paul Silvia ◽  
Alexander P. Christensen ◽  
Katherine N. Cotter
Keyword(s):  
Young Adults ◽  
Latent Variable ◽  
Latent Variable Models ◽  
Openness To Experience ◽  
Rasch Models ◽  
Right Wing ◽  
Right Wing Authoritarianism ◽  
Humor Appreciation ◽  
Negative Effect

Right-wing authoritarianism (RWA) has well-known links with humor appreciation, such as enjoying jokes that target deviant groups, but less is known about RWA and creative humor production—coming up with funny ideas oneself. A sample of 186 young adults completed a measure of RWA, the HEXACO-100, and 3 humor production tasks that involved writing funny cartoon captions, creating humorous definitions for quirky concepts, and completing joke stems with punchlines. The humor responses were scored by 8 raters and analyzed with many-facet Rasch models. Latent variable models found that RWA had a large, significant effect on humor production (β = -.47 [-.65, -.30], p < .001): responses created by people high in RWA were rated as much less funny. RWA’s negative effect on humor was smaller but still significant (β = -.25 [-.49, -.01], p = .044) after controlling for Openness to Experience (β = .39 [.20, .59], p < .001) and Conscientiousness (β = -.21 [-.41, -.02], p = .029). Taken together, the findings suggest that people high in RWA just aren’t very funny.

Two Comments on Guttman Scaling

1969 ◽  
Vol 75 (2) ◽  
pp. 278-280
Author(s):  
Peter Weldon ◽  
J. David Martin ◽  
Louis N. Gray
Keyword(s):  
Guttman Scaling

scholarly journals Elderly and caregiver demand: proposal for a care need classification

2018 ◽  
Vol 71 (suppl 2) ◽  
pp. 844-850 ◽  
Author(s):  
Daniella Pires Nunes ◽  
Tábatta Renata Pereira de Brito ◽  
Ligiana Pires Corona ◽  
Tiago da Silva Alexandre ◽  
Yeda Aparecida de Oliveira Duarte
Keyword(s):  
Well Being ◽  
The Elderly ◽  
Cross Sectional Study ◽  
Full Time ◽  
Cross Sectional ◽  
Everyday Activities ◽  
Aging Study ◽  
Good Internal Consistency ◽  
Caregiver Demand ◽  
Guttman Scaling

ABSTRACT Objective: To propose a care need classification for elderly people by identifying their functional demands. Method: Cross-sectional study carried out in São Paulo, in 2006, with 1,413 elderly (≥ 60 years old), participants in the Health, Well-being and Aging study (SABE – Saúde, Bem Estar e Envelhecimento). For the care need classification, we used the Guttman Scaling method e the frequency of assistance required by the elderly. Results: The hierarchy of activities of daily living had good internal consistency (α = 0.92) and satisfactory coefficients of reproducibility (98%), scalability (84%) and minimum marginal reproducibility (87%). Care need was categorized into: no need (requires no caregiver), minimum need (requires caregiver sporadically), moderate need (requires caregiver intermittently) and maximum need (requires full-time caregiver). Conclusion: This classification will allow identifying elderly that need assistance in everyday activities and will orientante health professionals in the development of a line of care.

Mokken Scale Analysis: Discussion and Application

2021 ◽  
Vol 8 (3) ◽  
pp. 672-695
Author(s):  
Thomas DeVaney
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Rating Scale ◽  
Scale Analysis ◽  
Guttman Scale ◽  
Response Theory ◽  
Data Set ◽  
Mokken Scale Analysis ◽  
Irt Models ◽  
Guttman Scaling

This article presents a discussion and illustration of Mokken scale analysis (MSA), a nonparametric form of item response theory (IRT), in relation to common IRT models such as Rasch and Guttman scaling. The procedure can be used for dichotomous and ordinal polytomous data commonly used with questionnaires. The assumptions of MSA are discussed as well as characteristics that differentiate a Mokken scale from a Guttman scale. MSA is illustrated using the mokken package with R Studio and a data set that included over 3,340 responses to a modified version of the Statistical Anxiety Rating Scale. Issues addressed in the illustration include monotonicity, scalability, and invariant ordering. The R script for the illustration is included.

scholarly journals Comparing item parameter estimates and fit statistics of the Rasch model from three different traditions

2020 ◽  
Vol 24 (1) ◽  
Author(s):  
Bahrul Hayat ◽  
Muhammad Dwirifqi Kharisma Putra ◽  
Bambang Suryadi
Keyword(s):  
Factor Analysis ◽  
Rasch Model ◽  
Measurement Model ◽  
Rasch Measurement ◽  
Item Parameter ◽  
Rasch Models ◽  
Rasch Measurement Model ◽  
Item Factor Analysis ◽  
The Rasch Model ◽  
Special Case

Rasch model is a method that has a long history in its application in the fields of social and behavioral sciences including educational measurement. Under certain circumstances, Rasch models are known as a special case of Item response theory (IRT), while IRT is equivalent to the Item Factor Analysis (IFA) models as a special case of Structural Equation Models (SEM), although there are other ‘tradition’ that consider Rasch measurement models not part of both. In this study, a simulation study was conducted to using simulated data to explain how the interrelationships between the Rasch model as a constraint version of 2-parameter logistic (2-PL) IRT, Rasch model as an item factor analysis were compared with the Rasch measurement model using Mplus, IRTPRO and WINSTEPS program, each of which came from its own 'tradition'. The results of this study indicate that Rasch models and IFA as a special case of SEM are mathematically equal, as well as the Rasch measurement model, but due to different philosophical perspectives people might vary in their understanding about this concept. Given the findings of this study, it is expected that confusion and misunderstanding between the three can be overcome.

A Comparison of Uniform DIF Effect Size Estimators Under the MIMIC and Rasch Models

2012 ◽  
Vol 73 (2) ◽  
pp. 339-358 ◽  
Author(s):  
Ying Jin ◽  
Nicholas D. Myers ◽  
Soyeon Ahn ◽  
Randall D. Penfield
Keyword(s):  
Effect Size ◽  
Rasch Models

Guttman Scaling: An Error Paradigm

1973 ◽  
Vol 16 (1) ◽  
pp. 5-26
Author(s):  
Richard R. Clayton
Keyword(s):  
Guttman Scaling ◽  
Error Paradigm
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