Guttman Scaling: An Error Paradigm

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.

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Mokken Scale Analysis: Discussion and Application

Advances in Social Sciences Research Journal ◽

10.14738/assrj.83.9949 ◽

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.

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