A Cross-National Comparison of Extreme Response Style Measures

2014 ◽  
Vol 56 (1) ◽  
pp. 89-110 ◽  
Author(s):  
Robert A. Peterson ◽  
Pablo Rhi-Perez ◽  
Gerald Albaum
Keyword(s):  
Rating Scale ◽  
Response Style ◽  
Traditional Measure ◽  
A Value ◽  
Extreme Response Style ◽  
Extreme Response ◽  
National Comparison ◽  
The Individual ◽  
Study Participants ◽  
Cross National

Five measures of extreme response style were compared across 6,146 study participants from 36 countries: the traditional measure, a modified traditional measure, the individual standard deviation, an index of dispersion and an index of entropy. The traditional measure of extreme response style, whereby the two extreme categories of an item or rating scale are assigned a value of ‘1’, all interior categories are assigned a value of ‘0’ and the sum of the ‘1’ values reflects the extent of extreme responding behaviour, performed slightly better than the other extreme response style measures examined with respect to reliability and ability to discriminate. The traditional measure of extreme response style was positively related to the variance of an attitudinal variable but unrelated to its mean. It was also related to Hofstede's cultural orientation variables of individualism-collectivism and power distance. Future cross-cultural and cross-national empirical research should systematically incorporate measures of extreme responding so that more is learned about the phenomenon and its possible effects.

A Scaled Threshold Model for Measuring Extreme Response Style

2019 ◽  
Vol 45 (1) ◽  
pp. 86-107
Author(s):  
Dirk Lubbe ◽  
Christof Schuster
Keyword(s):  
Rating Scale ◽  
Threshold Model ◽  
Model Fitting ◽  
Reliability And Validity ◽  
Scaling Factor ◽  
Response Style ◽  
Individual Response ◽  
Extreme Response Style ◽  
Extreme Response ◽  
Item Responses

Extreme response style is the tendency of individuals to prefer the extreme categories of a rating scale irrespective of item content. It has been shown repeatedly that individual response style differences affect the reliability and validity of item responses and should, therefore, be considered carefully. To account for extreme response style (ERS) in ordered categorical item responses, it has been proposed to model responder-specific sets of category thresholds in connection with established polytomous item response models. An elegant approach to achieve this is to introduce a responder-specific scaling factor that modifies intervals between thresholds. By individually expanding or contracting intervals between thresholds, preferences for selecting either the outer or inner response categories can be modeled. However, for a responder-specific scaling factor to appropriately account for ERS, there are two important aspects that have not been considered previously and which, if ignored, will lead to questionable model properties. Specifically, the centering of threshold parameters and the type of category probability logit need to be considered carefully. In the present article, a scaled threshold model is proposed, which accounts for these considerations. Instructions on model fitting are given together with SAS PROC NLMIXED program code, and the model’s application and interpretation is demonstrated using simulation studies and two empirical examples.

scholarly journals A Mixture IRTree Model for Extreme Response Style: Accounting for Response Process Uncertainty

2020 ◽  
pp. 001316442091391
Author(s):  
Nana Kim ◽  
Daniel M. Bolt
Keyword(s):  
Real Data ◽  
Response Style ◽  
Response Styles ◽  
Individual Level ◽  
Process Uncertainty ◽  
Extreme Response Style ◽  
Learning Mathematics ◽  
Extreme Response ◽  
The Individual ◽  
Mathematics And Science

This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the individual level (within an individual). Simulation analyses reveal the potential of the mixture approach in identifying subgroups of respondents exhibiting response behavior reflective of different underlying response processes. Application to real data from the Students Like Learning Mathematics (SLM) scale of Trends in International Mathematics and Science Study (TIMSS) 2015 demonstrates the superior comparative fit of the mixture representation, as well as the consequences of applying the mixture on the estimation of content and response style traits. We argue that methodology applied to investigate response styles should attend to the inherent uncertainty of response style influence due to the likely influence of both response styles and the content trait on the selection of extreme response categories.

scholarly journals Kernel Causality Among Teacher Self-Efficacy, Job Satisfaction, School Climate, and Workplace Well-Being and Stress in TALIS

2021 ◽  
Vol 12 ◽  
Author(s):  
Xue Zhang ◽  
Chunyang Zhao ◽  
Yuqiao Xu ◽  
Shanhuai Liu ◽  
Zhihui Wu
Keyword(s):  
Job Satisfaction ◽  
School Climate ◽  
Self Efficacy ◽  
Teaching And Learning ◽  
Well Being ◽  
Individual Characteristics ◽  
Response Style ◽  
Extreme Response Style ◽  
Extreme Response ◽  
Teacher Self Efficacy

Teachers play an important role in the educational system. Teacher self-efficacy, job satisfaction, school climate, and workplace well-being and stress are four individual characteristics shown to be associated with tendency to turnover. In this article, data from the Teaching and Learning International Survey (TALIS) 2018 teacher questionnaire are analyzed, with the goal to understand the interplay amongst these four individual characteristics. The main purposes of this study are to (1) measure extreme response style for each scale using unidimensional nominal response models, and (2) investigate the kernel causal paths among teacher self-efficacy, job satisfaction, school climate, and workplace well-being and stress in the TALIS-PISA linked countries/economies. Our findings support the existence of extreme response style, the rational non-normal distribution assumption of latent traits, and the feasibility of kernel causal inference in the educational sector. Results of the present study inform the development of future correlational research and policy making in education.

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