Application of a Longitudinal IRTree Model: Response Style Changes Over Time

Assessment ◽  
2021 ◽  
pp. 107319112110429
Author(s):  
Allison J. Ames ◽  
Brian C. Leventhal
Keyword(s):  
Data Collection ◽  
Response Style ◽  
Adult Health ◽  
Sexual Knowledge ◽  
Bias Estimation ◽  
Modeling Framework ◽  
Extreme Response ◽  
Item Responses ◽  
Psychometric Models ◽  
Knowledge Scale

Traditional psychometric models focus on studying observed categorical item responses, but these models often oversimplify the respondent cognitive response process, assuming responses are driven by a single substantive trait. A further weakness is that analysis of ordinal responses has been primarily limited to a single substantive trait at one time point. This study applies a significant expansion of this modeling framework to account for complex response processes across multiple waves of data collection using the item response tree (IRTree) framework. This study applies a novel model, the longitudinal IRTree, for response processes in longitudinal studies, and investigates whether the response style changes are proportional to changes in the substantive trait of interest. To do so, we present an empirical example using a six-item sexual knowledge scale from the National Longitudinal Study of Adolescent to Adult Health across two waves of data collection. Results show an increase in sexual knowledge from the first wave to the second wave and a decrease in midpoint and extreme response styles. Model validation revealed failure to account for response style can bias estimation of substantive trait growth. The longitudinal IRTree model captures midpoint and extreme response style, as well as the trait of interest, at both waves.

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.

Multidimensional Modeling of Traits and Response Styles

2017 ◽  
Vol 33 (5) ◽  
pp. 352-364 ◽  
Author(s):  
Eunike Wetzel ◽  
Claus H. Carstensen
Keyword(s):  
Personality Traits ◽  
Latent Trait ◽  
Response Style ◽  
Response Styles ◽  
Extreme Response ◽  
Item Responses ◽  
A Posteriori Estimates ◽  
Sum Scores ◽  
Different Response ◽  
A Minor

Abstract. Response styles can influence item responses in addition to a respondent’s latent trait level. A common concern is that comparisons between individuals based on sum scores may be rendered invalid by response style effects. This paper investigates a multidimensional approach to modeling traits and response styles simultaneously. Models incorporating different response styles as well as personality traits (Big Five facets) were compared regarding model fit. Relationships between traits and response styles were investigated and different approaches to modeling extreme response style (ERS) were compared regarding their effects on trait estimates. All multidimensional models showed a better fit than the unidimensional models, indicating that response styles influenced item responses with ERS showing the largest incremental variance explanation. ERS and midpoint response style were mainly trait-independent whereas acquiescence and disacquiescence were strongly related to several personality traits. Expected a posteriori estimates of participants’ trait levels did not differ substantially between two-dimensional and unidimensional models when a set of heterogeneous items was used to model ERS. A minor adjustment of trait estimates occurred when the same items were used to model ERS and the trait, though the ERS dimension in this approach only reflected scale-specific ERS, rather than a general ERS tendency.

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.

Response Biases

2016 ◽  
pp. 349-363 ◽  
Author(s):  
Eunike Wetzel ◽  
Jan R. Böhnke ◽  
Anna Brown
Keyword(s):  
Cultural Differences ◽  
Test Construction ◽  
Response Styles ◽  
Cross Cultural Differences ◽  
Extreme Response ◽  
Trait Level ◽  
Item Responses ◽  
Item Content ◽  
General Response ◽  
Response Biases

Response biases comprise a variety of systematic tendencies of responding to questionnaire items. Response biases exert an influence on item responses in addition to any constructs that the questionnaire is designed to measure and can therefore potentially bias the corresponding trait level estimates. This chapter addresses general response biases that are independent of item content, including response styles (e.g., extreme response style, acquiescence) and rater biases (halo effect, leniency/severity bias), as well as response biases that are related to item content and depend strongly on the context (socially desirable responding). The chapter summarizes research on correlates of response biases and research on inter-individual and cross-cultural differences in engaging in response styles and rater biases. It describes different methods that can be applied at the test construction stage to prevent or minimize the occurrence of response biases. Finally, it depicts methods developed for correcting for the effects of response biases.

Sign in / Sign up

Export Citation Format

Share Document