Item Response Tree Models to Investigate Acquiescence and Extreme Response Styles in Likert-Type Rating Scales

Park, Minjeong; Wu, Amery D.

doi:10.1177/0013164419829855

Cited by 30 publications

(27 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Except for the COVID-19 Anxiety Scale, which consisted of items on a semantic differential scale, all the other instruments chose Likert response options, which is an interesting observation in light of the potential acquiescence bias with Likert rating scales. 51 COVID-19-imposed lockdown and quarantine measures may necessitate some individuals to stay away from their families. However, none of the available scales focused on separation anxiety.…”

Section: Discussionmentioning

confidence: 99%

Measuring the Impact of COVID-19 on Mental Health: A Scoping Review of the Existing Scales

Chandu

Marella

Panga

et al. 2020

Indian Journal of Psychological Medicine

View full text Add to dashboard Cite

Background: The coronavirus disease (COVID-19) pandemic, associated with the economic consequences of non-pharmaceutical interventions such as lockdown, has led to mental health consequences among people worldwide. Protecting the mental well-being of populations is an imperative component of fighting the COVID-19 pandemic. This scoping review attempts to present an overview of the existing tools to measure COVID-19-related mental health problems. Methods: Literature search was conducted in the PubMed electronic database using developed key search terms. Reference lists of the identified eligible articles were reviewed to locate relevant articles missed from the electronic database search. Fifteen scales measuring COVID-19-associated mental health problems, validated among diverse populations across the world, were included in this review. Results: The majority of these scales were validated among middle-aged adults in Turkey. Only a few validated scales encompass the negative socioeconomic consequences of COVID-19. None of the available scales focused on the aspects of suicidal ideation or behavioral responses/coping strategies, neither were they inclusive of participants from diverse age, geographic, and COVID-19 exposure groups. Conclusion: This scoping review highlights the need for future research to develop and validate comprehensive psychometric tools to assess COVID-19-associated mental health problems. Also, in view of the vulnerable nature of healthcare professionals for developing mental health concerns in the course of providing services for COVID-19-affected individuals, future psychometric research needs to concentrate on the development of measures specific for these professionals.

show abstract

Section: Discussionmentioning

confidence: 99%

Measuring the Impact of COVID-19 on Mental Health: A Scoping Review of the Existing Scales

Chandu

Marella

Panga

et al. 2020

Indian Journal of Psychological Medicine

View full text Add to dashboard Cite

show abstract

“…However, other response styles, such as ARS and DRS, have been found in responses to rating scales (e.g., Weijters et al, 2010b). Future research can examine the validity of the MNRM, the extensions of IR tree models (e.g., Plieninger and Heck, 2018;Park and Wu, 2019), and methods outside the IRT framework (e.g., latent class confirmatory factor models; Moors et al, 2014) for measuring ARS and DRS. Another limitation is that the current research only focused on one definition of ERS and MRS. We acknowledge that adopting different definitions might lead to different results.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Validity of Three IRT Models for Measuring and Controlling Extreme and Midpoint Response Styles

Zhang

Wang

2020

Front. Psychol.

View full text Add to dashboard Cite

Response styles, the general tendency to use certain categories of rating scales over others, are a threat to the reliability and validity of self-report measures. The mixed partial credit model, the multidimensional nominal response model, and the item response tree model are three widely used models for measuring extreme and midpoint response styles and correcting their effects. This research aimed to examine and compare their validity by fitting them to empirical data and correlating the content-related factors and the response style-related factors in these models to extraneous criteria. The results showed that the content factors yielded by these models were moderately related to the content criterion and not related to the response style criteria. The response style factors were moderately related to the response style criteria and weakly related to the content criterion. Simultaneous analysis of more than one scale could improve their validity for measuring response styles. These findings indicate that the three models could control and measure extreme and midpoint response styles, though the validity of the mPCM for measuring response styles was not good in some cases. Overall, the multidimensional nominal response model performed slightly better than the other two models.

show abstract

“…IRTree models have been proposed for modeling response styles (Park & Wu, 2019; Plieninger & Meiser, 2014). IRTree models (Böckenholt, 2012; De Boeck & Partchev, 2012; Jeon & De Boeck, 2016) characterize the underlying response processes associated with response selection using a sequential decision tree structure where IRT measurement models represent the outcomes at each decision node.…”

Section: Response Styles and Irtree Modelsmentioning

confidence: 99%

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

Kim

Bolt

2020

Educational and Psychological Measurement

View full text Add to dashboard Cite

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.

show abstract

Item Response Tree Models to Investigate Acquiescence and Extreme Response Styles in Likert-Type Rating Scales

Cited by 30 publications

References 47 publications

Measuring the Impact of COVID-19 on Mental Health: A Scoping Review of the Existing Scales

Measuring the Impact of COVID-19 on Mental Health: A Scoping Review of the Existing Scales

Validity of Three IRT Models for Measuring and Controlling Extreme and Midpoint Response Styles

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

Contact Info

Product

Resources

About