Modeling Response Styles in Cross‐Country Self‐Reports: An Application of a Multilevel Multidimensional Nominal Response Model

Ju, Unhee; Falk, Carl F.

doi:10.1111/jedm.12205

Cited by 15 publications

(16 citation statements)

References 46 publications

(92 reference statements)

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“…Hence, they can be considered a systematic source of error in measurement. As a consequence, response styles can bias conclusions drawn from measurement in terms of measurement precision (Bolt, Lu, & Kim, 2014; Wetzel & Carstensen, 2017), relations between variables (Böckenholt & Meiser, 2017), or cross‐group comparisons, for example in cross‐cultural research (Cheung & Rensvold, 2000; Harzing, 2006; Ju & Falk, 2019).…”

mentioning

confidence: 99%

A Novel Partial Credit Extension Using Varying Thresholds to Account for Response Tendencies

Henninger

2020

J Educational Measurement

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Item Response Theory models with varying thresholds are essential tools to account for unknown types of response tendencies in rating data. However, in order to separate constructs to be measured and response tendencies, specific constraints have to be imposed on varying thresholds and their interrelations. In this article, a multidimensional extension of a Partial Credit Model using a sum‐to‐zero constraint for varying thresholds is proposed. The new model allows us to flexibly account for response tendencies and to model covariations between varying thresholds that are commonly found in empirical data. The model's ability to estimate different types of response tendencies under various data structures is shown in a simulation study. An illustrative multicountry analysis demonstrates that differences between respondents in terms of their response tendencies exist and can be captured by the new model. Furthermore, it is well suited to account for extreme and mid response styles, but also to accommodate unknown, previously unmodeled, response tendencies. Therewith, the sum‐to‐zero model can be considered a suitable candidate to examine the types response tendencies in rating data and to account for biases in construct measures due to response tendencies.

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confidence: 99%

A Novel Partial Credit Extension Using Varying Thresholds to Account for Response Tendencies

Henninger

2020

J Educational Measurement

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“…For instance, Buckley (2009) considered heterogeneous response scales across countries for PISA 2006 data. Ju and Falk (2019) used a multilevel multidimensional nominal response model to measure ERS using TALIS 2013 data.…”

Section: Response Stylesmentioning

confidence: 99%

“…As recommended by Ju and Falk (2019), the nominal response model (NRM; Bock, 1972) is applied to multi-group analysis to accommodate extreme response styles. Let y ijg denote the polytomous scored response of an examinee j (j = 1, .…”

Section: Response Stylesmentioning

confidence: 99%

“…Third, the influences of other factors (e.g., burnout, distributed leadership, or emotion regulation) should be considered and compared to seek an effective mechanism for teachers' psychological health (Rew, 2013;Liu and Hallinger, 2018;Moè and Katz, 2020a,b). Furthermore, we can use the multilevel or/and multidimensional nominal response model to analyze ERS (Ju and Falk, 2019). Finally, international comparative study of educational policies and education ecological environment should be conducted to explain the different causal paths among such factors.…”

Section: Limitationsmentioning

confidence: 99%

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

Zhang

Zhao

et al. 2021

Front. Psychol.

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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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“…Thus, the item still may provide more information regarding the participant's standing on QOL than it does for ERS, and additional work may still be required to further examine item information in the context of such a multidimensional model. It may instead be more worthwhile to compare slopes across items for a single dimension, such as comparing which items are most closely related to ERS (e.g., Deng and Bolt, 2017;Ju and Falk, 2019).…”

Section: Choice Of Scoring Functionsmentioning

confidence: 99%

Estimation of Response Styles Using the Multidimensional Nominal Response Model: A Tutorial and Comparison With Sum Scores

Falk

2020

Front. Psychol.

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Recent years have seen a dramatic increase in item response models for measuring response styles on Likert-type items. These model-based approaches stand in contrast to traditional sum-score-based methods where researchers count the number of times that participants selected certain response options. The multidimensional nominal response model (MNRM) offers a flexible model-based approach that may be intuitive to those familiar with sum score approaches. This paper presents a tutorial on the model along with code for estimating it using three different software packages: flexMIRT ® , mirt, and Mplus. We focus on specification and interpretation of response functions. In addition, we provide analytical details on how sum score to scale score conversion can be done with the MNRM. In the context of a real data example, three different scoring approaches are then compared. This example illustrates how sum-score-based approaches can sometimes yield scores that are confounded with substantive content. We expect that the current paper will facilitate further investigations as to whether different substantive conclusions are reached under alternative approaches to measuring response styles.

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Modeling Response Styles in Cross‐Country Self‐Reports: An Application of a Multilevel Multidimensional Nominal Response Model

Cited by 15 publications

References 46 publications

A Novel Partial Credit Extension Using Varying Thresholds to Account for Response Tendencies

A Novel Partial Credit Extension Using Varying Thresholds to Account for Response Tendencies

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

Estimation of Response Styles Using the Multidimensional Nominal Response Model: A Tutorial and Comparison With Sum Scores

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