scholarly journals A Mokken Scale Analysis of the Last Series of the Standard Progressive Matrices (SPM-LS)

2020 ◽  
Vol 8 (2) ◽  
pp. 22
Author(s):  
Nils Myszkowski
Keyword(s):  
Psychometric Properties ◽  
Item Response ◽  
Scale Analysis ◽  
Mokken Scale Analysis ◽  
General Mental Ability ◽  
Invariant Item Ordering ◽  
Raven's Standard Progressive Matrices ◽  
Sum Scores ◽  
Double Monotonicity ◽  
Theory Framework

Raven’s Standard Progressive Matrices (Raven 1941) is a widely used 60-item long measure of general mental ability. It was recently suggested that, for situations where taking this test is too time consuming, a shorter version, comprised of only the last series of the Standard Progressive Matrices (Myszkowski and Storme 2018) could be used, while preserving satisfactory psychometric properties (Garcia-Garzon et al. 2019; Myszkowski and Storme 2018). In this study, I argue, however, that some psychometric properties have been left aside by previous investigations. As part of this special issue on the reinvestigation of Myszkowski and Storme’s dataset, I propose to use the non-parametric Item Response Theory framework of Mokken Scale Analysis (Mokken 1971, 1997) and its current developments (Sijtsma and van der Ark 2017) to shed new light on the SPM-LS. Extending previous findings, this investigation indicated that the SPM-LS had satisfactory scalability ( H = 0.469 ), local independence and reliability ( M S = 0.841 , L C R C = 0.874 ). Further, all item response functions were monotonically increasing, and there was overall evidence for invariant item ordering ( H T = 0.475 ), supporting the Double Monotonicity Model (Mokken 1997). Item 1, however, appeared problematic in most analyses. I discuss the implications of these results, notably regarding whether to discard item 1, whether the SPM-LS sum scores can confidently be used to order persons, and whether the invariant item ordering of the SPM-LS allows to use a stopping rule to further shorten test administration.

Mokken Scale Analysis: Discussion and Application

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.

scholarly journals A Mokken scale analysis of the Kessler-6 screening measure among Chinese older population: findings from a national survey

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lisong Zhang ◽  
Zhongquan Li
Keyword(s):  
Psychological Distress ◽  
Psychometric Properties ◽  
Differential Item Functioning ◽  
Scale Analysis ◽  
Older Population ◽  
Old Chinese ◽  
Mokken Scale Analysis ◽  
Screening Measure ◽  
Item Functioning ◽  
Public Data

Abstract Background The aging population increases rapidly across the world. Timely and effective screening of their mental-health problems is important to individuals, families, and the whole society. The Kessler-6 screening measure (K6) is a very popular instrument for non-specific psychological distress. However, few studies have focused on the psychometric properties of this instrument in the older population. Methods The present study employed Mokken scale analysis to evaluate its dimensionality and structure. This study also used differential item functioning (DIF) to examine whether the same structure existed across sex in a national representative sample of old Chinese people. Data were drawn from a public data set, the 2010 China Family Panel Studies (CFPS2010), and responses from a total of 6450 participants aged 60 years old and above (3136 males and 3314 females) were included in the final analysis. Results Mokken scale analysis supported the unidimensional structure of the K6. Differential item functioning (DIF) analysis revealed that two of the six items (“Hopeless” and “Everything was an effort”) were marked for DIF based on the Chi-square. However, their impacts were negligible in terms of McFadden’s pseudo R2. Conclusions The K6 demonstrates adequate psychometric properties in the old Chinese population. The sum of all six items can be used as an indicator of non-specific psychological distress. Differences in the indicator across sex should be considered as a real difference in psychological distress between the female and the male.

scholarly journals Treading Carefully: Agnostic Identification as the First Step of Detecting Differential Item Functioning

2021 ◽  
Author(s):  
Ben Stenhaug ◽  
Michael C. Frank ◽  
Benjamin Domingue
Keyword(s):  
Best Practices ◽  
Differential Item Functioning ◽  
Item Response ◽  
Identification Problem ◽  
Demographic Groups ◽  
Test Items ◽  
Response Data ◽  
Item Functioning ◽  
Sum Scores ◽  
Theory Framework

Differential item functioning (DIF) is a popular technique within the item-response theory framework for detecting test items that are biased against particular demographic groups. The last thirty years have brought significant methodological advances in detecting DIF. Still, typical methods—such as matching on sum scores or identifying anchor items—are based exclusively on internal criteria and therefore rely on a crucial piece of circular logic: items with DIF are identified via an assumption that other items do not have DIF. This logic is an attempt to solve an easy-to-overlook identification problem at the beginning of most DIF detection. We explore this problem, which we describe as the Fundamental DIF Identification Problem, in depth here. We suggest three steps for determining whether it is surmountable and DIF detection results can be trusted. (1) Examine raw item response data for potential DIF. To this end, we introduce a new graphical method for visualizing potential DIF in raw item response data. (2) Compare the results of a variety of methods. These methods, which we describe in detail, include commonly-used anchor item methods, recently-proposed anchor point methods, and our suggested adaptations. (3) Interpret results in light of the possibility of DIF methods failing. We illustrate the basic challenge and the methodological options using the classic verbal aggression data and a simulation study. We recommend best practices for cautious DIF detection.

scholarly journals A Mokken Scale Analysis of the Kessler-6 Screening Measure among Chinese Older Population: Findings from a national survey

2020 ◽  
Author(s):  
Lisong Zhang ◽  
Zhongquan Li
Keyword(s):  
Psychological Distress ◽  
Psychometric Properties ◽  
Differential Item Functioning ◽  
Scale Analysis ◽  
Data Set ◽  
Old Chinese ◽  
Mokken Scale Analysis ◽  
Screening Measure ◽  
Item Functioning ◽  
Public Data

Abstract BackgroundThe aging population increases rapidly across the world. Timely and effective screening of their mental health problems is important to individuals, families, and the whole society. The Kessler-6 screening measure (K6) is a very popular instrument for non-specific psychological distress. However, few studies have focused on the psychometric properties of this instrument in the older population.MethodsThe present study employed Mokken scale analysis to evaluate its dimensionality and structure, and used differential item functioning (DIF) to examine whether the same structure existed across sex in a national representative sample of old Chinese people. Data were drawn from a public data set, the 2010 China Family Panel Studies (CFPS2010), and responses from a total of 6450 participants aged 60 years old and above (3136 males and 3314 females) were included in the final analysis.ResultsMokken scale analysis supported the unidimensional structure of the K6. Differential item functioning (DIF) analysis revealed that two of the six items ("Hopeless" and "Everything was an effort") were marked for DIF based on the Chi-square. However, their impacts were negligible in terms of McFadden's pseudo R 2.ConclusionsThe K6 demonstrates adequate psychometric properties in the old Chinese population. The sum of all six items can be used as an indicator of non-specific psychological distress. Differences in the indicator across sex should be considered as a real difference in psychological distress between the female and the male.

scholarly journals Psychometric properties of the short-form CART: Investigating its dimensionality through a Mokken Scale analysis

2021 ◽  
Vol 39 ◽  
pp. 100793
Author(s):  
Marion Tillema ◽  
Samantha Bouwmeester ◽  
Peter Verkoeijen ◽  
Anita Heijltjes
Keyword(s):  
Psychometric Properties ◽  
Short Form ◽  
Scale Analysis ◽  
Mokken Scale Analysis

scholarly journals A Mokken Scale Analysis of the Kessler-6 Screening Measure among Chinese Elderly Population: Findings from a national survey

2020 ◽  
Author(s):  
Lisong Zhang ◽  
Zhongquan Li
Keyword(s):  
Psychological Distress ◽  
Psychometric Properties ◽  
Differential Item Functioning ◽  
Elderly Population ◽  
Ageing Population ◽  
Scale Analysis ◽  
Old Chinese ◽  
Mokken Scale Analysis ◽  
Screening Measure ◽  
Item Functioning

Abstract Background The ageing population increases rapidly across the world. Timely and effective screening of their mental health problems is important to individuals, families and the whole society. The Kessler-6 screening measure (K6) is a very popular instrument for non-specific psychological distress. However, few studies have focused on the psychometric properties of this instrument in the elderly population. Methods The present study employed Mokken scale analysis to evaluate its dimensionality and structure, and employed differential item functioning (DIF) to examine whether the same structure existed across sex in a national representative sample of old Chinese people. Data were drawn from a public data set, the 2010 China Family Panel Studies (CFPS2010), and responses from a total of 6450 participants aged 60 years old and above (3136 males and 3314 females) were included in the final analysis. Results Mokken scale analysis supported the unidimensional structure of the K6. Differential item functioning (DIF) analysis revealed that two of the six items ("Hopeless" and "Everything was an effort") were marked for DIF based on the Chi-square. However, their impacts were negligible in term of McFadden's pseudo R2. Conclusions The K6 demonstrates adequate psychometric properties in the old Chinese population. The sum of all six items can be used as an indicator of non-specific psychological distress. Differences in the indicator across gender should be considered as a real difference in psychological distress between the female and the male.

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