Examining Multidimensional Measuring Instruments for Proximity to Unidimensional Structure Using Latent Variable Modeling

Raykov, Tenko; Bluemke, Matthias

doi:10.1177/0013164420940764

Cited by 7 publications

(6 citation statements)

References 31 publications

(52 reference statements)

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“…First, the inspection of the pattern showed that it exhibited positive manifold (i.e., all the loadings were substantial and positive). Second, the ECV estimate was .789 (bootstrap 95% CI = 0.764 and 0.815), above the 0.70 usual cutoff for judging a unidimensional approximation as reasonable (Raykov & Bluemke, 2021; Reise et al, 2013). Indeed, approximating a multidimensional structure by a unidimensional solution potentially presents the underfactoring problems discussed above: biased “mixture” loading estimates that would reflect the differential influence of the local factors, loss of information, and scores reflecting the influence of multiple sources of variance.…”

Section: Illustrative Examplementioning

confidence: 88%

A Relative Normed Effect-Size Difference Index for Determining the Number of Common Factors in Exploratory Solutions

Ferrando,

Navarro-González,

Lorenzo-Seva

2023

Educational and Psychological Measurement

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Descriptive fit indices that do not require a formal statistical basis and do not specifically depend on a given estimation criterion are useful as auxiliary devices for judging the appropriateness of unrestricted or exploratory factor analytical (UFA) solutions, when the problem is to decide the most appropriate number of common factors. While overall indices of this type are well known in UFA applications, especially those intended for item analysis, difference indices are much more scarce. Recently, Raykov and collaborators proposed a family of effect-size-type descriptive difference indices that are promising for UFA applications. As a starting point, we considered the simplest measure of this family, which (a) can be viewed as absolute and (b) from which only tentative cutoffs and reference values have been provided so far. In this situation, this article has three aims. The first is to propose a relative version of Raykov’s effect-size measure, intended to be used as a complement of the original measure, in which the increase in explained common variance is related to the overall prior estimated amount of common factor variance. The second is to establish reference values for both indices in item-analysis scenarios using simulation. And the third aim (instrumental) is to implement the proposal in both R language and a well-known non-commercial factor analysis program. The functioning and usefulness of the proposal is illustrated using an existing empirical dataset.

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Section: Illustrative Examplementioning

confidence: 88%

A Relative Normed Effect-Size Difference Index for Determining the Number of Common Factors in Exploratory Solutions

Ferrando,

Navarro-González,

Lorenzo-Seva

2023

Educational and Psychological Measurement

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“…The study further examined the validity of the TIOSS for explaining the validity of the scale and its predictive effect on actual behavior [56]. In previous studies, occupational stigma was observed to be negatively influencing the organizational atmosphere as well as practitioners' work attitudes, behaviors, intergroup relations, professional identity, and psychological well-being [57].…”

Section: Discussionmentioning

confidence: 99%

The development and validation of tour guides internalized occupational stigma scale (TIOSS)

Fan,

Shi,

Liu

et al. 2024

BMC Public Health

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Background Tour guides’ identification and internalization of occupational stigma may exacerbate their career development, perceived professional reputation and status, and mental health. The current study aimed to develop and verify the Tour guides Internalized Occupational Stigma Scale (TIOSS) to provide an effective tool for relevant quantitative research. Methods The study developed an initial questionnaire through literature analysis, expert review, and semi-structured surveys. We conducted item analyses and exploratory factor analyses among 326 tour guides, and confirmatory factor analysis and reliability and validity tests among 315 tour guides. Results The TIOSS consists of 21 items and is formed in three dimensions referring to Stigma Perception (SP), Status Loss (SL), and Career Denial (CD). The correlation coefficient values of the TIOSS total scale and dimension scores with the criterion instruments ranged from 0.17 to 0.68. In addition, the Cronbach’s α coefficients for the TIOSS and its dimensions ranged from 0.837 to 0.928, and the split-half reliability coefficients ranged from 0.843 to 0.916. The study also revealed that the TIOSS was consistent across genders. Conclusion The TIOSS performed favorable reliability and validity to be a valid instrument to assess tour guides' internalized occupational stigma.

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“…If analysis models are multidimensional (assuming no crossloadings), separate MIVIs should be used for each subscale. Alternatively, one might estimate how proximate the multidimensional model is to a unidimensional one, indicating whether the multidimensional model can be treated as essentially unidimensional (Raykov & Bluemke, 2020). Extensions of MIVI for multidimensional scales are conceivable but beyond the scope of the present demonstration.…”

Section: Quantifying Scalar Non-invariance Bias 24mentioning

confidence: 95%

Measurement Invariance Violation Indices (MIVIs): Effect sizes for (partial) non-invariance of items and item sets

Groskurth¹,

Bluemke²,

Lechner³

et al. 2021

Preprint

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When scalar invariance does not hold, which is often the case in application scenarios, the amount of non-invariance bias may either be consequential for observed mean comparisons or not. So far, only a few attempts have been made to quantify the extent of bias due to measurement non-invariance. Building on Millsap and Olivera-Aguilar (2012), we derived a new effect size measure, called Measurement Invariance Violation Index (MIVI), from first principles. MIVI merely assumes partial scalar invariance for a set of items forming a scale and quantifies the intercept difference of one non-invariant item (at the item-score level) or several non-invariant items (at the scale-score level) as the share (i.e., proportion) of the total observed scale score difference between groups. One can inspect the cancelation effects of item bias at the scale-score level when using directional instead of absolute terms. We provide computational code and exemplify MIVI in simulated contexts.

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Examining Multidimensional Measuring Instruments for Proximity to Unidimensional Structure Using Latent Variable Modeling

Cited by 7 publications

References 31 publications

A Relative Normed Effect-Size Difference Index for Determining the Number of Common Factors in Exploratory Solutions

A Relative Normed Effect-Size Difference Index for Determining the Number of Common Factors in Exploratory Solutions

The development and validation of tour guides internalized occupational stigma scale (TIOSS)

Measurement Invariance Violation Indices (MIVIs): Effect sizes for (partial) non-invariance of items and item sets

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