scholarly journals Measurement Invariance of the Career Futures Inventory–Revised Across General and Client Samples

2018 ◽  
Vol 27 (4) ◽  
pp. 711-725
Author(s):  
Chan Jeong Park ◽  
Patrick J. Rottinghaus ◽  
Ze Wang ◽  
Ti Zhang ◽  
Nikki A. Falk ◽  
...  
Keyword(s):  
Measurement Invariance ◽  
Scale Validation ◽  
Career Adaptability ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
Student Sample ◽  
Configural Invariance ◽  
Validation Procedure ◽  
Scalar Invariance ◽  
Latent Means

Establishing measurement invariance has been emphasized as an important scale validation procedure for group comparisons. The 28-item Career Futures Inventory–Revised (CFI-R) is a widely used measure of career adaptability that has demonstrated initial validity with various samples. The purpose of the present study is to further examine the validity of the CFI-R by testing measurement invariance between a general university student sample and a client sample. First, a five-factor confirmatory factor analysis model was tested with each group. Then, measurement invariance tests were conducted through subsequently examining configural invariance, metric invariance, and scalar invariance. Test of invariance was achieved until partial scalar invariance, suggesting that the CFI-R is similarly applicable to both clinical and nonclinical samples. In addition, the comparisons of latent means between two groups revealed that clients showed significantly lower latent means than general students for four factors: Career Agency, Occupational Awareness, Support, and Work–Life Balance.

Factorial Invariance in a Repeated Measures Design: An Application to the Study of Person-Organization Fit

2010 ◽  
Vol 13 (1) ◽  
pp. 485-493 ◽  
Author(s):  
Carmen Ximénez ◽  
Javier Revuelta
Keyword(s):  
Measurement Invariance ◽  
Repeated Measures ◽  
Point Of View ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
Factor Loadings ◽  
First Order ◽  
Repeated Measures Design ◽  
Order Factor ◽  
Person Organization Fit

An important methodological concern of any research based on a person-environment (P-E) fit approach is the operationalization of the fit, which imposes some measurement requirements that are rarely empirically tested with statistical methods. Among them, the assessment of the P and E components along commensurate dimensions is possibly the most cited one. This paper proposes to test the equivalence across the P and E measures by analyzing the measurement invariance of a multi-group confirmatory factor analysis model. From a methodological point of view, the distinct aspect of this approach within the context of P-E fit research is that measurement invariance is assessed in a repeated measures design. An example illustrating the procedure in a person-organization (P-O) fit dataset is provided. Measurement invariance was tested at five different hierarchical levels: (1) configural, (2) first-order factor loadings, (3) second-order factor loadings, (4) residual variances of observed variables, and (5) disturbances of first-order factors. The results supported the measurement invariance across the P and O measures at the third level. The implications of these findings for P-E fit studies are discussed.

scholarly journals Comparing Social Anxiety in Japanese and European Americans: Integrating Measurement Invariance and Prototype Analyses

2019 ◽  
Author(s):  
Alexander Krieg ◽  
Yiyuan Xu ◽  
David C Cicero ◽  
Sousuke Miyamoto ◽  
Hanna Krieg
Keyword(s):  
Social Anxiety ◽  
Measurement Invariance ◽  
Emotional Valence ◽  
Partial Metric ◽  
Configural Invariance ◽  
European Americans ◽  
Scalar Invariant ◽  
The Social ◽  
Item Content ◽  
Scalar Invariance

Objectives: The current studies examined measurement invariance and prototypical symptoms when comparing social anxiety between Japanese and European Americans. Methods: Study 1 investigated configural, metric, and scalar invariance for the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS), and their respective short forms (SPS-6 and SISA-6), among 163 Japanese and 193 European Americans. Study 2 examined 20 Japanese and 20 European Americans' responses to a social anxiety prototype vignette and investigated the emotional valence and content themes surrounding the generated descriptions.Results: Study 1 results supported partial scalar invariance of SPS-6 and SIAS-6, partial metric invariance for SIAS, and configural invariance for SPS. Study 2 found that although most descriptors generated by both groups were negative attributes, Japanese mentioned more neutral attributes that European Americans. Both groups mentioned similar percentages of descriptors consistent with the SPS and SIAS, but the non-invariant item content related to physiological anxiety such as fainting and becoming ill were mentioned more often by European Americans whereas the scalar invariant item content related to communication skills, such as mixing comfortably with others and difficulty talking with other people, were mentioned more often by Japanese.Conclusions: These findings highlight the need to integrate evidence of both measurement invariance and cultural validity in understanding and measurement of psychopathology across cultures.

scholarly journals Finding clusters of groups with measurement invariance: Unraveling intercept non-invariance with mixture multigroup factor analysis

2020 ◽  
Author(s):  
Kim De Roover
Keyword(s):  
Factor Analysis ◽  
Measurement Invariance ◽  
Behavioral Research ◽  
Invariant Factor ◽  
Factor Loadings ◽  
Latent Constructs ◽  
Daunting Task ◽  
Scalar Invariance ◽  
Metric Invariance ◽  
Latent Means

Comparisons of latent constructs across groups are ubiquitous in behavioral research and, nowadays, often numerous groups are involved. Measurement invariance of the constructs across the groups is imperative for valid comparisons and can be tested by multigroup factor analysis. For many groups, metric invariance (invariant factor loadings) often holds, whereas scalar invariance (invariant intercepts) is rarely supported. Scalar invariance is a prerequisite for comparing latent means, however. One may inspect group-specific intercepts to pinpoint non-invariances, but this is a daunting task in case of many groups. This paper presents mixture multigroup factor analysis (MMG-FA) for clustering groups based on their intercepts. Clusters of groups with scalar invariance are obtained by imposing cluster-specific intercepts and invariant loadings whereas unique variances, factor means and factor (co)variances can differ between groups. Thus, MMG-FA ties down the number of intercepts to inspect and generates clusters of groups wherein latent means can be validly compared.

Assessing the Measurement Invariance of the Gratitude Questionnaire–5 in Chinese and American Adolescents

2021 ◽  
Vol 24 ◽  
Author(s):  
Yu Ling ◽  
Qin Yang ◽  
Yifang Zeng ◽  
E. Scott Huebner
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Measurement Invariance ◽  
Factor Structure ◽  
Factor Analyses ◽  
Confirmatory Factor Analyses ◽  
Configural Invariance ◽  
Confirmatory Factor ◽  
Subsequent Comparison ◽  
Latent Means

Abstract Given the possibility of cultural differences in the meaning and levels of gratitude among children, we evaluated the measurement invariance of the Gratitude Questionnaire–5 (GQ–5) and differences in latent means across adolescents from two distinct cultures, China and America. Data were obtained from 1,991 Chinese and 1,685 American adolescents. Confirmatory factor analysis and multigroup confirmatory factor analysis were performed to examine the factor structure and the measurement equivalence across Chinese and American adolescents. The Cronbach’s alpha and Item-total Correlations of the GQ–5 were also evaluated. Results of confirmatory factor analyses provided support for the expected one-factor structure. Also, a series of multi-group confirmatory factor analyses supported full configural invariance, full metric invariance, and partial scalar invariance between the two groups. Furthermore, the findings suggested that the GQ–5 is suitable for conducting mean level comparisons. The subsequent comparison of latent means revealed that the Chinese adolescents reported significantly lower gratitude than American adolescents.

scholarly journals Finding clusters of groups with measurement invariance: Unraveling intercept non-invariance with mixture multigroup factor analysis

2020 ◽  
Author(s):  
Kim De Roover
Keyword(s):  
Factor Analysis ◽  
Measurement Invariance ◽  
Behavioral Research ◽  
Invariant Factor ◽  
Factor Loadings ◽  
Latent Constructs ◽  
Daunting Task ◽  
Scalar Invariance ◽  
Metric Invariance ◽  
Latent Means

Comparisons of latent constructs across groups are ubiquitous in behavioral research and, nowadays, often numerous groups are involved. Measurement invariance of the constructs across the groups is imperative for valid comparisons and can be tested by multigroup factor analysis. For many groups, metric invariance (invariant factor loadings) often holds, whereas scalar invariance (invariant intercepts) is rarely supported. Scalar invariance is a prerequisite for comparing latent means, however. One may inspect group-specific intercepts to pinpoint non-invariances, but this is a daunting task in case of many groups. This paper presents mixture multigroup factor analysis (MMG-FA) for clustering groups based on their intercepts. Clusters of groups with scalar invariance are obtained by imposing cluster-specific intercepts and invariant loadings whereas unique variances, factor means and factor (co)variances can differ between groups. Thus, MMG-FA ties down the number of intercepts to inspect and generates clusters of groups wherein latent means can be validly compared.

Measurement Invariance of Three Brief Measures of Rumination in Young Adults With and Without a History of Self-Injury

2020 ◽  
pp. 1-8
Author(s):  
Kate E. Tonta ◽  
Penelope Hasking ◽  
Mark Boyes ◽  
Joel Howell ◽  
Peter McEvoy ◽  
...  
Keyword(s):  
Measurement Invariance ◽  
Partial Metric ◽  
Total N ◽  
Thought Style ◽  
Configural Invariance ◽  
Self Injury ◽  
Item Functioning ◽  
History Of ◽  
Scalar Invariance ◽  
Metric Invariance

Abstract. Rumination is central to understanding the onset and maintenance of non-suicidal self-injury. Yet, no study has evaluated whether reported differences in rumination between people with and without a history of self-injury represent genuine group differences. The present study reports an investigation into the measurement invariance of three common measures of rumination in university students with and without a history of self-injury (total N = 1,519). Results revealed configural invariance for the Ruminative Responses Scale (RRS), the Ruminative Thought Style Questionnaire (RTSQ), and the Repetitive Thinking Questionnaire (RTQ). Additionally, the RTSQ and RTQ supported metric invariance, while the RRS supported partial metric invariance. Further, the RTQ demonstrated partial scalar invariance while the RTSQ demonstrated full scalar invariance. The current findings suggest that observed differences using the RTSQ and RTQ reflect genuine differences in rumination between people with and without a history of self-injury, while researchers using the RRS are advised to account for differential item functioning.

Assessing cross-national invariance of the Community Assessment of Psychic Experiences (CAPE)

2018 ◽  
Vol 49 (15) ◽  
pp. 2600-2607 ◽  
Author(s):  
Baptiste Pignon ◽  
Hugo Peyre ◽  
Aziz Ferchiou ◽  
Jim van Os ◽  
Bart P. F. Rutten ◽  
...  
Keyword(s):  
Measurement Invariance ◽  
Self Report ◽  
Environment Interaction ◽  
Factorial Structure ◽  
Community Assessment ◽  
Factor Loadings ◽  
Configural Invariance ◽  
Scalar Invariance ◽  
Incident Cases ◽  
Cross National

AbstractBackgroundThe Community Assessment of Psychic Experiences (CAPE) is a 42-item self-report questionnaire that has been developed and validated to measure the dimensions of psychosis in the general population. The CAPE has a three-factor structure with dimensions of positive, negative and depression. Assessing the cross-national equivalence of a questionnaire is an essential prerequisite before pooling data from different countries. In this study, our aim was to investigate the measurement invariance of the CAPE across different countries.MethodsData were drawn from the European Union Gene-Environment Interaction (EU-GEI) study. Participants (incident cases of psychotic disorder, controls and siblings of cases) were recruited in Brazil, France, Italy, the Netherlands, Spain and UK. To analyse the measurement invariance across these samples, we tested configural invariance (i.e. identical structures of the factors), metric invariance (i.e. equivalence of the factor loadings) and scalar invariance (i.e. equivalence of the thresholds) of the three CAPE dimensions using multigroup categorical confirmatory factor analysis methods.ResultsThe configural invariance model fits well, providing evidence for identical factorial structure across countries. In comparison with the configural model invariance, the fit indices were very similar in the metric and scalar invariance models, indicating that factor loadings and thresholds did not differ across the six countries.ConclusionWe found that, across six countries, the CAPE showed equivalent factorial structure, factor loadings and thresholds. Thus, differences observed in scores between individuals from different countries should be considered as reflecting different levels of psychosis.

The Factor Structure and Measurement Invariance of Positive and Negative Affect

2016 ◽  
Vol 32 (4) ◽  
pp. 265-272 ◽  
Author(s):  
Mohsen Joshanloo ◽  
Ali Bakhshi
Keyword(s):  
Negative Affect ◽  
Measurement Invariance ◽  
Factor Structure ◽  
Factor Model ◽  
Positive And Negative Affect ◽  
Cultural Groups ◽  
Invariance Testing ◽  
The Usa ◽  
Scalar Invariance ◽  
Gender Groups

Abstract. This study investigated the factor structure and measurement invariance of the Mroczek and Kolarz’s scales of positive and negative affect in Iran (N = 2,391) and the USA (N = 2,154), and across gender groups. The two-factor model of affect was supported across the groups. The results of measurement invariance testing confirmed full metric and partial scalar invariance of the scales across cultural groups, and full metric and full scalar invariance across gender groups. The results of latent mean analysis revealed that Iranians scored lower on positive affect and higher on negative affect than Americans. The analyses also showed that American men scored significantly lower than American women on negative affect. The significance and implications of the results are discussed.

Is That Measure Really One-Dimensional?

Methodology ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 188-196 ◽  
Author(s):  
Esther T. Beierl ◽  
Markus Bühner ◽  
Moritz Heene
Keyword(s):  
Model Fit ◽  
Nuisance Parameters ◽  
Factorial Validity ◽  
Fit Indices ◽  
Analysis Model ◽  
Factor Analysis Model ◽  
One Dimensional ◽  
Confirmatory Factor Analysis Model ◽  
Cutoff Values ◽  
Confirmatory Factor

Abstract. Factorial validity is often assessed using confirmatory factor analysis. Model fit is commonly evaluated using the cutoff values for the fit indices proposed by Hu and Bentler (1999) . There is a body of research showing that those cutoff values cannot be generalized. Model fit does not only depend on the severity of misspecification, but also on nuisance parameters, which are independent of the misspecification. Using a simulation study, we demonstrate their influence on measures of model fit. We specified a severe misspecification, omitting a second factor, which signifies factorial invalidity. Measures of model fit showed only small misfit because nuisance parameters, magnitude of factor loadings and a balanced/imbalanced number of indicators per factor, also influenced the degree of misfit. Drawing from our results, we discuss challenges in the assessment of factorial validity.

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