What to do when scalar invariance fails: The extended alignment method for multi-group factor analysis comparison of latent means across many groups.

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.

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Multi-Group Factor Analysis and Latent Means Analysis of the Sports Sociability Scale

Asian Journal of Physical Education and Sport Science ◽

10.24007/ajpess.2017.5.2.004 ◽

2017 ◽

Vol 5 (2) ◽

pp. 37-49

Author(s):

김성훈

Keyword(s):

Factor Analysis ◽

Group Factor ◽

Latent Means

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

10.31234/osf.io/82brm ◽

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.

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Development and Validation of the Economic Coercion Scale 36 (ECS-36) in Rural Bangladesh

Journal of Interpersonal Violence ◽

10.1177/0886260520987812 ◽

2021 ◽

pp. 088626052098781

Author(s):

Kathryn M. Yount ◽

Yuk Fai Cheong ◽

Stephanie Miedema ◽

Ruchira T. Naved

Keyword(s):

Factor Analysis ◽

Partner Violence ◽

Short Form ◽

Latent Trait ◽

Married Women ◽

Primary Data ◽

Group Factor ◽

Rural Bangladesh ◽

Multiple Group ◽

Economic Coercion

Assessing progress toward Sustainable Development Goal (SDG) 5, to achieve gender equality and to empower women, requires monitoring trends in intimate partner violence (IPV). Current measures of IPV may miss women’s experiences of economic coercion, or interference with the acquisition, use, and maintenance of financial resources. This sequential, mixed-methods study developed and validated a scale for economic coercion in married women in rural Bangladesh, where women’s expanding economic opportunities may elevate the risks of economic coercion and other IPV. Forty items capturing lifetime and prior-year economic coercion were adapted from formative qualitative research and prior scales and administered to a probability sample of 930 married women 16–49 years. An economic coercion scale (ECS) was validated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) with primary data from random-split samples ( N1 = 310; N2 = 620). Item response theory (IRT) methods gauged the measurement precision of items and scales over the range of the economic-coercion latent trait. Multiple-group factor analysis assessed measurement invariance of the economic-coercion construct. Two-thirds (62.26%) of women reported any lifetime economic coercion. EFA suggested a 36-item, two-factor model capturing barriers to acquire and to use or maintain economic resources. CFA, multiple group factor analysis, and multidimensional IRT methods confirmed that this model provided a reasonable fit to the data. IRT analysis showed that each dimension provided most precision over the higher range of the economic coercion trait. The Economic Coercion Scale 36 (ECS-36) should be validated elsewhere and over time. It may be added to violence-specific surveys and evaluations of violence-prevention and economic-empowerment programs that have a primary interest measuring economic coercion. Short-form versions of the ECS may be developed for multipurpose surveys and program monitoring.

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The Effect of Nepotism on Organizational Silence, Alienation and Commitment: A Study on Hotel Employees in Turkey

Journal of Management Research ◽

10.5296/jmr.v7i4.7806 ◽

2015 ◽

Vol 7 (4) ◽

pp. 82 ◽

Cited By ~ 2

Author(s):

Elbeyi Pelit ◽

Füsun İstanbullu Dinçer ◽

İbrahim Kılıç

Keyword(s):

Factor Analysis ◽

Regression Analysis ◽

Standard Deviation ◽

Positive Relationship ◽

Negative Relationship ◽

Group Factor ◽

Correlation And Regression Analysis ◽

Hotel Employees ◽

Organizational Silence ◽

Study Results

<p>The aim of this study is to determine the effect of nepotism on organizational silence, alienation and commitment. As a data collecting method a questionnaire which contains nepotism, organizational silence, alienation and commitment scales was used. It was applied on 662 employees working in 30 five star hotels in Turkey. Since nepotism covers the practices in establishments in which family-relative relations are concentrated, the hotels included in the sampling group have been selected from establishments whose proprietors are a part of a family/family group. Factor analysis, Cronbach’s Alpha, mean, standard deviation, correlation and regression analysis were used to analyze the acquired data. The study results revealed that nepotism has a positive relationship with organizational silence and alienation and a negative relationship with organizational commitment. </p>

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