Measurement equivalence and latent mean differences of safety climate measures across industries, positions, and gender

2013 ◽  
Author(s):  
Gargi Sawhney ◽  
Konstantin P. Cigularov ◽  
Pete Kines
Keyword(s):  
Safety Climate ◽  
Measurement Equivalence ◽  
Latent Mean Differences ◽  
And Gender ◽  
Mean Differences

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

Longitudinal and Gender Measurement Invariance of the Gratitude Questionnaire in Chinese Adolescents

2021 ◽  
pp. 003329412110360
Author(s):  
Qingsong Tan ◽  
Jilin Zou ◽  
Feng Kong
Keyword(s):  
Measurement Invariance ◽  
Time Interval ◽  
Longitudinal Measurement Invariance ◽  
Multiple Group ◽  
Longitudinal Measurement ◽  
Confirmatory Factor ◽  
Adolescent Sample ◽  
Good Internal Consistency ◽  
And Gender ◽  
Mean Differences

The 5-item Gratitude Questionnaire (GQ-5) is one of the most commonly used instruments to measure dispositional gratitude in adolescents. The purpose of this study was to verify the longitudinal measurement invariance (LMI) and gender measurement invariance (GMI) of the GQ-5 that was administered to an adolescent sample twice over the course of 18 months ( N = 669). Single-group confirmatory factor analysis (CFA) was adopted to examine the LMI and multiple-group CFA was conducted to assess the GMI. The results showed that the GQ-5 had strong invariance (i.e., equality of factor patterns, loadings, and intercepts) across time and gender. Validation of latent factor mean differences showed that females had higher gratitude scores than males. In addition, the GQ-5 exhibited good internal consistency indices across time and a moderate stability coefficient was also found across an 18-month time interval in adolescents. In summary, our study showed that LMI and GMI of the GQ-5 are satisfactory and the GQ-5 is a reliable instrument for measuring gratitude in adolescents.

Psychometric Properties and Measurement Invariance Across Sex of the Wong and Law Emotional Intelligence Scale in Chinese adolescents

2020 ◽  
pp. 003329412097263
Author(s):  
Meilin Di ◽  
Xinping Deng ◽  
Jingjing Zhao ◽  
Feng Kong
Keyword(s):  
Emotional Intelligence ◽  
Measurement Invariance ◽  
Factor Model ◽  
Chinese Adolescents ◽  
Female Adolescents ◽  
Intelligence Scale ◽  
Male Adolescents ◽  
Latent Mean Differences ◽  
Emotional Appraisal ◽  
Mean Differences

The aim of this study was to validate the Wong and Law Emotional Intelligence Scale (WLEIS) in Chinese adolescents by examining factor structure, sex-related measurement invariance and latent mean differences, reliability, and criterion-related validity.A total of 1674 Chinese adolescents aged 12–17 years old (Mage = 15.26, SD = .58) were recruited. Results of confirmatory factor analysis (CFA) supported the four-factor model of the WLEIS as the best fit to the data. Multi-group CFA suggested that the measurement structure of the WLEIS was invariant across sex. Testing for the latent mean differences showed that male adolescents scored lower on the Other-Emotional Appraisal subscale, but scored higher on the Regulation of Emotion subscale than female adolescents. Furthermore, all the subscales of male and female adolescents had satisfactory composite reliability. Finally, the WLEIS had favorable criterion-related validity with self-esteem, life satisfaction, positive affect, negative affect and perceived stress. These findings suggested that the WLEIS is a reliable and valid instrument for assessing trait emotional intelligence of adolescents and can be generalized across sex.

Validation, factorial invariance, and latent mean differences across sex of the Depression, Anxiety, and Stress Scales (DASS-21) in Ecuadorian university sample.

2022 ◽  
Author(s):  
Ricardo Sanmartín ◽  
Raquel Suria-Martínez ◽  
María de Lourdes López-López ◽  
María Vicent ◽  
Carolina Gonzálvez ◽  
...  
Keyword(s):  
Factorial Invariance ◽  
Latent Mean Differences ◽  
Mean Differences

scholarly journals Measuring Individuals’ Misogynistic Attitudes: Development and Validation of the Misogyny Scale

2021 ◽  
Author(s):  
Bettina Rottweiler ◽  
Paul Gill
Keyword(s):  
Factor Analysis ◽  
Discriminant Validity ◽  
Age Groups ◽  
Strong Relationship ◽  
Hostile Sexism ◽  
Medium Effect ◽  
Extensive Literature ◽  
Male And Female ◽  
Latent Mean Differences ◽  
Mean Differences

Across three studies based on a nationally representative survey (n = 1500), we developed and validated the misogyny scale. Initial items were generated from an extensive literature search and subsequently derived from validated scales assessing internalised misogyny, hostile sexism, and hostility towards women. Construct and measurement validity were established across several studies. An exploratory factor analysis (Study 1, n = 750) established the factor structure of the 10-item misogyny scale. In study 2 (n = 750), the 10-item structure was replicated via confirmatory factor analysis. The misogyny scale displayed good convergent (i.e., significant and strong relationship with male sexual entitlement, masculinity related violent beliefs and willingness to use violence) and discriminant validity (i.e., no relationship with analytical thinking). In study 3 (n = 750), we established measurement invariance across gender and age groups. This allows researchers to deploy the scale among male and female individuals, across different age groups as well as to assess latent mean differences. Significant latent mean differences for all three latent factors emerged between male and female participants, demonstrating that men had significantly stronger misogynistic attitudes than women (MDiff1 = -.482***; MDiff2 = -.324***; MDiff3 = -.197***). The latent mean differences ranged from small (Cohen’s d2 = .27; Cohen’s d3 = .19) to medium effect sizes (Cohen’s d1 = .38). The strongest latent mean differences between age groups were found for the factor ‘manipulative and exploitative nature of women’. Older age groups reported significantly stronger attitudes relating to this factor than younger participants. The misogyny scale will allow researchers to explore the psychological antecedents and consequences of misogyny among population samples and the subsequent findings may have important practical implications for prevention and intervention programs on violent (extremist) propensity development.

Methods

2018 ◽  
pp. 68-87
Keyword(s):  
Factor Structure ◽  
Academic Motivation ◽  
Longitudinal Design ◽  
Time Stability ◽  
Motivation And Engagement ◽  
And Gender ◽  
Mean Differences ◽  
Senior Secondary

The current study examined how motivation developed in four Australian senior secondary colleges, using Martin's model of motivation and engagement. It explored changes in the nature of academic motivation through a longitudinal design with three measurement points by examining the factor structure of the SMES-HS, the concurrent associations among its constructs at each point in time, stability and mean differences between the constructs across time and gender. In this chapter, the methods used in the current study will be explained.

scholarly journals NOSACQ-50 for Safety Climate Assessment in Agricultural Activities: A Case Study in Central Italy

2020 ◽  
Vol 17 (24) ◽  
pp. 9177
Author(s):  
Mario Fargnoli ◽  
Mara Lombardi
Keyword(s):  
Safety Climate ◽  
Central Italy ◽  
Agricultural Activities ◽  
Cross Sectional ◽  
Safety Issues ◽  
Climate Assessment ◽  
And Gender ◽  
Sustainable Agricultural Systems ◽  
Sectional Analysis

Safety climate assessment has been recognized as a powerful tool to bring to light workers’ perceptions related to safety practices, attitudes and behaviors at the workplace. Accordingly, its investigation can provide useful information about safety problems within a company before accidents occur. In literature, numerous studies can be found investigating safety climates in different types of industry. However, safety climate assessment in agricultural activities is addressed scarcely, even though agriculture represents a very hazardous sector. To reduce this gap, the present study proposes an investigation of safety climate among farmers by means of the Nordic Safety Climate Questionnaire (NOSACQ-50). The results of the survey brought to light a low level of safety perception of the interviewed sample, especially as concerns safety commitment and risk-taking attitudes. In particular, a different attitude toward safety issues has been registered depending on both the position and gender of the interviewed farmers. Overall, the output of this cross-sectional analysis adds to the current literature by expanding knowledge of safety climate among farmers, representing a baseline for further investigations based on human-centered approaches to enhance safety in agriculture and consequently social and workplace aspects of sustainable agricultural systems.

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