scholarly journals Examining Measurement Invariance of Depression among Male and Female in Chinese Older Adults

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 860-860
Author(s):  
Roberto Melipillán ◽  
Mengyao Hu
Keyword(s):  
Older Adults ◽  
Measurement Invariance ◽  
Epidemiological Studies ◽  
Difficult Problem ◽  
Health Concern ◽  
Confirmatory Factor Analyses ◽  
Male And Female ◽  
Chinese Older Adults ◽  
Multiple Group ◽  
Cultural Research

Abstract Depression of older adults is an important public health concern. With the increasing popularity of cross-cultural research and comparison studies, researchers are facing a difficult problem: responses to the depression scales obtained from different population groups may not always be comparable. This study examines the measurement invariance of the 10-item version of the Center for Epidemiological Studies Depression (CES-D) Scale across male and female in Chinese older adults. Data are drawn from the baseline wave of the China Health and Retirement Survey (CHARLS), a national survey conducted biennially with a sample of the Chinese population who are 45 years of age or older. The final sample size includes 15,977 respondents; 53.2% of whom are female. The mean age for the sample is 58.3 (SD = 10.2). Measurement invariance (MI) tests based on Multiple Group Categorical Confirmatory Factor Analyses (MGCCFA) was performed. Results show that full scalar model was not supported, and question items invariant across groups were identified. These results indicate that any mean comparisons of CES-D across Chinese male and female older adults not accounting for the noninvariance in the items could be biased, highlighting the importance of performing MI tests before conducting mean comparisons across groups.

scholarly journals Measurement invariance of the Illness Invalidation Inventory (3*I) across language, rheumatic disease and gender

2013 ◽  
Vol 73 (3) ◽  
pp. 551-556 ◽  
Author(s):  
Marianne Belia Kool ◽  
Rens van de Schoot ◽  
Isabel López-Chicheri García ◽  
Ricarda Mewes ◽  
José A P Da Silva ◽  
...  
Keyword(s):  
Rheumatic Disease ◽  
Measurement Invariance ◽  
Rheumatic Diseases ◽  
Future Research ◽  
Dutch Version ◽  
Confirmatory Factor Analyses ◽  
Online Study ◽  
Multiple Group ◽  
Antecedents And Consequences ◽  
And Gender

ObjectivesThe Illness Invalidation Inventory (3*I) assesses patients’ perception of responses of others that are perceived as denying, lecturing, not supporting and not acknowledging the condition of the patient. It includes two factors: ‘discounting’ and ‘lack of understanding’. In order to use the 3*I to compare and pool scores across groups and countries, the questionnaire must have measurement invariance; that is, it should measure identical concepts with the same factor structure across groups. The aim of this study was to examine measurement invariance of the 3*I across rheumatic diseases, gender and languages.MethodsParticipants with rheumatic disease from various countries completed an online study using the 3*I, which was presented in Dutch, English, French, German, Portuguese and Spanish; 6057 people with rheumatic diseases participated. Single and multiple group confirmatory factor analyses were used to test the factorial structure and measurement invariance of the 3*I with Mplus.ResultsThe model with strong measurement invariance, that is, equal factor loadings and thresholds (distribution cut-points) across gender and rheumatic disease (fibromyalgia vs other rheumatic diseases) had the best fit estimates for the Dutch version, and good fit estimates across the six language versions.ConclusionsThe 3*I showed measurement invariance across gender, rheumatic disease and language. Therefore, it is appropriate to compare and pool scores of the 3*I across groups. Future research may use the questionnaire to examine antecedents and consequences of invalidation as well as the effect of treatments targeting invalidation.

Construction and Factorial Structure of a Short Version of the Trendsetting Questionnaire (TDS-K)

2008 ◽  
Vol 24 (2) ◽  
pp. 88-94 ◽  
Author(s):  
Bernad Batinic ◽  
Hans-Georg Wolff ◽  
Christiane M. Haupt
Keyword(s):  
Measurement Invariance ◽  
Online Survey ◽  
Short Version ◽  
Confirmatory Factor Analyses ◽  
Multiple Group ◽  
Wide Range ◽  
Confirmatory Factor ◽  
Partial Invariance ◽  
Administration Methods ◽  
Broad Interest

This paper reports the development of a short version of the trendsetting questionnaire (TDS; Batinic, Haupt, & Wieselhuber, 2006 ). According to Batinic et al., individuals high on trendsetting keep an eye open for new trends and have a broad interest in innovations. They inform a wide range of others and explain to them the value of innovations, and they recommend specific products to friends and acquaintances. Empirical criteria as well as substantive criteria were used to select nine items representing the three subtypes of the trendsetting model: input, throughput, and output. Dimensionality and measurement invariance of the short version (TDS-K) were examined in two offline surveys (N = 2,001 and 948) and two online surveys (N = 4,450 and 12,087). Multiple group confirmatory factor analyses supported the unidimensionality of the measure and showed that measurement invariance held within each of the administration methods (offline vs. online survey), but only partial invariance held across these methods.

scholarly journals Forgiveness in the Context of Divorce: A Cross-Cultural Measurement Invariance Study via Multiple-Group Factor Analysis (CFA) across Chile and Spain

2021 ◽  
Vol 18 (16) ◽  
pp. 8236
Author(s):  
Diana Rivera-Ottenberger ◽  
Mónica Guzmán-González ◽  
Carlos Calderón ◽  
Sagrario Yárnoz-Yaben ◽  
Priscila Comino
Keyword(s):  
Measurement Invariance ◽  
Initial Step ◽  
Cross Cultural ◽  
Confirmatory Factor Analyses ◽  
Invariance Testing ◽  
Cross Cultural Differences ◽  
Multiple Group ◽  
Cultural Field ◽  
Confirmatory Factor ◽  
The Cross

(1) Background: Current research on the factors involved in the adaptation process to divorce or separation has explored cross-cultural differences. An initial step in the cross-cultural field is to investigate whether the measurements applied are comparable in different cultural contexts. The aim of the present study is to test the measurement invariance of the Questionnaire of Forgiveness in Divorce-Separation (CPD-S); (2) Methods: The CPD-S was completed by 556 (M = 44.52, SD = 10.18) and 240 (M = 41.44, SD = 7.87) Chilean and Spanish divorced individuals, respectively. Confirmatory factor analyses in single samples and measurement invariance testing in a multi-group framework were conducted to test the cross-group equivalence; (3) Results: The single-factor structure of the CPD-S was supported in both countries. Measurement invariance analysis demonstrated that the CPD-S had partial scalar measurement invariance; (4) Conclusions: The evidence supports the conclusion that CPD-S operates similarly across both countries. Findings are discussed from a cross-cultural and methodological perspective.

scholarly journals Measurement Invariance Testing Using Confirmatory Factor Analysis and Alignment Optimization: A Tutorial for Transparent Analysis Planning and Reporting

2021 ◽  
Author(s):  
Jessica Kay Flake ◽  
Raymond Luong
Keyword(s):  
Measurement Invariance ◽  
Traditional Approach ◽  
Research Question ◽  
Measurement Properties ◽  
Confirmatory Factor Analyses ◽  
Invariance Testing ◽  
Measurement Models ◽  
Multiple Group ◽  
Confirmatory Factor ◽  
Traditional Approaches

Measurement invariance—the notion that the measurement properties of a scale are equalacross groups, contexts, or time—is an important assumption underlying much of psychology research. The traditional approach for evaluating measurement invariance is to fit a series of nested measurement models using multiple-group confirmatory factor analyses. However, traditional approaches are strict, vary across the field in implementation, and present multiplicity challenges, even in the simplest case of two groups under study. The alignment method was recently proposed as an alternative approach. This method is more automated, requires fewer decisions from researchers, and accommodates two or more groups. However, it has different assumptions, estimation techniques, and limitations from traditional approaches. To address the lack of accessible resources that explain the methodological differences and complexities between the two approaches, we introduce and illustrate both, comparing them side by side. First, we overview the concepts, assumptions, advantages, and limitations of each approach. Based on this overview, we propose a list of four key considerations to help researchers decide which approach to choose and how to document their analytical decisions in a preregistration or analysis plan. We then demonstrate our key considerations on an illustrative research question using an open dataset and provide an example of a completed preregistration. Our illustrative example is accompanied by an annotated analysis report that shows readers, step-by-step, how to conduct measurement invariance tests using R and Mplus. Finally, we provide recommendations for how to decide between and use each approach and next steps for methodological research.

The benefits of latent variable modeling to develop norms for a translated version of a standardized scale

2016 ◽  
Vol 41 (6) ◽  
pp. 743-750 ◽  
Author(s):  
Hyojeong Seo ◽  
Leslie A. Shaw ◽  
Karrie A. Shogren ◽  
Kyle M. Lang ◽  
Todd D. Little
Keyword(s):  
Measurement Invariance ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Model Parameters ◽  
Confirmatory Factor Analyses ◽  
Standardization Sample ◽  
Multiple Group ◽  
The Us ◽  
Latent Means

This article demonstrates the use of structural equation modeling to develop norms for a translated version of a standardized scale, the Supports Intensity Scale – Children’s Version (SIS-C). The latent variable norming method proposed is useful when the standardization sample for a translated version is relatively small to derive norms independently but the original standardization sample is larger and more robust. Specifically, we leveraged a large, representative US standardization sample ( n = 4,015) to add power and stability to a smaller Spanish ( n = 405) standardization sample. Using a series of multiple-group mean and covariance structures confirmatory factor analyses using effects-coded scaling constraints, measurement invariance was tested across (a) Spanish only and (b) both US and Spanish age bands (5–6, 7–8, 9–10, 11–12, 13–14, and 15–16). After establishing measurement invariance across the US and Spain, tests for latent means and variance differences within age-bands were only performed for Spanish data; the latent means and variances in the US sample were freely estimated. The study findings suggest that the information in the US data stabilized the overall model parameters, and the inclusion of the US sample did not influence on the norms of the SIS-C Spanish Translation.

Measurement Invariance by Age Group for the Aging Men’s Masculinity Ideologies Inventory

2020 ◽  
Vol 28 (3) ◽  
pp. 301-317
Author(s):  
Edward H. Thompson ◽  
Britney A. Webster ◽  
Jennifer Tehan Stanley ◽  
Ronald F. Levant
Keyword(s):  
Older Adults ◽  
Measurement Invariance ◽  
Young Adulthood ◽  
Age Groups ◽  
Age Group ◽  
Factor Analyses ◽  
Confirmatory Factor Analyses ◽  
Gender Expectations ◽  
Aging Men ◽  
Confirmatory Factor

To date, work on masculinity ideologies, or the culture-based standards and norms expected of boys and men, has focused almost exclusively on younger adulthood. Given the emphases in men’s lives during middle and late adulthood vis-à-vis young adulthood, it is important to determine what norms script aging men’s lives. The Aging Men’s Masculinity Ideologies Inventory (AMMII) is a measure designed to assess the masculinities relevant to aging men. The present study investigated whether individuals ( N = 1,352) of different age groups respond to a scale measuring the gender expectations for aging men in a similar way. Multigroup confirmatory factor analyses were performed to assess the measurement invariance of the AMMII across three age groups—young adults (ages 18–29 years), established adults (ages 30–59 years), and older adults (ages 60+ years). Support for configural, metric, and partial scalar invariance was found, allowing for the comparison of means between groups.

scholarly journals Comparing Classic and Novel Approaches to Measurement Invariance

2020 ◽  
Author(s):  
Zoe Magraw-Mickelson ◽  
Alejandro Hermida Carrillo ◽  
Maas Misha'ari Weerabangsa ◽  
Chuma Kevin Owuamalam ◽  
Mario Gollwitzer
Keyword(s):  
Measurement Invariance ◽  
Cross Validation ◽  
Optimization Method ◽  
New Methods ◽  
Multiple Group ◽  
Cultural Research ◽  
Confirmatory Factor ◽  
Cross Cultural Research ◽  
Partial Invariance ◽  
Recent Extension

Measurement invariance (MI) is vital to any comparison of heterogeneous groups. With multiple-group confirmatory factor analysis (MG-CFA), which is the standard practice for testing MI, there are widely acknowledged limitations, especially with a large number of groups for which strict invariance is difficult or impossible to achieve. New methods, specifically Alignment optimization, gives increased flexibility and new opportunities to make comparisons across a large number of groups. This article compares MG-CFA with Alignment optimization for MI testing in three demonstrative studies. First, in a study of eight countries looking at eight different measures, the MG-CFA method found strict MI is problematic; only partial invariance was achievable and additionally required some of the countries to be excluded in some analysis. However, in using the Alignment optimization method there were not these drawbacks. Next, in a cross-validation reanalysis of existing data from five countries, we tested the reproducibility of conclusions from Alignment and MG-CFA analyses, finding only the results of the Alignment method reproducible. Finally, we show how to apply a recent extension of the Alignment optimization method, Alignment-within-CFA (AwC), to correlational analysis with samples from 30 countries. In a comparison of results with and without Alignment adjustments, we found some differences in conclusions drawn. This article illustrates the differences between methods as well as how to apply them to cross-cultural research.

An Adapted Measure of Teacher Self-Efficacy for Preservice Teachers: Exploring its Validity Across two Countries

2014 ◽  
Vol 28 (3) ◽  
pp. 83-92 ◽  
Author(s):  
Franziska Pfitzner-Eden ◽  
Felicitas Thiel ◽  
Jenny Horsley
Keyword(s):  
Preservice Teachers ◽  
Self Efficacy ◽  
Confirmatory Factor Analyses ◽  
3 Dimensional ◽  
Multiple Group ◽  
Three Samples ◽  
Confirmatory Factor ◽  
Teacher Self Efficacy ◽  
Dimensional Assessment ◽  
Metric Measurement

Teacher self-efficacy (TSE) is an important construct in the prediction of positive student and teacher outcomes. However, problems with its measurement have persisted, often through confounding TSE with other constructs. This research introduces an adapted TSE instrument for preservice teachers, which is closely aligned with self-efficacy experts' recommendations for measuring self-efficacy, and based on a widely used measure of TSE. We provide first evidence of construct validity for this instrument. Participants were 851 preservice teachers in three samples from Germany and New Zealand. Results of the multiple-group confirmatory factor analyses showed a uniform 3-factor solution for all samples, metric measurement invariance, and a consistent and moderate correlation between TSE and a measure of general self-efficacy across all samples. Despite limitations to this study, there is some first evidence that this measure allows for a valid 3-dimensional assessment of TSE in preservice teachers.

Measurement Invariance Analysis of the Parental Stress Index

2019 ◽  
Vol 35 (6) ◽  
pp. 771-778 ◽  
Author(s):  
Bernhard Piskernik ◽  
Barbara Supper ◽  
Lieselotte Ahnert
Keyword(s):  
Measurement Invariance ◽  
Parental Stress ◽  
Stress Index ◽  
Factor Analyses ◽  
Confirmatory Factor Analyses ◽  
Mean Values ◽  
Confirmatory Factor ◽  
Structural Invariance ◽  
Parent Domain ◽  
Structural Levels

Abstract. While parenting research continues to compare similarities and differences in mothers’ and fathers’ behaviors based on mean values on the respective dimensions, measurement invariance as a prerequisite for these comparisons has seldom been assured. The present study thus subjected the well-known Parenting Stress Index (PSI), widely used in models of family functioning, to a rigorous measurement invariance analysis based on ( N = 214) Austrian couples with children younger than 3 years of age. We evaluated configural, metric, scalar, and uniqueness invariance on item and subscale levels, and tested for structural invariance of means and variances of the PSI parent and child domain by second-order confirmatory factor analyses. As a result, only measurement differences on the scalar levels affected the factor scores, though negligibly. On the structural levels, no differences were found on the PSI child domain across parents, but on the PSI parent domain, mothers reported more stress.

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