Supplemental Material for Permutation Randomization Methods for Testing Measurement Equivalence and Detecting Differential Item Functioning in Multiple-Group Confirmatory Factor Analysis

2017 ◽  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Differential Item Functioning ◽  
Measurement Equivalence ◽  
Multiple Group ◽  
Item Functioning ◽  
Confirmatory Factor

Confirmatory Factor Analysis, Internal Consistency, Gender Differential Item Functioning and Discriminant Validity of the Fear of COVID-5 Scale Amidst Emerging Adult University Students in Mexico

2021 ◽  
pp. 003022282110162
Author(s):  
Adalberto Campo-Arias ◽  
Andrés Felipe Tirado-Otálvaro ◽  
Isabel Álvarez-Solorza ◽  
Carlos Arturo Cassiani-Miranda
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Differential Item Functioning ◽  
Internal Consistency ◽  
Discriminant Validity ◽  
Emerging Adult ◽  
One Dimension ◽  
Item Functioning ◽  
Confirmatory Factor ◽  
Gender Differential

The study aimed to perform confirmatory factor analysis, internal consistency, gender differential item functioning, and discriminant validity of the Fear of COVID-5 Scale in emerging adult students of a university in Mexico. Confirmatory factor analysis, internal consistency (Cronbach's alpha and McDonald's omega), and gender differential item functioning were estimated (Kendall tau b correlation). The Fear of COVID-5 Scale showed a one-dimension structure (RMSEA = 0.07, CFI = 0.98, TLI = 0.96, and SRMR = 0.02), with high internal consistency (Cronbach's alpha of 0.78 and McDonald's omega of 0.81), non-gender differential item functioning (Kendall tau b between 0.07 and 0.10), and significant discriminant validity (Higher scores for fear of COVID-19 were observed in high clinical anxiety levels). In conclusion, the Fear of COVID-5 Scale presents a clear one-dimension structure similar to a previous study.

scholarly journals Differential Item Functioning Effect Size From the Multigroup Confirmatory Factor Analysis for a Meta-Analysis: A Simulation Study

2020 ◽  
pp. 001316442092588
Author(s):  
Sung Eun Park ◽  
Soyeon Ahn ◽  
Cengiz Zopluoglu
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Differential Item Functioning ◽  
Effect Size ◽  
Tetrachoric Correlation ◽  
Correlation Matrices ◽  
New Approach ◽  
Item Functioning ◽  
Confirmatory Factor ◽  
Multigroup Confirmatory Factor Analysis

This study presents a new approach to synthesizing differential item functioning (DIF) effect size: First, using correlation matrices from each study, we perform a multigroup confirmatory factor analysis (MGCFA) that examines measurement invariance of a test item between two subgroups (i.e., focal and reference groups). Then we synthesize, across the studies, the differences in the estimated factor loadings between the two subgroups, resulting in a meta-analytic summary of the MGCFA effect sizes (MGCFA-ES). The performance of this new approach was examined using a Monte Carlo simulation, where we created 108 conditions by four factors: (1) three levels of item difficulty, (2) four magnitudes of DIF, (3) three levels of sample size, and (4) three types of correlation matrix (tetrachoric, adjusted Pearson, and Pearson). Results indicate that when MGCFA is fitted to tetrachoric correlation matrices, the meta-analytic summary of the MGCFA-ES performed best in terms of bias and mean square error values, 95% confidence interval coverages, empirical standard errors, Type I error rates, and statistical power; and reasonably well with adjusted Pearson correlation matrices. In addition, when tetrachoric correlation matrices are used, a meta-analytic summary of the MGCFA-ES performed well, particularly, under the condition that a high difficulty item with a large DIF was administered to a large sample size. Our result offers an option for synthesizing the magnitude of DIF on a flagged item across studies in practice.

scholarly journals Multiple Group Confirmatory Factor Analysis of the DASS-21 Depression and Anxiety Scales: How Do They Perform in a Cancer Sample?

2017 ◽  
Vol 121 (3) ◽  
pp. 548-565 ◽  
Author(s):  
Rina S. Fox ◽  
Teresa A. Lillis ◽  
James Gerhart ◽  
Michael Hoerger ◽  
Paul Duberstein
Keyword(s):  
Factor Analysis ◽  
Standard Deviation ◽  
Confirmatory Factor Analysis ◽  
Psychometric Properties ◽  
Cancer Patients ◽  
Internal Consistency Reliability ◽  
Total Sample ◽  
Depression And Anxiety ◽  
Multiple Group ◽  
Confirmatory Factor

The DASS-21 is a public domain instrument that is commonly used to evaluate depression and anxiety in psychiatric and community populations; however, the factor structure of the measure has not previously been examined in oncologic settings. Given that the psychometric properties of measures of distress may be compromised in the context of symptoms related to cancer and its treatment, the present study evaluated the psychometric properties of the DASS-21 Depression and Anxiety scales in cancer patients ( n = 376) as compared to noncancer control participants ( n = 207). Cancer patients ranged in age from 21 to 84 years (mean = 58.3, standard deviation = 10.4) and noncancer control participants ranged in age from 18 to 81 years (mean = 45.0, standard deviation = 11.7). Multiple group confirmatory factor analysis supported the structural invariance of the DASS-21 Depression and Anxiety scales across groups; the factor variance/covariance invariance model was the best fit to the data. Cronbach’s coefficient alpha values demonstrated acceptable internal consistency reliability across the total sample as well as within subgroups of cancer patients and noncancer control participants. Expected relationships of DASS-21 Depression and Anxiety scale scores to measures of suicidal ideation, quality of life, self-rated health, and depressed mood supported construct validity. These results support the psychometric properties of the DASS-21 Depression and Anxiety scales when measuring psychological distress in cancer patients.

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