The Impact of Categorization With Confirmatory Factor Analysis

By C. Distefano. 2002

377 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/4520ef2c2c08b6e6ded08d9e000f348a136c8f7c

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In Computer Networks and Communications

In Management Science and Operations Research

In Organizational Behavior and Human Resource Management

Citations in the corpus

Evaluating Measurement Invariance of TALIS 2013 Complex Scales: Comparison between Continuous and Categorical Multiple-Group Confirmatory Factor Analyses (2014, methodology): “, Likert-scale items, constructed responses, ordered categorical responses) is based on at least five response categories or if the data show a lack of normal distribution of the item responses (e.g., Babaku et al. 1987; Curran et al. 1996; Muthén and Kaplan 1985; DiStefano 2002).”
Why Ordinal Variables Can (Almost) Always Be Treated as Continuous Variables: Clarifying Assumptions of Robust Continuous and Ordinal Factor Analysis Estimation Methods (2020, background): “There is a diversity of methodological literature addressing this issue (Dolan, 1994; DiStefano, 2002; Lei, 2009; Flora et al., 2012; Rhemtulla et al., 2012; Sass et al., 2014; Barendse et al., 2015; Asún et al., 2016; Li, 2016; Jia andWu, 2019).”
Relative Performance of Categorical Diagonally Weighted Least Squares and Robust Maximum Likelihood Estimation (2014, background): “…in the weight matrix has been shown to result in misleading fit statistics (Dolan, 1994; Flora & Curran, 2004; Hutchinson & Olmos, 1998; Muthén & Kaplan, 1992; Potthast, 1993) and negatively biased standard errors (DiStefano, 2002; Flora & Curran, 2004; Muthén & Kaplan, 1992; Potthast, 1993).”
Assessing Goodness of Fit: Simple Rules of Thumb Simply Do Not Work (2011, methodology): “5 15 16 1⁄4 360, DiStefano (2002) showed that samples of 350 resulted in biased parameter estimates in WLS models.”
Sexual Assault on the College Campus (2012, methodology): “In line with existing research on path analysis, the appropriate remedy involved the use of a corrected test statistic—the Satorra–Bentler χ2, which produces reliable estimates using categorical data (Bentler, 2004; Byrne, 2008; also see DiStefano, 2002).”
Methodological Measurement Fruitfulness of Exploratory Structural Equation Modeling (ESEM): New Approaches to Key Substantive Issues in Motivation and Engagement (2011, methodology): “2 (Muthén & Muthén, 2008), using robust maximum likelihood estimator (MLR) with standard errors and tests of fit that are robust in relation to nonnormality of observations and the use of categorical variables when there are at least four or more response categories (e.g., Beauducel & Herzberg, 2006”
The Relationships among Attachment Style, Personality Traits, Interpersonal Competency, and Facebook Use (2012, background): “These conclusions and recommendations by researchers seem to hold true proportionally to the degree of non-normality in the data: when ordinal data begins to deviate from the ML estimator‟s normality assumption results become increasingly biased (DiStefano, 2002).”
The Use of Discrete Data in PCA: Theory, Simulations, and Applications to Socioeconomic Indices (2004, background): “The problems related to the discrete data have received a considerable attention in quantitative sociology (Olsson 1979, Bollen & Barb 1981, Johnson & Creech 1983, Babakus et al. 1987, Dolan 1994, DiStefano 2002).”
On the Performance of Maximum Likelihood Versus Means and Variance Adjusted Weighted Least Squares Estimation in CFA (2006, methodology): “WLSMV may be an interesting alternative to WLS, which requires very large samples (more than 1,000 cases) and its standard errors show large amounts of negative bias (DiStefano, 2002).”
Reliability of Summed Item Scores Using Structural Equation Modeling: An Alternative to Coefficient Alpha (2009, neutral): “Consistent with the literature (Curran, West, & Finch, 1996; DiStefano, 2002; Finney & DiStefano, 2006; Green, Akey, Fleming, Hershberger, & Marquis, 1997), the result is a lack of fit.”
A Comparison of Diagonal Weighted Least Squares Robust Estimation Techniques for Ordinal Data (2014, methodology): “First, it was hypothesized that the techniques would produce accurate parameter estimates (DiStefano, 2002; Flora & Curran, 2004); however, it was not known if one estimation process would produce lower standard errors of parameter estimates.”
Testing Measurement Invariance in Longitudinal Data with Ordered-Categorical Measures (2016, neutral): “However, this practice can lead to biased parameter estimates when there are fewer categories (e.g., Beauducel & Herzberg, 2006; DiStefano, 2002; Dolan, 1994; Rhemtulla, Brosseau-Liard, & Savalei, 2012) or when the observed indicator distributions are skewed (e.g., asymmetric threshold spacing1;…”
Strategic Performance Measurement Systems, Job‐Relevant Information, and Managerial Behavioral Responses—Role Stress and Performance (2007, methodology): “For larger samples, the full information maximum likelihood method provides efficient estimators (Kline 1998; Boomsma and Hoogland 2001; Byrne 2001; DiStefano 2002).”
Effect of the Number of Response Categories on the Reliability and Validity of Rating Scales (2008, background): “As far as factorial validity is concerned, there are several studies on how it is affected as the number of response options changes (Babakus, Ferguson, & Jöreskog, 1987; DiStefano, 2002; Dolan, 1994; Green, Akey, Fleming, Hershberger, & Marquis, 1997; Hutchinson & Olmos, 1998).”
When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. (2012, methodology): “A high rate of convergence failures, improper solutions, and outliers is an undesirable characteristic of an estimation method, both because these situations lead to uninterpretable results and also because researchers frequently interpret such outcomes as revealing poor model fit (Chen, Bollen,…”
Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares (2016, background): “9 in the majority of empirical research and simulation studies (DiStefano, 2002; Hoogland & Boomsma, 1998; Li, 2012; Paxton, Curran, Bollen, Kirby, & Chen, 2001).”