Confirmatory Factor Analysis for Applied Research

By Phil Wood. 2008

2,383 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/c7a160daeb5048dd21d4e1c3a855c82b4c6b8559

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In Computer Networks and Communications

Citations in the corpus

Analysis of Multivariate Social Science Data (2nd ed.) (2011, neutral): “, Hair, Black, Babin, & Anderson, 2009; Lattin, Carroll, & Green, 2003; Manly, 2005; Tabachnick & Fidell, 2006; Warner, 2008). Among these, Analysis of Multivariate Social Science Data is somewhat of an outlier in terms of the methods that the authors cover. The book is characterized by a heavy late”
Jamovi: An Easy to Use Statistical Software for the Social Scientists (2019, methodology): “Confirmatory Factor Analysis CFA is used to determine whether or not the predicted structure is present in the dataset at hand in cases where a strong a priori regarding the structure is apparent to the researcher (Brown, 2015).”
The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence (2022, positive): “This showed (Brown, 2015).”
Coefficient Alpha: Interpret With Caution (2013, neutral): “Brown (2006) refers to three different groups of indices depending on the information they provide and advises researchers to use at least one from each group. For this reason, the researcher used the Standardised Root Mean Square Residual (SRMR) from the Absolute fit group of indices, the Root Mean”
The Gaussian Graphical Model in Cross-Sectional and Time-Series Data (2016, background): “Then, (4) reduces to the well-known factor model (Brown, 2014).”
Validation and psychometric properties of a short version of Young's Internet Addiction Test (2013, neutral): “Out of the three proposed categories of fit indices to verify the model fit (Brown, 2006; Schermelleh-Engel, Moosbrugger, & Müller, 2003), the following fit indices were calculated: 1) absolute fitindices like the 2 -index and the standardized root mean square residual (SRMR), 2) parsimony…”
Author Guidelines for Reporting Scale Development and Validation Results in the Journal of the Society for Social Work and Research (2010, neutral): “80 may indicate poor discriminant validity (Brown, 2006).”
How Sound Is NSSE?: Investigating the Psychometric Properties of NSSE at a Public, Research-Extensive Institution (2011, methodology): “…suited (Byrne, 2006; Hancock & Mueller, 2009). coNStRuct vaLidity of NSSe The principle of construct validity asks for evidence of the extent to which items or scales measure the construct they purport to represent (Bollen, 1989; Brown, 2006; Byrne, 2006; Cronbach & Meehl, 1953; Kline, 2005).”
The Physical Appearance Perfectionism Scale: Development and Preliminary Validation (2011, methodology): “001), we used the robust maximum likelihood estimator (MLM) to compute fit indices that are robust to violations of multivariate normality (Brown, 2006).”
Testing Factorial Invariance in Multilevel Data: A Monte Carlo Study (2012, neutral): “E-mail: omkwok@neo.tamu.edu 250 Although the importance of measurement invariance has long been advocated (e.g., Borsboom, 2006; Fan & Sivo, 2009; Meade & Bauer, 2007; Meredith & Teresi, 2006; Millsap & Kwok, 2004; Widaman & Reise, 1997; Yoon & Millsap, 2007), the issues of measurement invariance…”
The generality-specificity of creativity: Exploring the structure of creative potential with EPoC (2016, methodology): “This procedure initially developed for use within the exploratory factor analysis framework generalizes to CFA in a straightforward manner(Brown, 2006), and is used to calculate the contribution of lower and higher-order factors to the prediction of observed measures.”
Exploratory Factor Analysis (2018, positive): “If > 0.85, the is a multicollinearity between the factors, thus the factors are not distinct from each other, thus can be combined (change number of fixed factors) (Brown, 2006).”
When Preference Is Not Satisfied but the Individual Is (2014, positive): “Modeling this method variance in an a priori manner is not only justifiable but necessary (Brown, 2006).”
An Examination of the Latent Structure of the Difficulties in Emotion Regulation Scale (2012, positive): “A higher-order CFA seeks to investigate whether a general factor accounts for the interrelations among the lower-order latent factors of a scale (Brown 2006).”
Predicting entrepreneurial behaviour: a test of the theory of planned behaviour (2013, positive): “…generates weighted-least-square parameter estimates employing a diagonal weight matrix with robust SEs and mean and variance adjusted chi-square test statistics (Muthén and Muthén, 1998–2010), which are suitable for models with categorical dependent variables (Muthén, 1983; Brown, 2006).”