Victoria V. Savalei, Ph.D.
Affiliations: | 2007 | University of California, Los Angeles, Los Angeles, CA |
Area:
Personality, drug abuse, psychometrics, structural equation modeling, factor analysis, reliability theoryGoogle:
"Victoria Savalei"Mean distance: 23.36 (cluster 20) | S | N | B | C | P |
Parents
Sign in to add mentorPeter M. Bentler | grad student | 2007 | UCLA | |
(Studies in asymptotic robustness.) |
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Publications
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Chen L, Savalei V, Rhemtulla M. (2023) Pay Attention to the Ignorable Missing Data Mechanisms! An Exploration of Their Impact on the Efficiency of Regression Coefficients. Multivariate Behavioral Research. 1-26 |
Savalei V, Brace JC, Fouladi RT. (2023) We need to change how we compute RMSEA for nested model comparisons in structural equation modeling. Psychological Methods |
Zhang X, Savalei V. (2022) New computations for RMSEA and CFI following FIML and TS estimation with missing data. Psychological Methods |
Chen L, Savalei V. (2021) Three Sample Estimates of Fraction of Missing Information From Full Information Maximum Likelihood. Frontiers in Psychology. 12: 667802 |
Dunn EW, Chen L, Proulx JDE, et al. (2020) Can Researchers' Personal Characteristics Shape Their Statistical Inferences? Personality & Social Psychology Bulletin. 146167220950522 |
Chen L, Savalei V, Rhemtulla M. (2020) Two-stage maximum likelihood approach for item-level missing data in regression. Behavior Research Methods |
Savalei V. (2020) Improving Fit Indices in Structural Equation Modeling with Categorical Data. Multivariate Behavioral Research. 1-18 |
Zhang X, Savalei V. (2019) Examining the effect of missing data on RMSEA and CFI under normal theory full-information maximum likelihood Structural Equation Modeling: a Multidisciplinary Journal. 27: 219-239 |
Benjamin DJ, Berger JO, Johannesson M, et al. (2018) Redefine statistical significance. Nature Human Behaviour. 2: 6-10 |
Savalei V. (2018) A comparison of several approaches for controlling measurement error in small samples. Psychological Methods. 24: 352-370 |