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About

Albert Satorra is a distinguished academic and Professor Emeritus of Statistics at Pompeu Fabra University (UPF) in Barcelona. His research primarily focuses on the application of statistics in behavioral and social sciences, with a particular emphasis on structural equation models (SEMs). These models, which involve latent variables and simultaneous equations, are a cornerstone of his work, and he has contributed significantly to this field through numerous publications in leading journals. Satorra's academic journey began with a strong foundation in mathematics and statistics, which later led him to psychometrics. His passion for improving methods of model evaluation and ensuring robust inferences in SEMs has driven much of his career. He has also been associated with esteemed institutions such as the Barcelona School of Economics, BI Norwegian Business School, and the University of Barcelona. His work spans various subject categories, including mathematics, psychological methods, and social sciences, as well as business and economics. Satorra's contributions have not only advanced statistical methodologies but also enriched interdisciplinary research, making him a prominent figure in his field.

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Skills

Experience

Organization
Professor Emeritus

Pompeu Fabra University Barcelona

Mar-1987 to Present

Publication

  • dott image February, 2025

Corrigenda to Satorra, A., and Bentler, P.M. (2010), “Ensuring Positiveness of the Scaled Difference Chi-Square Test Statistic,” Psychometrika, 75...

On page 245, lines 3 and 4, of the published paper, we find the following text: “Since tr{UdΓ} can be expressed as the trace of the product of two positive definite matrices, tr{UdΓ} >...

  • dott image January, 2010

Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic

A scaled difference test statistic that can be computed from standard software of structural equation models (SEM) by hand calculations was proposed in Satorra and Bentler (Psychometrika 66...

  • dott image December, 2001

A Scaled Difference Chi-Square Test Statistic for Moment Structure Analysis

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra an...

  • dott image March, 1994

Corrections to test statistics and standard errors in covariance structure analysis

developed an approach to the asymptotic behavior of covariance structure statistics that rather naturally yields corrections to the goodness-of-fit statistic of the scaling and Satterthwaite...

  • dott image November, 1991

Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: A Monte Carlo study

Research studying robustness of maximum likelihood (ML) statistics in covariance structure analysis has concluded that test statistics and standard errors are biased under severe non-normali...