His scientific interests lie mostly in Econometrics, Covariance, Psychological research, Statistics and Goodness of fit. His Econometrics study frequently draws connections to other fields, such as Sample. The study incorporates disciplines such as Exploratory factor analysis and Analisis factorial in addition to Psychological research.
His is involved in several facets of Statistics study, as is seen by his studies on Sample size determination, Simple linear regression and Scale. His Sample size determination research includes elements of Statistical hypothesis testing, Statistical power, Range, Null hypothesis and Null. His Goodness of fit course of study focuses on Analysis of covariance and Generalizability theory.
His main research concerns Econometrics, Statistics, Covariance, Goodness of fit and Multidimensional scaling. His Econometrics study combines topics in areas such as Representation, Covariance matrix, Structural equation modeling, Mathematical model and Sample. His Structural equation modeling study combines topics from a wide range of disciplines, such as Structure and Psychological research.
His research integrates issues of Analysis of covariance and Estimation theory in his study of Covariance. His work deals with themes such as Statistical hypothesis testing, Null, Null hypothesis and Statistical power, which intersect with Goodness of fit. His Principal axis factoring research integrates issues from Social psychology and Analisis factorial.
Econometrics, Statistics, Structural equation modeling, Immunology and Chronic stress are his primary areas of study. His work deals with themes such as Linear regression and Correlation, which intersect with Econometrics. His work is connected to Covariance matrix, Sample size determination, Errors-in-variables models, Goodness of fit and Sample, as a part of Statistics.
His studies in Structural equation modeling integrate themes in fields like Structure, Representation and Psychological research. His Structure research incorporates themes from Minimum description length and Covariance. With his scientific publications, his incorporates both Psychological research and Management science.
His primary scientific interests are in Econometrics, Statistics, Sample, Variety and Structural equation modeling. His Econometrics study frequently draws connections between related disciplines such as Operations research. His Statistics and Sample size determination, Sampling error, Errors-in-variables models, Sampling and Goodness of fit investigations all form part of his Statistics research activities.
His research in Sample intersects with topics in Lack-of-fit sum of squares, Linear regression, Simple linear regression, Scale and Moderation. His research integrates issues of Research design, LISREL and Psychological research in his study of Variety.
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Power analysis and determination of sample size for covariance structure modeling.
Robert C. MacCallum;Michael W. Browne;Hazuki M. Sugawara.
Psychological Methods (1996)
Evaluating the use of exploratory factor analysis in psychological research.
Leandre R. Fabrigar;Duane T. Wegener;Robert C. MacCallum;Erin J. Strahan.
Psychological Methods (1999)
Sample size in factor analysis.
Robert C. MacCallum;Keith F. Widaman;Shaobo Zhang;Sehee Hong.
Psychological Methods (1999)
On the Practice of Dichotomization of Quantitative Variables
Robert C. MacCallum;Shaobo Zhang;Kristopher J. Preacher;Derek D. Rucker.
Psychological Methods (2002)
Applications of Structural Equation Modeling in Psychological Research
Robert C. MacCallum;James T. Austin.
Annual Review of Psychology (2000)
THE APPLICATION OF EXPLORATORY FACTOR ANALYSIS IN APPLIED PSYCHOLOGY: A CRITICAL REVIEW AND ANALYSIS
J. Kevin Ford;Robert C. MacCALLUM;Marianne Tait.
(1986)
Model modifications in covariance structure analysis: the problem of capitalization on chance.
Robert C. MacCallum;Mary Roznowski;Lawrence B. Necowitz.
Psychological Bulletin (1992)
Chronic stress and age-related increases in the proinflammatory cytokine IL-6.
Janice K. Kiecolt-Glaser;Kristopher J. Preacher;Robert C. MacCallum;Cathie Atkinson.
Proceedings of the National Academy of Sciences of the United States of America (2003)
The use of causal indicators in covariance structure models: some practical issues.
Robert C. MacCallum;Michael W. Browne.
Psychological Bulletin (1993)
Sample size in factor analysis: The role of model error
Robert C. MacCallum;Keith F. Widaman;Kristopher J. Preacher;Sehee Hong.
Multivariate Behavioral Research (2001)
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