Roger Millsap's Home Page

This website contains links to various pages related to my teaching, research, publications, and personal interests.

Professional Stuff

I am a faculty member in the Department of Psychology at Arizona State University in Tempe, Arizona. My research focus is in quantitative psychology, which means that I develop and/or apply statistical and mathematical methods to help resolve research questions in psychology. I am currently teaching coursework in psychological measurement and statistical methods at the undergraduate and doctoral levels as an active member of the Quantitative Psychology Doctoral Program in the Department. I am also working as the Co-Director of the Methodology Core group at the Prevention Research Center on campus. This Center conducts research on programs to help children and families cope with stressful experiences, with a focus on parental divorce, poverty, bereavement, and parental job loss.

For a general description of the field of quantitative psychology, a list of doctoral programs, how to get into the field, and so forth, go here. If you want to find out more about what topics or questions are addressed in this field, Albert Maydeu-Olivares and I edited a book that surveys current methods in the field of quantitative psychology.

My publications are listed here. I now serve as the Editor of Psychometrika, the journal of the Psychometric Society. Psychometrika is a journal that publishes papers on all aspects of quantitative psychology. I am on the Editorial Boards of three other journals, Multivariate Behavioral Research, Applied Psychological Measurement, and Structural Equation Modeling.

I am active in several professional organizations:

Research Interests

My central research interest at present concerns methods for detecting bias in psychological measures. The bias of interest concerns systematic errors of measurement that are associated with group membership, with groups usually defined demographically (although other definitions of "group", such as randomized groups in experiments, are potentially interesting as well). Technically, we say that a measure is "biased" if systematic group differences in observed scores exist among individuals who are identical on the attribute(s) being measured. This latter requirement is the difficult part, as there is ordinarily no sure way to completely "match" individuals on attributes that cannot be directly measured. Nearly all psychological attributes fall in this category; we cannot directly measure emotions, attitudes, or abilities. The challenge of this research area is to develop methods for studying bias in the absence of simple, direct measures on which to match individuals from different groups.

Related to the above, I have an ongoing interest in statistical methods associated with latent variable models , especially factor analysis and item response theory. Simply put, latent variable models attempt to model observed states or conditions as outcomes of unobserved processes or conditions. A latent variable model imposes some structure in the relationship between the observed and unobserved variables, but the structure is not generally fully amenable to empirical tests. Factor analysis is one of the older models (see FA100 for a recent conference on 100 years of factor analysis); item response theory is a bit younger, but hardly new. Aside from applications of latent variable models to the measurement bias problem, I have done work in longitudinal models, factor models for multitrait-multimethod data(MTMM), and identification problems in latent variable models.

For a list of resources related to the above research interests, see the following:

Current Teaching

I am currently teaching several courses on a rotating basis:

Personal Interests

Last Updated April 17, 2011
Web Page by Roger E. Millsap
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