Research Interests

My research program has been about making improvements to the scientific methods used in the social and behavioral sciences, in an effort to produce a more accurate and cumulative literature. My research evaluates, improves, and develops research methods of a statistical and measurement nature for the fields that use psychological, behavioral, or social data (e.g., psychology, sociology, management, marketing, education, behavioral medicine). My research focuses on the methods of designing studies and analyzing data for the social and behavioral sciences, which are arguably the most foundational aspects of an empirical science. Without an appropriate design or if impoverished analysis methods are used, the value of the research is questionable and leads to a literature filled with suspect conclusions, thereby limiting the effectiveness of what should be a living and cumulative literature. My efforts in this space have helped to reduce various methodological shortcomings. A general way of saying what I do is work on methods of designing studies and analyzing data. Additionally, I apply a variety of methods collaboratively with others in mutually beneficial collaborations in a variety of domain specific areas, where I can develop needed or apply existing methods to address interesting and important real-world problems. As Tukey pointed out, “the best thing about being a statistician is that you get to play in everyone’s backyard!”

Primary Area of Research-General

My primary research is on the interrelated topics of effect sizes, confidence intervals, and sample size planning. Sample size planning is one of the most important aspects of designing an empirical study, because using a sample size that is much too large for the particular research goal potentially puts more participants than necessary at risk, delays dissemination of findings, and is not an effective use of limited resources. Using a sample size that is too small for the goal, however, lowers the likelihood that the research goal can be addressed with enough confidence to add to the literature or ensure that the participants’ and researcher’s time was used wisely. The design stage of an empirical study is where researchers can have arguably the biggest impact on success, and where potential methodological shortcomings can be prevented (instead of attempting to fix later).

General Research Interests

My interests span widely across the field of research methodology – I just do not have enough time to work on all of them with the same intensity as I do for research design! Some of the other topics that I work on are longitudinal data analysis, mixed-effects models/multilevel models, mediation models, general latent variable models, finite mixture modeling, statistical classification and statistical discrimination, the bootstrap technique, the proper design and implementation of Monte Carlo simulation studies, and various psychometric issues. The methods that I am interested in need not be conceptualized as being mutually exclusive, as many times the methods are combined to form a unified approach to designing research studies and analyzing data. Further, much of what I do involves statistical computing and R is involved in much of my work. An interest related to all others is the cross-fertilization of methods from a variety of fields. Methodological developments in one field are often not well known in other fields, even though both fields may ask questions that can be addressed with the same or similar methods. By working in a variety of fields in an interdisciplinary fashion and borrowing methods from each, better methodological practice can be implemented in each field, which is beneficial all around.

General Research Interests

My interests span widely across the field of research methodology – I just do not have enough time to work on all of them with the same intensity as I do for research design! Some of the other topics that I work on are longitudinal data analysis, general latent variable models, finite mixture modeling, statistical classification and statistical discrimination, the bootstrap technique, the proper design and implementation of Monte Carlo simulation studies, and various psychometric issues. The methods that I am interested in need not be conceptualized as being mutually exclusive, as many times the methods are combined to form a unified approach to designing research studies and analyzing data. An interest related to all others is the cross-fertilization of methods from a variety of fields. Methodological developments in one field are often not well known in other fields, even though both fields ask questions that can be addressed with the same or similar methods. By working in a variety of fields and borrowing methods from each, better methodological practice can be implemented in each field and all fields benefit.

Overarching Research Goal

The overall goal of my research is to evaluate, improve, and develop research methods of a statistical and measurement nature for fields that use psychological, behavioral, or social data (e.g., management, marketing, education, behavioral medicine, information technology, sociology, psychology) so that substantive questions can be addressed with quality methods.

Collaboration

I have been a consultant on many research projects ranging from small scale narrowly focused studies to large scale government funded projects. Feel free to contact me if you think my research could be beneficial to your research. Depending on many factors, I may or may not be able to provide assistance and/or collaborate.

Get Involved
Graduate students interested in getting involved with methodological should feel free to contact me.