Research Interests
Broadly speaking, my research involves the development, improvement, and evaluation of quantitative methods, especially as they relate to statistical issues in applied research. More specifically, my research focuses on the design of research studies and longitudinal data analysis. Additionally, I apply a variety of methods collaboratively with others in mutually beneficial collaborations in a variety of 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 area of research is research design. This is especially influenced by my work on effect sizes, confidence intervals, and sample size planning (particularly from the accuracy in parameter estimation approach).
Primary Area of Research-Specific
The specific area within the design of research studies is sample size planning. In particular, I focus on the interplay between sample size planning for statistical power (i.e., power analysis) and sample size planning for accuracy in parameter estimation (AIPE). Accuracy in parameter estimation in this sense is operationalized by obtaining confidence intervals that are sufficiently narrow. A narrow confidence interval provides more information about the population parameter of interest than does a wide interval or a null hypothesis significance test, as the interval reveals whether or not some null value (generally zero) can be rejected and it defines the range of plausible values for the parameter at some specified level of confidence. All of this being said, some research questions are best addressed from a power analytic perspective where sample size should be planned so that a false null hypothesis can be rejected with a specified level of statistical power. Realizing that AIPE is appropriate in some situations and power analysis in others, I work on sample size planning from both perspectives. Much of this line of research involves unstandardized and standardized effect sizes, their corresponding confidence intervals, and finding the optimal effect size to represent the research questions of interest.
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 develop, improve, and evaluate quantitative methods so that substantive questions can be addressed with methodologically sound techniques and procedures.
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.