LSAT Test Prep: I use a data-driven approach where I gather data from students' practice tests and then analyze those data to identify the most important areas for improvement. This includes analyzing students' accuracy and speed across different categories of LSAT questions (Assumptions, Deductions and Inference, etc.) and different levels of question difficulty. From the results, I develop an individualized plan for a given student that targets the areas for improvement that will most efficiently yield improved test performance. My students often improve 10-15 points in around 3-4 weeks.
Statistics and Research Methods Tutoring and Consultation: My PhD training heavily emphasized research and statistical coursework, and since then I have worked for about 10 years in academia with a major focus on research. I have published over 15 data-analytic peer-reviewed research papers and received a $750,000 K99/R00 research grant from NIH. I have also frequently taught undergraduate- and graduate-level courses on statistics and research methods, including training students in SPSS and other software packages. My data-analytic areas of expertise include longitudinal data analysis with latent and multilevel growth modeling, path analysis and cross-lag panel modeling with structural equation models, mediation analysis, developmental-cascade modeling, latent-class and latent-transition-analysis mixture modeling, measurement modeling including exploratory and confirmatory factor analysis and moderated nonlinear factor analyses for integrative data analysis, and Monte Carlo simulations for statistical-power estimation. I am proficient in conducting data analysis with a number of statistical software packages including Excel, SPSS, Mplus, SAS, and R.
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