December 12, 2018

Final Exam

  • Will be available at 9pm.

  • Due by end of day December 17th.

  • You may use your book and course materials.

  • There are two parts:
    1. Part one multiple choice questions and short answer questions.
    2. Part two has a small data set to analyze with R, then answer some interpretation questions.

  • Put your answers in the Rmarkdown file and submit the PDF file. Please do not post your answers online!

Presentations

  • Juliann McEachern (6.27)
  • Jithendra Seneviratne (8.15 / 8.17) slides
  • Anthony Pagan (8.1) slides
  • Jack Russo (8.3)
  • Zachary Herold

My Work

My research interest is in propensity score methods. Propensity score analysis (PSA) is a quasi-experimental design used to estimate causality from observational studies. It is generally conducted in two phases:

  1. Estimate propensity scores (i.e. probability of being in the treatment) using the observed covariates.
    1. Check balance
    2. Re-estimate propensity scores
  2. Estimate effect sizes using typical group differences (e.g. t-tests)

Areas I have worked on:

  • Multilevel PSA (see multilevelPSA R package)
  • Matching with non-binary treatments (see TriMatch R package)
  • Bootstrapping PSA (see PSAboot R package)

Thank You