Daniel Baer

Background

About Daniel Baer

I am a biostatistician with expertise in Bayesian statistical modeling, especially in the areas of longitudinal data analysis and variable selection. I am passionate about using my skills as a biostatistician to inform decision making in the biomedical sciences in a rigorous and reproducible manner. I have a wealth of experience generating exploratory data analyses, conducting simulation-based study design analyses, developing and evaluating novel statistical models, and analyzing biomedical datasets. I am highly skilled in R programming and performing sophisticated data wrangling and visualization procedures, especially with the tidyverse suite of R packages. I am also highly skilled in developing and implementing Markov chain Monte Carlo (MCMC) algorithms in R in order to estimate biomedical parameters of interest from Bayesian models. I ensure that my work is rigorous and reproducible using tools such as Github and R Markdown.