Nick Williams

I’m a biostatistician and research software engineer who focuses on the development (and application) of nonparametric methods with the goal of answering causal questions. My most recent substantive work has been in the area of substance abuse epidemiology.

I’m a Ph.D. student in Biostatistics at the University of California, Berkeley, working with Laura Balzer. I also work part-time in the Department of Epidemiology at Columbia University with Kara Rudolph, and frequently collaborate with Iván Díaz at NYU.

I received a B.A. in Psychology from the University of Colorado, Boulder in 2017 and an M.P.H in Biostatistics from Columbia University in 2019.

Software

lmtp Non-parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies
mlr3superlearner Super learner fitting and prediction using mlr3
crumble General targeted machine learning for modern causal mediation analysis
ife S7 class (with Ops) for influence function based estimands
adjrct Doubly-Robust and Efficient Estimators for Survival and Ordinal Outcomes in RCTs Without Proportional Hazards or Odds Assumptions
codebreak A light weight codebook framework for R

Nick Williams

I’m a biostatistician and research software engineer who focuses on the development (and application) of nonparametric methods with the goal of answering causal questions. My most recent substantive work has been in the area of substance abuse epidemiology.

I’m a Ph.D. student in Biostatistics at the University of California, Berkeley, working with Laura Balzer. I also work part-time in the Department of Epidemiology at Columbia University with Kara Rudolph, and frequently collaborate with Iván Díaz at NYU.

I received a B.A. in Psychology from the University of Colorado, Boulder in 2017 and an M.P.H in Biostatistics from Columbia University in 2019.

Software

lmtp Non-parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies
mlr3superlearner Super learner fitting and prediction using mlr3
crumble General targeted machine learning for modern causal mediation analysis
ife S7 class (with Ops) for influence function based estimands
adjrct Doubly-Robust and Efficient Estimators for Survival and Ordinal Outcomes in RCTs Without Proportional Hazards or Odds Assumptions
codebreak A light weight codebook framework for R