ehsanx Goto Github PK

2022_acic_data_challenge

adherence_lrccppt

Code for the paper titled 'Adjusting for adherence in randomized trials when adherence is measured as a continuous variable: an application to the Lipid Research Clinics Coronary Primary Prevention Trial'

aipw

R package: Augmented Inverse Probability Weighted (AIPW) estimation for average causal effect

appliedpredictivemodeling

:exclamation: This is a read-only mirror of the CRAN R package repository. AppliedPredictiveModeling — Functions and Data Sets for 'Applied Predictive Modeling'. Homepage: http://appliedpredictivemodeling.com/

apsals

APSALS ltmle application code

arch

Repo for the ARCH project

auc_r2

autoencoderps

bartcause

Causal Inference using Bayesian Additive Regression Trees

bda_course_aalto

Bayesian Data Analysis course at Aalto

bigsurvsgd

Big survival data analysis using stochastic gradient descent

blog-decision-tree-fundamental

bwsnooping

Critical values adjusted for bandwidth snooping

causal

Causal Inference using R. Examples are from the book Causal Inference (Chapman & Hall/CRC, 2012) by Miguel Hernán and Jamie Robins. Complete contributor/reviewer list is updated in http://www.hsph.harvard.edu/faculty/miguel-hernan/causal-inference-book/

causal-inference-methods-for-pragmatic-trials

Developing and Evaluating Causal Inference Methods for Pragmatic Trials

causal_sim

Simulating longitudinal data from marginal structural models using the additive hazards model

causalcalibration

causalinferenceintro

Guest lecture for SPPH 500

causalsurvivalanalysisworkshop

cbal

Covariate Balancing Weights with Bregman Distances

censoringdl

choosing-epidemiological-journals

ci_covsel

classimb_calibration

clustmixtype

:exclamation: This is a read-only mirror of the CRAN R package repository. clustMixType — k-Prototypes Clustering for Mixed Variable-Type Data

cmaverse

A suite of functions for reproducible causal mediation analyses

code-machine-learning-comparison

confounder

confoundercontrol

Code for paper on automating propensity scores. Comparing high-dimensional confounder control methods for rapid cohort studies from electronic health records

course-content

NMA Computational Neuroscience course