sdshwetadixit's Stars
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
CausalInference/bariatric
Analytic code for bariatric analysis including synthetic data
qkrcks0218/UDiDEpi
qkrcks0218/ClusterEff
avehtari/ROS-Examples
Regression and other stories R examples
stan-dev/projpred
Projection predictive variable selection
katehu/COVID-PM-STZINB
katehu/addhazard
Fitting the additive hazards model to case-cohort data in R
ehsanx/into2ML
A very basic introduction to machine learning.
ehsanx/EpiMethods
A unique open textbook to teach the nuances of applying advanced epidemiological methods using real data.
mrc-ide/priority-pathogens
https://mrc-ide.github.io/priority-pathogens/
mrc-ide/monty
mrc-ide/malariasimulation
The malaria model
ImperialCollegeLondon/ReCoDE_IDMS
sejdemyr/ecls
Processing data from the Early Childhood Longitudinal Study (ECLS)
asjadnaqvi/DiD
Keeping track of what is going on with the latest DiD innovations.
pymc-devs/pymc
Bayesian Modeling and Probabilistic Programming in Python
pymc-labs/pymc-marketing
Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.
ccubc/PSmatching
do the green drivers also drive longer? --- causal identification using the propensity score approach
jbryer/PSAgraphics
Propensity Score Analysis Graphics
kaz-yos/multinomial-ps-trimming
Multinomial Propensity Score Trimming (Am J Epidemiol 2018)
ehsanx/SARGC-TIMethods
TI Methods Speaker Series in collaboration with the Student and Recent Graduate Committee (SARGC) of the Statistical Society of Canada.
ehsanx/TMLEworkshop
Targeted maximum likelihood estimation (TMLE) enables the integration of machine learning approaches in comparative effectiveness studies. It is a doubly robust method, making use of both the outcome model and propensity score model to generate an unbiased estimate as long as at least one of the models is correctly specified.
jbryer/psa
Propensity Score Analysis with R
jbryer/PSAboot
Bootstrapping for Propensity Score Analysis
nhejazi/haldensify
:package: R/haldensify: Highly Adaptive Lasso Conditional Density Estimation
Minyus/causallift
CausalLift: Python package for causality-based Uplift Modeling in real-world business
causaltext/causal-text-papers
Curated research at the intersection of causal inference and natural language processing.
dixitamol/insuranceSalePredictor
The feature of interest is whether or not a customer buys a caravan insurance, based on socio-demographic factors and ownership of other insurance policies; and to build profile of a typical customer.
NSAPH-Software/CausalGPS
Matching on generalized propensity scores with continuous exposures