Causal¶
Documentation for each of the causal inference methods implemented in zEpid
Causal Diagrams¶
DirectedAcyclicGraph (exposure, outcome) |
Inverse Probability Weights¶
IPTW (df, treatment, outcome[, weights, …]) |
Calculates inverse probability of treatment weights. |
StochasticIPTW (df, treatment, outcome[, weights]) |
Calculates the IPTW estimate for stochastic treatment plans. |
IPMW (df, missing_variable[, stabilized, …]) |
Calculates inverse probability of missing weights. |
IPCW (df, idvar, time, event[, flat_df, enter]) |
Calculates inverse probability of censoring weights. |
Time-Fixed Treatment G-Formula¶
TimeFixedGFormula (df, exposure, outcome[, …]) |
G-formula for time-fixed exposure and single endpoint, also referred to as the g-computation algorithm formula. |
SurvivalGFormula (df, idvar, exposure, …[, …]) |
G-formula for time-to-event data where the exposure is fixed at baseline. |
Time-Varying Treatment G-Formula¶
MonteCarloGFormula (df, idvar, exposure, …) |
Time-varying implementation of the Monte Carlo g-formula. |
IterativeCondGFormula (df, exposures, outcomes) |
Iterative conditional g-formula estimator. |
Augmented Inverse Probability Weights¶
AIPTW (df, exposure, outcome[, weights, alpha]) |
Augmented inverse probability of treatment weight estimator. |
SingleCrossfitAIPTW (df, exposure, outcome[, …]) |
Implementation of the Augmented Inverse Probability Weighting estimator with a cross-fit procedure. |
DoubleCrossfitAIPTW (df, exposure, outcome[, …]) |
Implementation of the augmented inverse probability weighted estimator with a double cross-fit procedure. |
Targeted Maximum Likelihood Estimator¶
TMLE (df, exposure, outcome[, alpha, …]) |
Implementation of target maximum likelihood estimator. |
StochasticTMLE (df, exposure, outcome[, …]) |
Implementation of target maximum likelihood estimator for stochastic treatment plans. |
SingleCrossfitTMLE (df, exposure, outcome[, …]) |
Implementation of the Targeted Maximum Likelihood Estimator with a single cross-fit procedure. |
DoubleCrossfitTMLE (df, exposure, outcome[, …]) |
Implementation of the Targeted Maximum Likelihood Estimator with a double cross-fit procedure. |
G-estimation of SNM¶
GEstimationSNM (df, exposure, outcome[, weights]) |
G-estimation for structural nested mean models. |
Generalizability / Transportability¶
IPSW (df, exposure, outcome, selection[, …]) |
Calculate inverse probability of sampling weights through logistic regression. |
GTransportFormula (df, exposure, outcome, …) |
Calculate the g-transport-formula using a observed study sample and a sample from the target population. |
AIPSW (df, exposure, outcome, selection[, …]) |
Doubly robust estimator for generalizability. |