Streamlined Estimation of Survival for Static, Dynamic and Stochastic Treatment and Monitoring Regimes

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Documentation for package ‘stremr’ version 0.4

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stremr-package Estimate the Survival of Intervention on Exposures and MONITORing Process for Right Censored Longitudinal Data.
BinaryOutcomeModel R6 class for fitting and making predictions for a single binary outcome regression model P(B | PredVars)
BinomialGLM R6 class for storing the design matrix and the binary outcome for a single GLM (logistic) regression
CategorModel R6 class for fitting and predicting joint probability for a univariate categorical summary A[j]
ContinModel R6 class for fitting and predicting joint probability for a univariate continuous summary A[j]
DataStorageClass R6 class for storing, managing, subsetting and manipulating the input data.
defineIntervedTRT Define counterfactual dynamic treatment
defineMONITORvars Helper routine to define the monitoring indicator and time since last visit
define_single_regression Define regression models
fitIterTMLE Iterative TMLE wrapper for 'fitSeqGcomp'
fitPropensity Define and fit propensity score models.
fitSeqGcomp Fit sequential GCOMP and TMLE for survival
fitTMLE TMLE wrapper for 'fitSeqGcomp'
GenericModel Generic R6 class for modeling (fitting and predicting) P(A=a|W=w) where A can be a multivariate (A[1], ..., A[k]) and each A[i] can be binary, categorical or continous
getIPWeights Inverse Probability Weights.
get_FUPtimes Follow-up times by regimen
get_MSM_RDs Risk Difference Estimates and SEs for IPW-MSM
get_TMLE_RDs Risk Difference Estimates and SEs for a list of TMLE outputs
get_wtsummary IP-Weights Summary Tables
importData Import data, define various nodes, define dummies for factor columns and define OData R6 object
make_report_rmd Generate report(s) with modeling stats and survival estimates using pandoc.
OdataCatCENS An example of a dataset in long format with categorical censoring variable.
OdataNoCENS An example of a dataset in long format with random monitoring and no right censoring.
OdatDT_10K An example of a dataset in long format with random monitoring process and no right censoring.
openFileInOS Open file
pander.H2OBinomialMetrics Pander method for H2OBinomialMetrics class
pander.H2ORegressionMetrics Pander method for H2ORegressionMetrics class
print.GLMmodel S3 methods for printing model fit summary for glmfit class object
print.H2Oensemblemodel S3 methods for printing model fit summary for H2Omodel class object
print.H2Omodel S3 methods for printing model fit summary for H2Omodel class object
print_stremr_opts Print Current Option Settings for 'stremr'
QlearnModel R6 Class for Q-Learning
RegressionClass R6 class that defines regression models evaluating P(sA|sW), for summary measures (sW,sA)
set_all_stremr_options Setting 'stremr' Options
StratifiedModel R6 class for fitting and predicting with several stratified models for a single outcome variable (conditional on some covariate values)
stremr Estimate Survival with Interventions on Exposure and MONITORing Process in Right Censored Longitudinal Data.
stremrOptions Querying/setting a single 'stremr' option
summary.GLMmodel S3 methods for getting model fit summary for glmfit class object
summary.H2Oensemblemodel S3 methods for getting model fit summary for H2Oensemblemodel class object
summary.H2Omodel S3 methods for getting model fit summary for H2Omodel class object
survDirectIPW Direct (bounded) IPW estimator of discrete survival function.
survMSM Estimate Survival with a particular MSM for the survival-hazard function using previously fitted weights.
survNPMSM Non-parametric (saturated) MSM for survival based on previously evaluated IP weights.