Nonparametric Methods for Generating High Quality Comparative Effectiveness Evidence
Deprecated LocalControl functions
Local Control
Local Control Classic
Calculate confidence intervals around the cumulative incidence functio...
Provides a bootstrapped confidence interval estimate for LocalControl ...
Plot cumulative incidence functions (CIFs) from Local Control.
Plots the local treatment difference as a function of radius for Local...
Test for Within-Bin X-covariate Balance in Supervised Propensiy Scorin...
LOESS Smoothing of Outcome by Treatment in Supervised Propensiy Scorin...
Propensity Score prediction of Treatment Selection from Patient Baseli...
Change the Number of Bins in Supervised Propensiy Scoring
Examine Treatment Differences on an Outcome Measure in Supervised Prop...
Prepare for Accumulation of (Outcome,Treatment) Results in Unsupervise...
Artificial Distribution of LTDs from Random Clusters
Returns a series of boxplots comparing LTD distributions given differe...
Display Sensitivity Analysis Graphic in Unsupervised Propensiy Scoring
Hierarchical Clustering of Patients on X-covariates for Unsupervised P...
Instrumental Variable LATE Linear Fitting in Unsupervised Propensiy Sc...
Plot the LTD distribution as a function of the number of clusters.
Nearest Neighbor Distribution of LTDs in Unsupervised Propensiy Scorin...
Implements novel nonparametric approaches to address biases and confounding when comparing treatments or exposures in observational studies of outcomes. While designed and appropriate for use in studies involving medicine and the life sciences, the package can be used in other situations involving outcomes with multiple confounders. The package implements a family of methods for non-parametric bias correction when comparing treatments in observational studies, including survival analysis settings, where competing risks and/or censoring may be present. The approach extends to bias-corrected personalized predictions of treatment outcome differences, and analysis of heterogeneity of treatment effect-sizes across patient subgroups. For further details, please see: Lauve NR, Nelson SJ, Young SS, Obenchain RL, Lambert CG. LocalControl: An R Package for Comparative Safety and Effectiveness Research. Journal of Statistical Software. 2020. p. 1–32. Available from <doi:10.18637/jss.v096.i04>.