R: Conduct Sensitivity Analysis with Continuous Exposures and Binary Outcomes

# Conduct Sensitivity Analysis with Continuous Exposures and Binary Outcomes

## Documentation for package ‘doseSens’ version 0.1.0

- DESCRIPTION file.

## Help Pages

binary_thresh_attribute | Separable algorithm for threshold attributable effect in a sensitivity analysis with at most one over-exposed unit in each matched set. For a greater than alternative, finds the 'a' matched sets that most decrease the mean and/or variance.
change_Delta | A helper that takes a gurobi model object outputted from dose_attributable_general or dose_thresh_attributable_one_sided and changes the Delta parameter. Saves computation time by directly editing the constraint involving Delta without having to reinitialize the other constraints that are kept the same. Outputs a list analogous to output from dose_attributable_general or dose_thresh_attributable_one_sided.
dev_TV | Computes deviation from uniform distribution in total variation distance for a given amount of unmeasured confounding and a greater than alternative with a binary outcome.
dose_attributable_general | Inference for general attributable effects in sensitivity analysis with continuous exposures and binary outcomes. Gurobi must be installed to use this function.
dose_sensitivity_mc_gen | Sharp null monte-carlo sensitivity analysis for continuous exposures and binary outcomes.
dose_thresh_attributable_one_sided | Inference for threshold attributable effects in sensitivity analysis with continuous exposures and binary outcomes. Gurobi must be installed to use this function.
normal_test_gen | Sharp null sensitivity analysis for continuous exposures and binary outcomes using normal approximation.
treat_out_match | Matched lead dataset