Package: doseSens 0.1.0

doseSens: Conduct Sensitivity Analysis with Continuous Exposures and Binary Outcomes

Performs sensitivity analysis for the sharp null and attributable effects in matched studies with continuous exposures and binary outcomes. Two of the functions require installation of the 'Gurobi' optimizer. Please see <https://www.gurobi.com/documentation/9.0/refman/ins_the_r_package.html> for guidance.

Authors:Jeffrey Zhang [aut, cre]

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doseSens.pdf |doseSens.html✨
doseSens/json (API)

# Install 'doseSens' in R:
install.packages('doseSens', repos = c('https://jzhang1937.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jzhang1937/dosesens/issues

Datasets:

On CRAN:

6 exports 0.73 score 17 dependencies 190 downloads

Last updated 8 months agofrom:0b84be7716. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 23 2024
R-4.5-winNOTEAug 23 2024
R-4.5-linuxNOTEAug 23 2024
R-4.4-winNOTEAug 23 2024
R-4.4-macNOTEAug 23 2024
R-4.3-winNOTEAug 23 2024
R-4.3-macNOTEAug 23 2024

Exports:binary_thresh_attributedev_TVdose_attributable_generaldose_sensitivity_mc_gendose_thresh_attributable_one_sidednormal_test_gen

Dependencies:clidplyrfansigenericsgluegtoolslifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr

Readme and manuals

Help Manual

Help pageTopics
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.binary_thresh_attribute
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.change_Delta
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.dev_TV
Inference for general attributable effects in sensitivity analysis with continuous exposures and binary outcomes. Gurobi must be installed to use this function.dose_attributable_general
Sharp null monte-carlo sensitivity analysis for continuous exposures and binary outcomes.dose_sensitivity_mc_gen
Inference for threshold attributable effects in sensitivity analysis with continuous exposures and binary outcomes. Gurobi must be installed to use this function.dose_thresh_attributable_one_sided
Sharp null sensitivity analysis for continuous exposures and binary outcomes using normal approximation.normal_test_gen
Matched lead datasettreat_out_match