Package: episensr 1.3.0

Denis Haine

episensr: Basic Sensitivity Analysis of Epidemiological Results

Basic sensitivity analysis of the observed relative risks adjusting for unmeasured confounding and misclassification of the exposure/outcome, or both. It follows the bias analysis methods and examples from the book by Lash T.L, Fox M.P, and Fink A.K. "Applying Quantitative Bias Analysis to Epidemiologic Data", ('Springer', 2021).

Authors:Denis Haine [aut, cre]

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Bug tracker:https://github.com/dhaine/episensr/issues

On CRAN:

biasepidemiologysensitivity-analysisstatistics

20 exports 12 stars 2.03 score 65 dependencies 1 dependents 1 mentions 37 scripts 529 downloads

Last updated 6 months agofrom:fcacc9272f. Checks:OK: 5 NOTE: 2. Indexed: yes.

Exports:%>%boot.biasconfoundersconfounders.arrayconfounders.emmconfounders.evalueconfounders.extconfounders.limitconfounders.polymbiasmisclassificationmisclassification.covmultidimBiasmultiple.biasprobsensprobsens.confprobsens.irrprobsens.irr.confprobsens.selselection

Dependencies:actuarassertthatbootcachemclicolorspacecpp11curldagittydplyrexpintfansifarverfastmapforcatsgenericsggdagggforceggplot2ggraphggrepelgluegraphlayoutsgridExtragtableigraphisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmunsellnlmepillarpkgconfigpolyclippurrrR6RColorBrewerRcppRcppArmadilloRcppEigenrlangscalesstringistringrsystemfontstibbletidygraphtidyrtidyselecttrapezoidtriangletweenrutf8V8vctrsviridisviridisLitewithr