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sensitivitymult (version 1.0.2)

Sensitivity Analysis for Observational Studies with Multiple Outcomes

Description

Sensitivity analysis for multiple outcomes in observational studies. For instance, all linear combinations of several outcomes may be explored using Scheffe projections in the comparison() function; see Rosenbaum (2016, Annals of Applied Statistics) . Alternatively, attention may focus on a few principal components in the principal() function. The package includes parallel methods for individual outcomes, including tests in the senm() function and confidence intervals in the senmCI() function.

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Version

Install

install.packages('sensitivitymult')

Monthly Downloads

185

Version

1.0.2

License

GPL-2

Maintainer

Paul Rosenbaum

Last Published

August 29th, 2017

Functions in sensitivitymult (1.0.2)

planScheffe

Combining One Planned Comparison and a Scheffe Correction For All Comparisons.
principal

Sensitivity Analysis for Principal Components of M-Scores for Several Outcomes in an Observational Study.
separable1v

Asymptotic separable calculations internal to other functions.
tbmetaphase

Genetic damage from drugs used to treat TB
senm

Sensitivity Analysis for a Matched Comparison in an Observational Study.
senmCI

Sensitivity Analysis for a Confidence Interval.
comparison

Sensitivity Analysis for a Comparison Involving Several Outcomes in an Observational Study.
mscorev

Computes M-scores for M-tests and estimates.
amplify

Amplification of sensitivity analysis in observational studies.
artcog

Arthritis and cognition in the elderly.
teeth

Smoking and Periodontal Disease.