status](https://www.r-pkg.org/badges/version/SensIAT)](https://CRAN.R-project.org/package=SensIAT)

SensIAT

R Package for sensitivity analysis with irregular assessment times.

Installation

# Install from CRAN
install.packages("SensIAT")

You can also install the current development version from GitHub:

devtools::install_github("UofUEpiBio/pcoriRPackage")

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Version

Install

install.packages('SensIAT')

Monthly Downloads

466

Version

0.1.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Repository

https://github.com/UofUEpiBio/SensIAT

Maintainer

Andrew Redd

Last Published

November 17th, 2024

Functions in SensIAT (0.1.1)

SensIAT_jackknife

Estimate response with jackknife resampling

SensIAT-package

SensIAT: Sensitivity Analysis for Irregular Assessment Times

SensIAT_sim_outcome_modeler

Outcome Modeler for SensIAT Single Index Model.

pcori_conditional_means

Compute Conditional Means

fit_SensIAT_fulldata_model

Produce fitted model for group (treatment or control)

pcoriaccel_NW_basic

Runs a basic implementation of the "NW" function with the "K2_Biweight" kernel, just as a proof-of-concept.

pcori_control

Control Parameters for Fitting the within Group Model

SensIAT_example_data

SensIAT Example Data

pcoriaccel_NW

Runs an optimized implementation of the "NW" function.

Cond_mean_fn

Estimate Subject Predicted Mean Outcome

pcoriaccel_integrate_simp

Integrate function using adaptive Simpson quadrature.

pcoriaccel_evaluate_basis

Compiled version of evaluate_basis() function

predict.SensIAT_fulldata_model

Predict mean and variance of the outcome for a SensIAT within-group model

pcoriaccel_estimate_pmf

Directly estimate the probability mass function of Y.

pcoriaccel_compute_influence_term_2_quadv_sim_via_matrix

Runs an optimized implementation of the compute_influence_term_2_quadv_sim_via_matrix function.