CRAN/E | pssmooth

pssmooth

Flexible and Efficient Evaluation of Principal Surrogates/Treatment Effect Modifiers

Installation

About

Implements estimation and testing procedures for evaluating an intermediate biomarker response as a principal surrogate of a clinical response to treatment (i.e., principal stratification effect modification analysis), as described in Juraska M, Huang Y, and Gilbert PB (2020), Inference on treatment effect modification by biomarker response in a three-phase sampling design, Biostatistics, 21(3): 545-560 doi:10.1093/biostatistics/kxy074. The methods avoid the restrictive 'placebo structural risk' modeling assumption common to past methods and further improve robustness by the use of nonparametric kernel smoothing for biomarker density estimation. A randomized controlled two-group clinical efficacy trial is assumed with an ordered categorical or continuous univariate biomarker response measured at a fixed timepoint post-randomization and with a univariate baseline surrogate measure allowed to be observed in only a subset of trial participants with an observed biomarker response (see the flexible three-phase sampling design in the paper for details). Bootstrap-based procedures are available for pointwise and simultaneous confidence intervals and testing of four relevant hypotheses. Summary and plotting functions are provided for estimation results.

Citation pssmooth citation info
github.com/mjuraska/pssmooth
Bug report File report

Key Metrics

Version 1.0.3
Published 2020-11-18 1415 days ago
Needs compilation? no
License GPL-2
CRAN checks pssmooth results

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Maintainer

Maintainer

Michal Juraska

Authors

Michal Juraska

aut / cre

Material

README
NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

pssmooth archive

Imports

graphics
stats
osDesign
np
chngpt
MASS

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