pssmooth: Flexible and Efficient Evaluation of Principal Surrogates/Treatment Effect Modifiers

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.

Version: 1.0.3
Imports: graphics, stats, osDesign, np, chngpt, MASS
Suggests: knitr, rmarkdown
Published: 2020-11-18
DOI: 10.32614/CRAN.package.pssmooth
Author: Michal Juraska [aut, cre]
Maintainer: Michal Juraska <mjuraska at>
License: GPL-2
NeedsCompilation: no
Citation: pssmooth citation info
Materials: README NEWS
CRAN checks: pssmooth results


Reference manual: pssmooth.pdf


Package source: pssmooth_1.0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): pssmooth_1.0.3.tgz, r-oldrel (arm64): pssmooth_1.0.3.tgz, r-release (x86_64): pssmooth_1.0.3.tgz, r-oldrel (x86_64): pssmooth_1.0.3.tgz
Old sources: pssmooth archive


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