LatencyA: Latency Analysis in Epidemiological Studies Using Weighted Cumulative Exposures

Implements weighted cumulative exposure Cox proportional hazards models for latency analysis with repeatedly measured, time-varying exposures. Instead of entering every lagged exposure as a separate and highly correlated covariate, the lag-specific log hazard ratios are constrained to follow a smooth function of the time since exposure, parameterized by natural cubic splines or polynomials, so that the susceptible window of an exposure can be identified from the estimated lag-risk curve. Functions are provided to fit models with a prespecified number of knots or polynomial degree, to select the number of knots by a grid search or the spline terms by a stepwise search using the Akaike or Bayesian information criterion, and to extract lag-specific log hazard ratios with their variances. For the data-driven model selection procedures, inference is based on a cluster bootstrap that resamples subjects, which can be run sequentially or in parallel. The methods are described in Guo, Qian, Wang, Wang, Rosner and Wang (2026) "Taking Into Account the Susceptible Window for Exposures in Cox Proportional Hazards Model: A Way Using Splines to Model the Lag-Risk Relationship" <doi:10.1002/sim.70755>.

Version: 1.0.2
Depends: R (≥ 4.1.0)
Imports: Hmisc, survival, stats, MASS, stringr, future, furrr
Published: 2026-10-21
DOI: 10.32614/CRAN.package.LatencyA (may not be active yet)
Author: Fuyu Guo [aut, cre], Zihan Qian [aut], Molin Wang [aut]
Maintainer: Fuyu Guo <fuyuguo at hsph.harvard.edu>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: LatencyA results

Documentation:

Reference manual: LatencyA.html , LatencyA.pdf

Downloads:

Package source: LatencyA_1.0.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

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