Package: stpm 1.7.12

Ilya Y. Zhbannikov

stpm: Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes

Utilities to estimate parameters of the models with survival functions induced by stochastic covariates. Miscellaneous functions for data preparation and simulation are also provided. For more information, see: (i)"Stochastic model for analysis of longitudinal data on aging and mortality" by Yashin A. et al. (2007), Mathematical Biosciences, 208(2), 538-551, <doi:10.1016/j.mbs.2006.11.006>; (ii) "Health decline, aging and mortality: how are they related?" by Yashin A. et al. (2007), Biogerontology 8(3), 291(302), <doi:10.1007/s10522-006-9073-3>.

Authors:I. Zhbannikov, Liang He, K. Arbeev, I. Akushevich, A. Yashin.

stpm_1.7.12.tar.gz
stpm_1.7.12.tar.gz(r-4.5-noble)stpm_1.7.12.tar.gz(r-4.4-noble)
stpm_1.7.12.tgz(r-4.4-emscripten)stpm_1.7.12.tgz(r-4.3-emscripten)
stpm.pdf |stpm.html✨
stpm/json (API)
NEWS

# Install 'stpm' in R:
install.packages('stpm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • ex_data - This is the longitudinal genetic dataset.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.68 score 95 scripts 370 downloads 1 mentions 17 exports 8 dependencies

Last updated 2 years agofrom:66e4b79dc3. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-linux-x86_64OKNov 10 2024

Exports:prepare_datasim_pobssimdata_contsimdata_discrsimdata_gamma_frailtysimdata_time_depspmspm_con_1dspm_con_1d_gspm_cont_linspm_cont_quad_linspm_continuousspm_discretespm_pobsspm_projectionspm_time_depspm.impute

Dependencies:latticeMASSMatrixnloptrRcppRcppArmadillosas7bdatsurvival

Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes

Ilya Y. Zhbannikov

Rendered fromstpm-vignette.Rmdusingknitr::rmarkdownon Nov 10 2024.

Last update: 2022-09-05
Started: 2016-02-09

Readme and manuals

Help Manual

Help pageTopics
function loading results in global environmentassign_to_global
This is the longitudinal genetic dataset.ex_data
An internal function to compute m and gamma based on continuous-time model (Yashin et. al., 2007)func1
An internal function to obtain column index by its nameget.column.index
An internal function to compute next Y based on continous-time model (Yashin et. al., 2007)getNextY.cont
An internal function to compute next value of physiological variable YgetNextY.cont2
An internal function to compute the next value of physiological variable Y based on discrete-time model (Akushevich et. al., 2005)getNextY.discr
An internal function to compute next m based on dicrete-time modelgetNextY.discr.m
An internal function to compute previous value of physiological variable Y based on discrete-time modelgetPrevY.discr
An internal function to compute previous m based on discrete-time modelgetPrevY.discr.m
This is the longitudinal dataset.longdat
Likelihood-ratio testLRTest
An internal function to compute m fromm
An internal function which construct short data format from a given longmake.short.format
An internal function to compute mumu
Data pre-processing for analysis with stochastic process model methodology.prepare_data
Prepares continuouts-time dataset.prepare_data_cont
Prepares discrete-time dataset.prepare_data_discr
An internal function to compute sigma square analyticallysigma_sq
Multi-dimension simulation function for data with partially observed covariates (multidimensional GenSPM) with arbitrary intervalssim_pobs
Multi-dimensional simulation function for continuous-time SPM.simdata_cont
Multi-dimension simulation functionsimdata_discr
This script simulates data using familial frailty model. We use the following variation: gamma(mu, ssq), where mu is the mean and ssq is sigma square. See: https://www.rocscience.com/help/swedge/webhelp/swedge/Gamma_Distribution.htmsimdata_gamma_frailty
Simulation function for continuous trait with time-dependant coefficients.simdata_time_dep
A central function that estimates Stochastic Process Model parameters a from given dataset.spm
Fitting a 1-D SPM model with constant parametersspm_con_1d
Fitting a 1-D genetic SPM model with constant parametersspm_con_1d_g
Continuous multi-dimensional optimization with linear terms in mu onlyspm_cont_lin
Continuous multi-dimensional optimization with quadratic and linear termsspm_cont_quad_lin
Continuous multi-dimensional optimizationspm_continuous
Discrete multi-dimensional optimizationspm_discrete
Continuous-time multi-dimensional optimization for SPM with partially observed covariates (multidimensional GenSPM)spm_pobs
A data projection with previously estimated or user-defined parameters. Projections are constructed for a cohort with fixed or normally distributed initial covariates.spm_projection
A function for the model with time-dependent model parameters.spm_time_dep
Multiple Data Imputation with SPMspm.impute
Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomesstpm-package stpm
Returns string w/o leading or trailing whitespacetrim
Returns string w/o leading whitespacetrim.leading
Returns string w/o trailing whitespacetrim.trailing
Vital (mortality) statistics.vitstat