This package is considered a duplicate. The official version of this package is found at:https://mayamathur.r-universe.dev/SimTimeVar

Package: SimTimeVar 1.0.0

Maya B. Mathur

SimTimeVar: Simulate Longitudinal Dataset with Time-Varying Correlated Covariates

Flexibly simulates a dataset with time-varying covariates with user-specified exchangeable correlation structures across and within clusters. Covariates can be normal or binary and can be static within a cluster or time-varying. Time-varying normal variables can optionally have linear trajectories within each cluster. See ?make_one_dataset for the main wrapper function. See Montez-Rath et al. <arxiv:1709.10074> for methodological details.

Authors:Maya B. Mathur, Kristopher Kapphahn, Ariadna Garcia, Manisha Desai, Maria E. Montez-Rath

SimTimeVar_1.0.0.tar.gz
SimTimeVar_1.0.0.zip(r-4.7-any)SimTimeVar_1.0.0.zip(r-4.6-any)SimTimeVar_1.0.0.zip(r-4.5-any)
SimTimeVar_1.0.0.tgz(r-4.6-any)SimTimeVar_1.0.0.tgz(r-4.5-any)
SimTimeVar_1.0.0.tar.gz(r-4.7-any)SimTimeVar_1.0.0.tar.gz(r-4.6-any)
SimTimeVar_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SimTimeVar/json (API)

# Install 'SimTimeVar' in R:

install.packages('SimTimeVar', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Datasets:

cat.params - An example dataframe for categorical variable parameters
params - An example parameters dataframe
pcor - An example across-cluster correlation dataframe
wcor - An example within-cluster correlation dataframe

On CRAN:

archived packages r-universe

1.70 score 5 stars 192 downloads 15 exports 81 dependencies

Last updated from:5f686a137c (on package/SimTimeVar). Checks:7 NOTE, 2 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	NOTE	193
source / vignettes	OK	209
linux-release-x86_64	NOTE	163
macos-release-arm64	NOTE	92
macos-oldrel-arm64	NOTE	83
windows-devel-x86_64	NOTE	77
windows-release-x86_64	NOTE	66
windows-oldrel-x86_64	NOTE	72
wasm-release	OK	122

Exports:add_one_categorical add_time_function_vars BN.rBound closest complete_parameters expand_matrix expand_subjects has_drug_suffix make_one_dataset make_one_linear_pred mod.jointly.generate.binary.normal override_static override_tbin_probs proportionize upper_tri_vec

Dependencies:abind backports boot broom car carData cli colorspace corpcor cowplot cpp11 Deriv digest doBy dplyr farver forecast Formula fracdiff generics ggplot2 glue GPArotation gtable ICC isoband labeling lattice lifecycle lme4 lmtest magrittr MASS mathjaxr Matrix MatrixModels metadat metafor mgcv minqa miscTools mnormt modelr mvtnorm nlme nloptr nnet numDeriv pbapply pbkrtest pillar pkgconfig plyr psych purrr quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas rlang S7 scales SparseM stringi stringr survival tibble tidyr tidyselect timeDate urca utf8 vctrs viridisLite withr zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Generate linear predictor from logistic model	add_one_categorical
Creates linear time-function variables	add_time_function_vars
Maximum correlation between binary and normal random variables	BN.rBound
An example dataframe for categorical variable parameters	cat.params
Return closest value	closest
Fill in partially incomplete parameters matrix	complete_parameters
Longitudinally expand a matrix of single observations by cluster	expand_matrix
Longitudinally expand a cluster	expand_subjects
Checks whether string has "_s" suffix	has_drug_suffix
Simulate time-varying covariates	make_one_dataset
Generate linear predictor from logistic model	make_one_linear_pred
Return closest value	mod.jointly.generate.binary.normal
Override static variable	override_static
Override probabilities for time-varying binary variables	override_tbin_probs
An example parameters dataframe	params
An example across-cluster correlation dataframe	pcor
Turn a number into a valid proportion	proportionize
Turn symmetric matrix into vector	upper_tri_vec
An example within-cluster correlation dataframe	wcor