Package: splinetrials 0.1.1

splinetrials: Facilitate Clinical Trials Analysis Using Natural Cubic Splines

Create mixed models with repeated measures using natural cubic splines applied to an observed continuous time variable, as described by Donohue et al. (2023) <doi:10.1002/pst.2285>. Iterate through multiple covariance structure types until one converges. Categorize observed time according to scheduled visits. Perform subgroup analyses.

Authors:Nik Krieger [aut, cre], Daniel Sabanes Bove [ctb], Eli Lilly and Company [cph]

splinetrials_0.1.1.tar.gz
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splinetrials_0.1.1.tgz(r-4.6-any)splinetrials_0.1.1.tgz(r-4.5-any)
splinetrials_0.1.1.tar.gz(r-4.7-any)splinetrials_0.1.1.tar.gz(r-4.6-any)
splinetrials_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
splinetrials/json (API)
NEWS

# Install 'splinetrials' in R:

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

Bug tracker:https://github.com/nikkrieger/splinetrials/issues

Pkgdown/docs site:https://nikkrieger.github.io

On CRAN:

3.88 score 3 stars 154 downloads 15 exports 91 dependencies

Last updated from:0acbc72e68. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	168
source / vignettes	OK	197
linux-release-x86_64	OK	156
macos-release-arm64	OK	131
macos-oldrel-arm64	OK	127
windows-devel	OK	116
windows-release	OK	102
windows-oldrel	OK	91
wasm-release	OK	123

Exports:bin_timepoints change_from_baseline make_visit_labels midpoints ncs_analysis ncs_analysis_subgroup ncs_emmeans ncs_mmrm_fit ncs_plot_means ncs_plot_means_subgroup percent_slowing_using_change_from_bl plot_outcome_by_visit_and_group time_spline time_spline_basis treatment_effect

Dependencies:abind backports boot brio broom callr car carData checkmate cli colorspace cowplot cpp11 crayon Deriv desc diffobj doBy dplyr emmeans estimability evaluate farver forecast Formula fracdiff fs generics ggplot2 glue gtable isoband jsonlite labeling lattice lifecycle lme4 lmtest magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa mmrm modelr mvtnorm nlme nloptr nnet numDeriv pbkrtest pillar pkgbuild pkgconfig pkgload praise processx ps purrr quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas rlang rprojroot S7 scales SparseM stringi stringr survival testthat tibble tidyr tidyselect timeDate TMB urca utf8 vctrs viridisLite waldo withr zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Categorize Observed Timepoints According to Scheduled Timepoints	bin_timepoints
Calculate the Change from Baseline or Treatment Effects from Estimated Marginal Means	change_from_baseline treatment_effect
Make Visit Labels Based on a Numeric Vector	make_visit_labels
Midpoints of a Numeric Vector	midpoints
Run a Natural Cubic Spline (NCS) Analysis.	ncs_analysis ncs_analysis_subgroup
Estimate Marginal Means for a Natural Cubic Splines Analysis	ncs_emmeans
Create a Mixed Model with Repeated Measures Using Natural Cubic Splines.	ncs_mmrm_fit
Plot Actual and Predicted Response Variable Means by Study Arm.	ncs_plot_means
Plot Actual and Predicted Response Variable Means by Study Arm and Subgroup.	ncs_plot_means_subgroup
Calculates Percent Slowing from a Data Frame of Change-from-Baseline Data	percent_slowing_using_change_from_bl
Plot Outcome Variable by Timepoint and Study Arm	plot_outcome_by_visit_and_group
'splinetrials_analysis' object	splinetrials_analysis-class
'splinetrials_subgroup_analysis' object	splinetrials_subgroup_analysis-class
Create Natural Cubic Spline Approximations for Continuous Time	time_spline
Natural Cubic Spline Basis Matrix for Continuous Time.	time_spline_basis