Package: snSMART 0.2.4

Michael Kleinsasser

snSMART: Small N Sequential Multiple Assignment Randomized Trial Methods

Consolidated data simulation, sample size calculation and analysis functions for several snSMART (small sample sequential, multiple assignment, randomized trial) designs under one library. See Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M. "A Bayesian analysis of small n sequential multiple assignment randomized trials (snSMARTs)." (2018) Statistics in medicine, 37(26), pp.3723-3732 <doi:10.1002/sim.7900>.

Authors:Sidi Wang [aut], Kelley Kidwell [aut], Michael Kleinsasser [cre]

snSMART_0.2.4.tar.gz
snSMART_0.2.4.zip(r-4.5)snSMART_0.2.4.zip(r-4.4)snSMART_0.2.4.zip(r-4.3)
snSMART_0.2.4.tgz(r-4.4-any)snSMART_0.2.4.tgz(r-4.3-any)
snSMART_0.2.4.tar.gz(r-4.5-noble)snSMART_0.2.4.tar.gz(r-4.4-noble)
snSMART_0.2.4.tgz(r-4.4-emscripten)snSMART_0.2.4.tgz(r-4.3-emscripten)
snSMART.pdf |snSMART.html✨
snSMART/json (API)

# Install 'snSMART' in R:

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

Bug tracker:https://github.com/sidiwang/snsmart/issues

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC
c++– GNU Standard C++ Library v3

Datasets:

data_binary - Dataset with binary outcomes
data_dose - Dose Level dataset with binary outcomes
groupseqDATA_full - Group sequential full data
groupseqDATA_look1 - Group sequential data look 1
trialDataMF - Dataset with continuous outcomes

On CRAN:

bayesian-analysis clinical-trials rare-disease small-sample

3.90 score 1 stars 3 scripts 314 downloads 17 exports 54 dependencies

Last updated 2 months agofrom:39aa45736b. Checks:OK: 6 ERROR: 1. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 06 2024
R-4.5-win	ERROR	Nov 06 2024
R-4.5-linux	OK	Nov 06 2024
R-4.4-win	OK	Nov 06 2024
R-4.4-mac	OK	Nov 06 2024
R-4.3-win	OK	Nov 06 2024
R-4.3-mac	OK	Nov 06 2024

Exports:BJSM_binary BJSM_c group_seq LPJSM_binary print.BJSM_binary print.BJSM_c print.BJSM_dose_binary print.group_seq print.LPJSM_binary print.sample_size print.summary.BJSM_binary print.summary.BJSM_c print.summary.BJSM_dose_binary print.summary.group_seq print.summary.LPJSM_binary print.summary.sample_size sample_size

Dependencies:backports bayestestR broom cli coda colorspace condMVNorm cpp11 cubature datawizard dplyr EnvStats evd fansi farver geepack generics ggplot2 glue gtable HDInterval insight isoband labeling lattice lifecycle magrittr MASS Matrix mgcv munsell mvtnorm nlme nortest pillar pkgconfig pracma purrr R6 RColorBrewer Rcpp rjags rlang scales stringi stringr tibble tidyr tidyselect truncdist utf8 vctrs viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
BJSM for snSMART (3 active treatments/placebo and 2 dose level) with binary outcome	BJSM_binary print.BJSM_binary print.BJSM_dose_binary print.summary.BJSM_binary print.summary.BJSM_dose_binary
BJSM continuous (snSMART with three active treatments and a continuous outcome design)	BJSM_c print.BJSM_c print.summary.BJSM_c summary.BJSM_c
Dataset with binary outcomes	data_binary
Dose Level dataset with binary outcomes	data_dose
BJSM method for interim analysis and final analysis of group sequential trial design	group_seq print.group_seq print.summary.group_seq
Group sequential full data	groupseqDATA_full
Group sequential data look 1	groupseqDATA_look1
LPJSM for snSMART with binary outcomes (3 active treatments or placebo and two dose level)	LPJSM_binary print.LPJSM_binary print.summary.LPJSM_binary summary.LPJSM_binary
Sample size calculation for snSMART with 3 active treatments and a binary outcome	print.sample_size print.summary.sample_size sample_size summary.sample_size
Summarizing BJSM fits	summary.BJSM_binary
Summarizing BJSM fits	summary.BJSM_dose_binary
Summarizing BJSM fits	summary.group_seq
Dataset with continuous outcomes	trialDataMF