Package: MRTSampleSizeBinary 0.1.2

MRTSampleSizeBinary: Sample Size Calculator for MRT with Binary Outcomes

Provides a sample size calculator for micro-randomized trials (MRTs) with binary outcomes based on Cohn et al. (2023) <doi:10.1002/sim.9748>. Also provides a power calculator when the sample size is input by the user.

Authors:Eliot Wong-Toi, Thabat Dahdoul, Tianchen Qian

MRTSampleSizeBinary_0.1.2.tar.gz
MRTSampleSizeBinary_0.1.2.zip(r-4.7-any)MRTSampleSizeBinary_0.1.2.zip(r-4.6-any)MRTSampleSizeBinary_0.1.2.zip(r-4.5-any)
MRTSampleSizeBinary_0.1.2.tgz(r-4.6-any)MRTSampleSizeBinary_0.1.2.tgz(r-4.5-any)
MRTSampleSizeBinary_0.1.2.tar.gz(r-4.7-any)MRTSampleSizeBinary_0.1.2.tar.gz(r-4.6-any)
MRTSampleSizeBinary_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MRTSampleSizeBinary/json (API)

# Install 'MRTSampleSizeBinary' in R:

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

Bug tracker:https://github.com/tqian/mrtsamplesizebinary/issues

Datasets:

alpha_1 - Vector that defines the success probability null curve.
beta_1 - Vector that defines the MEE under the alternative hypothesis.
f_t_1 - A matrix defining the MEE under the alternative hypothesis.
g_t_1 - A matrix defining the success probability null curve.
m_matrix_1 - An example matrix for "bread" of sandwich estimator of variance.
p_t_1 - A vector of randomization probabilities for each time point.
sigma_matrix_1 - An example matrix for "meat" of sandwich estimator of variance.
tau_t_1 - Vector that holds the average availability at each time point.

On CRAN:

4.59 score 39 scripts 325 downloads 9 exports 19 dependencies

Last updated from:635e66ed02. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	176
source / vignettes	OK	165
linux-release	OK	126
macos-release	OK	99
macos-oldrel	OK	121
windows-devel	OK	116
windows-release	OK	85
windows-oldrel	OK	91
wasm-release	OK	95

Exports:compute_m_sigma compute_ncp is_full_column_rank max_samp min_samp mrt_binary_power mrt_binary_ss power_summary power_vs_n_plot

Dependencies:cli cpp11 farver ggplot2 glue gtable isoband labeling lattice lifecycle Matrix R6 RColorBrewer rlang S7 scales vctrs viridisLite withr

Sample Size Calculator for Micro-Randomized Trials with Binary Outcomes

Rendered fromsample-size-calcualtor-for-mrt.Rmdusingknitr::rmarkdown

Last update: 2023-12-02
Started: 2020-11-28

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Vector that defines the success probability null curve.	alpha_1
Vector that defines the MEE under the alternative hypothesis.	beta_1
Computes "M" and "Sigma" matrices for the sandwich estimator of variance-covariance matrix.	compute_m_sigma
Computes the non-centrality parameter for an F distributed random variable in the context of a MRT with binary outcome.	compute_ncp
A matrix defining the MEE under the alternative hypothesis.	f_t_1
A matrix defining the success probability null curve.	g_t_1
Check if a matrix is full column rank.	is_full_column_rank
An example matrix for "bread" of sandwich estimator of variance.	m_matrix_1
Returns default maximum sample size to end power_vs_n_plot().	max_samp
Compute minimum sample size.	min_samp
Calculate power for binary outcome MRT	mrt_binary_power
Calculate sample size for binary outcome MRT	mrt_binary_ss
A vector of randomization probabilities for each time point.	p_t_1
Calculate sample size at a range of power levels.	power_summary
Returns a plot of power vs sample size in the context of a binary outcome MRT. See the vignette for more details.	power_vs_n_plot
An example matrix for "meat" of sandwich estimator of variance.	sigma_matrix_1
Vector that holds the average availability at each time point.	tau_t_1