Package: DRpower 1.0.3

Bob Verity

DRpower: Study design and analysis for pfhrp2/3 deletion prevalence studies

This package can be used in the design and/or analysis stages of Plasmodium falciparum pfhrp2/3 deletion prevalence studies. We assume that the study takes the form of a clustered prevalence survey, meaning the data consists of a numerator (number of deletions found) and denominator (number tested) over multiple clusters. We are interested in estimating the study-level prevalence, i.e. over all clusters, while accounting for the possibility of high intra-cluster correlation. The analysis approach uses a Bayesian random effects model to estimate prevalence and intra-cluster correlation. The approach to power analysis is simulation-based, running the analysis many times on simulated data and estimating empirical power. This method can be used to establish a minimum sample size required to achieve a given target power.

Authors:Bob Verity [aut, cre], Shazia Ruybal [aut]

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DRpower.pdf |DRpower.html
DRpower/json (API)

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

Peer review:

Bug tracker:https://github.com/mrc-ide/drpower/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • df_sim - Summary of simulations from the threshold analysis
  • df_ss - Minimum sample sizes for the threshold analysis
  • historical_data - Data from historical pfhrp2 studies that passed filters for inclusion into an ICC analysis.

On CRAN:

4.96 score 1 stars 26 scripts 18 exports 41 dependencies

Last updated 7 days agofrom:109b266938. Checks:OK: 9. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-win-x86_64OKNov 08 2024
R-4.5-linux-x86_64OKNov 08 2024
R-4.4-win-x86_64OKNov 08 2024
R-4.4-mac-x86_64OKNov 08 2024
R-4.4-mac-aarch64OKNov 08 2024
R-4.3-win-x86_64OKNov 08 2024
R-4.3-mac-x86_64OKNov 08 2024
R-4.3-mac-aarch64OKNov 08 2024

Exports:%>%check_DRpower_loadedget_ICCget_jointget_marginget_margin_Bayesianget_margin_CPget_power_presenceget_power_thresholdget_prevalenceget_sample_size_marginget_sample_size_margin_CPget_sample_size_presenceget_sample_size_tableplot_ICCplot_jointplot_powerplot_prevalence

Dependencies:clicolorspacecpp11dplyrextraDistrfansifarvergenericsggplot2gluegtableisobandknitrProgressBarlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpurrrR.methodsS3R.ooR6RColorBrewerRcpprlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Analysing data

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Background

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CIs and Overdispersion

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Designing a study

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Historical analysis

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How to Summarise the Prevalence

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Installation

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Mathematical Details

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Power and Sample Size in the DRpower Model

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Sample Size Calculation in the 2020 WHO Master Protocol

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The Design Effect

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The DRpower model

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The One-sample Z-test

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Weaknesses with the CI-based Approach

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