Package: DRpower 1.0.3
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:
DRpower_1.0.3.tar.gz
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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')) |
Bug tracker:https://github.com/mrc-ide/drpower/issues
- 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.
Last updated 7 days agofrom:109b266938. Checks:OK: 9. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 08 2024 |
R-4.5-win-x86_64 | OK | Nov 08 2024 |
R-4.5-linux-x86_64 | OK | Nov 08 2024 |
R-4.4-win-x86_64 | OK | Nov 08 2024 |
R-4.4-mac-x86_64 | OK | Nov 08 2024 |
R-4.4-mac-aarch64 | OK | Nov 08 2024 |
R-4.3-win-x86_64 | OK | Nov 08 2024 |
R-4.3-mac-x86_64 | OK | Nov 08 2024 |
R-4.3-mac-aarch64 | OK | Nov 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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