--- title: "Getting started with rpact" author: "Friedrich Pahlke and Gernot Wassmer" date: "`r Sys.Date()`" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Getting started with rpact} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r setup, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` **Confirmatory Adaptive Clinical Trial Design, Simulation, and Analysis** ## Functional Range * Fixed sample design and designs with interim analysis stages * Sample size and power calculation for + means (continuous endpoint) + rates (binary endpoint) + survival trials with flexible recruitment and survival time options + count data * Simulation tool for means, rates, survival data, and count data + Assessment of adaptive sample size/event number recalculations based on conditional power + Assessment of treatment selection strategies in multi-arm trials * Adaptive analysis of means, rates, and survival data * Adaptive designs and analysis for multi-arm trials * Adaptive analysis and simulation tools for enrichment design testing means, rates, and hazard ratios * Automatic boundary recalculations during the trial for analysis with alpha spending approach, including under- and over-running ## Learn to use rpact We recommend three ways to learn how to use `rpact`: > 1. Use the Shiny app: [shiny.rpact.com](https://www.rpact.com/products#public-rpact-shiny-app) > 2. Use the Vignettes: > [www.rpact.org/vignettes](https://www.rpact.org/vignettes/) > 3. Book a training: > [www.rpact.com](https://www.rpact.com/services#learning-and-training) ### Vignettes The vignettes are hosted at [www.rpact.org/vignettes](https://www.rpact.org/vignettes/) and cover the following topics: 1. Defining Group Sequential Boundaries with rpact 2. Designing Group Sequential Trials with Two Groups and a Continuous Endpoint with rpact 3. Designing Group Sequential Trials with a Binary Endpoint with rpact 4. Designing Group Sequential Trials with Two Groups and a Survival Endpoint with rpact 5. Simulation-Based Design of Group Sequential Trials with a Survival Endpoint with rpact 6. An Example to Illustrate Boundary Re-Calculations during the Trial with rpact 7. Analysis of a Group Sequential Trial with a Survival Endpoint using rpact 8. Defining Accrual Time and Accrual Intensity with rpact 9. How to use R Generics with rpact 10. How to Create Admirable Plots with rpact 11. Comparing Sample Size and Power Calculation Results for a Group Sequential Trial with a Survival Endpoint: rpact vs. gsDesign 12. Supplementing and Enhancing rpact’s Graphical Capabilities with ggplot2 13. Using the Inverse Normal Combination Test for Analyzing a Trial with Continuous Endpoint and Potential Sample Size Re-Assessment with rpact 14. Planning a Trial with Binary Endpoints with rpact 15. Planning a Survival Trial with rpact 16. Simulation of a Trial with a Binary Endpoint and Unblinded Sample Size Re-Calculation with rpact 17. How to Create Summaries with rpact 18. How to Create One- and Multi-Arm Analysis Result Plots with rpact 19. How to Create One- and Multi-Arm Simulation Result Plots with rpact 20. Simulating Multi-Arm Designs with a Continuous Endpoint using rpact 21. Analysis of a Multi-Arm Design with a Binary Endpoint using rpact 22. Step-by-Step rpact Tutorial 23. Planning and Analyzing a Group-Sequential Multi-Arm Multi-Stage Design with Binary Endpoint using rpact 24. Two-arm Analysis for Continuous Data with Covariates from Raw Data using rpact (*exclusive*) 25. How to Install the Latest rpact Developer Version (*exclusive*) 26. Delayed Response Designs with rpact 27. Sample Size Calculation for Count Data ## User Concept ### Workflow * Everything is starting with a design, e.g.: `design <- getDesignGroupSequential()` * Find the optimal design parameters with help of `rpact` comparison tools: `getDesignSet` * Calculate the required sample size, e.g.: `getSampleSizeMeans()`, `getPowerMeans()` * Simulate specific characteristics of an adaptive design, e.g.: `getSimulationMeans()` * Collect your data, import it into R and create a dataset: `data <- getDataset()` * Analyze your data: `getAnalysisResults(design, data)` ### Focus on Usability The most important `rpact` functions have intuitive names: * `getDesign`[`GroupSequential`/`InverseNormal`/`Fisher`]`()` * `getDesignCharacteristics()` * `getSampleSize`[`Means`/`Rates`/`Survival`/`Counts`]`()` * `getPower`[`Means`/`Rates`/`Survival`/`Counts`]`()` * `getSimulation`[`MultiArm`/`Enrichment`]``[`Means`/`Rates`/`Survival`]`()` * `getDataSet()` * `getAnalysisResults()` * `getStageResults()` RStudio/Eclipse: auto code completion makes it easy to use these functions. ### R generics In general, everything runs with the R standard functions which are always present in R: so-called R generics, e.g., `print`, `summary`, `plot`, `as.data.frame`, `names`, `length` ### Utilities Several utility functions are available, e.g. * `getAccrualTime()` * `getPiecewiseSurvivalTime()` * `getNumberOfSubjects()` * `getEventProbabilities()` * `getPiecewiseExponentialDistribution()` * survival helper functions for conversion of `pi`, `lambda` and `median`, e.g., `getLambdaByMedian()` * `testPackage()`: installation qualification on a client computer or company server (via unit tests) ## Validation Please [contact](https://www.rpact.com/contact) us to learn how to use `rpact` on FDA/GxP-compliant validated corporate computer systems and how to get a copy of the formal validation documentation that is customized and licensed for exclusive use by your company, e.g., to fulfill regulatory requirements. ## About * **rpact** is a comprehensive validated^[The rpact validation documentation is available exclusively for our customers and supporting companies. For more information visit [www.rpact.com/services/sla](https://www.rpact.com/services/sla)] R package for clinical research which + enables the design and analysis of confirmatory adaptive group sequential designs + is a powerful sample size calculator + is a free of charge open-source software licensed under [LGPL-3](https://cran.r-project.org/web/licenses/LGPL-3) + particularly, implements the methods described in the recent monograph by [Wassmer and Brannath (2016)](https://doi.org/10.1007%2F978-3-319-32562-0) > For more information please visit [www.rpact.org](https://www.rpact.org) * **RPACT** is a company which offers + enterprise software development services + technical support for the `rpact` package + consultancy and user training for clinical research using R + validated software solutions and R package development for clinical research > For more information please visit [www.rpact.com](https://www.rpact.com) ## Contact * [info@rpact.com](mailto:info@rpact.com) * [www.rpact.com/contact](https://www.rpact.com/contact)