From 9a717d6a0f7cf1d0e534865e9d1cd391dcb2dadf Mon Sep 17 00:00:00 2001 From: gowerc Date: Fri, 11 Oct 2024 16:38:39 +0100 Subject: [PATCH 1/4] added validation blurb --- README.md | 5 +++++ vignettes/FAQ.Rmd | 22 +++++++++++++++++++++ vignettes/FAQ.html | 48 +++++++++++++++++++++++++++++++--------------- 3 files changed, 60 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index 3b9bb2a55..f23563fa8 100644 --- a/README.md +++ b/README.md @@ -38,6 +38,11 @@ The basic usage of these core functions is described in the quickstart vignette: vignette(topic = "quickstart", package = "rbmi") ``` +## Validation + +For clarification on the current validation status of rbmi please see the FAQ vignette. + + ## Support For any help with regards to using the package or if you find a bug please create a [GitHub issue](https://github.com/insightsengineering/rbmi/issues) diff --git a/vignettes/FAQ.Rmd b/vignettes/FAQ.Rmd index 69d8c140c..fd9c36508 100644 --- a/vignettes/FAQ.Rmd +++ b/vignettes/FAQ.Rmd @@ -31,6 +31,28 @@ knitr::opts_chunk$set( This document provides answers to common questions about the `rbmi` package. It is intended to be read after the `rbmi: Quickstart` vignette. +
+ + +## Is `rbmi` validated ? + +With regards to software, validation is the act of ensuring that the software meets the needs and +requirements of users given the conditions of actual use. The FDA provides general principles and +guidance for validation but leaves it to individual sponsors to define their specific validation +processes. Therefore, no individual R package can claim to be 'validated' independently, as +validation depends on the entire software stack and the specific processes of each company. + +That being said, some of the core components of any validation process are the design specification +(what is the software supposed to do) as well as the testing / test results that demonstrate that +the design specification has been met. For rbmi, the design specification is documented extensively, +both at a macro level in vignettes and literature publications, and at a micro level in detailed +function manuals. This is supported by our extensive suite of unit and integration tests, which +ensure the software consistently produces correct output across a wide range of input scenarios. + +This documentation and test coverage enable rbmi to be easily installed and integrated into any +R system, in alignment with the system's broader validation process. + +
## How do the methods in `rbmi` compare to the mixed model for repeated measures (MMRM) implemented in the `mmrm` package? diff --git a/vignettes/FAQ.html b/vignettes/FAQ.html index 50b0abc9f..3283ef533 100644 --- a/vignettes/FAQ.html +++ b/vignettes/FAQ.html @@ -355,11 +355,12 @@

Alessandro Noci, Craig Gower-Page and Marcel Wolbers

@@ -369,8 +370,25 @@

1 Introduction

This document provides answers to common questions about the rbmi package. It is intended to be read after the rbmi: Quickstart vignette.


-
-

1.1 How do the methods in rbmi compare to the mixed model for repeated measures (MMRM) implemented in the mmrm package?

+
+

1.1 Is rbmi validated ?

+

With regards to software, validation is the act of ensuring that the software meets the needs and +requirements of users given the conditions of actual use. The FDA provides general principles and +guidance for validation but leaves it to individual sponsors to define their specific validation +processes. Therefore, no individual R package can claim to be ‘validated’ independently, as +validation depends on the entire software stack and the specific processes of each company.

+

That being said, some of the core components of any validation process are the design specification +(what is the software supposed to do) as well as the testing / test results that demonstrate that +the design specification has been met. For rbmi, the design specification is documented extensively, +both at a macro level in vignettes and literature publications, and at a micro level in detailed +function manuals. This is supported by our extensive suite of unit and integration tests, which +ensure the software consistently produces correct output across a wide range of input scenarios.

+

This documentation and test coverage enable rbmi to be easily installed and integrated into any +R system, in alignment with the system’s broader validation process.

+


+
+
+

1.2 How do the methods in rbmi compare to the mixed model for repeated measures (MMRM) implemented in the mmrm package?

rbmi was designed to complement and, occasionally, replace standard MMRM analyses for clinical trials with longitudinal endpoints.

Strengths of rbmi compared to the standard MMRM model are:

    @@ -384,8 +402,8 @@

    1.1 How do the methods in r


-
-

1.2 How does rbmi compare to general-purpose software for multiple imputation (MI) such as mice?

+
+

1.3 How does rbmi compare to general-purpose software for multiple imputation (MI) such as mice?

rbmi covers only “MMRM-type” settings, i.e. settings with a single longitudinal continuous outcome which may be missing at some visits and hence require imputation.

For these settings, it has several advantages over general-purpose MI software:

    @@ -396,14 +414,14 @@

    1.2 How does rbmi co

    However, rbmi is much more limited in its functionality than general-purpose MI software.


-
-

1.3 How to handle missing data in baseline covariates in rbmi?

+
+

1.4 How to handle missing data in baseline covariates in rbmi?

rbmi does not support imputation of missing baseline covariates. Therefore, missing baseline covariates need to be handled outside of rbmi. The best approach for handling missing baseline covariates needs to be made on a case-by-case basis but in the context of randomized trials, relatively simple approach are often sufficient (White and Thompson (2005)).


-
-

1.4 Why does rbmi by default use an ANCOVA analysis model and not an MMRM analysis model?

+
+

1.5 Why does rbmi by default use an ANCOVA analysis model and not an MMRM analysis model?

The theoretical justification for the conditional mean imputation method requires that the analysis model leads to a point estimator which is a linear function of the outcome vector (Wolbers et al. (2022)). This is the case for ANCOVA but not for general MMRM models. For the other imputation methods, both ANCOVA and MMRM are valid analysis methods. An MMRM analysis model could be implemented by providing a custom analysis function to the analyse() function.

For further expalanations, we also cite the end of section 2.4 of the conditional mean imputation paper (Wolbers et al. (2022)):

@@ -414,8 +432,8 @@

1.4 Why does rbmi by


-
-

1.5 How can I analyse the change-from-baseline in the analysis model when imputation was done on the original outcomes?

+
+

1.6 How can I analyse the change-from-baseline in the analysis model when imputation was done on the original outcomes?

This can be achieved using custom analysis functions as outlined in Section 7 of the Advanced Vignette. e.g.

ancova_modified <- function(data, ...) {
     data2 <- data %>% mutate(ENDPOINT = ENDPOINT - BASELINE)

From 6296da9332915e9ca84adc4abb36cd85f9d7b0a0 Mon Sep 17 00:00:00 2001
From: Craig Gower-Page 
Date: Tue, 15 Oct 2024 14:08:06 +0100
Subject: [PATCH 2/4] Update vignettes/FAQ.Rmd

Co-authored-by: Isaac Gravestock <83659704+gravesti@users.noreply.github.com>
Signed-off-by: Craig Gower-Page 
---
 vignettes/FAQ.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/vignettes/FAQ.Rmd b/vignettes/FAQ.Rmd
index fd9c36508..63e1ba8ab 100644
--- a/vignettes/FAQ.Rmd
+++ b/vignettes/FAQ.Rmd
@@ -34,7 +34,7 @@ It is intended to be read after the `rbmi: Quickstart` vignette.
 

 
 
-## Is `rbmi` validated ? 
+## Is rbmi validated? 
 
 With regards to software, validation is the act of ensuring that the software meets the needs and
 requirements of users given the conditions of actual use. The FDA provides general principles and

From baa81684069d2b71fcb3cc470e38793fca0db040 Mon Sep 17 00:00:00 2001
From: Craig Gower-Page 
Date: Tue, 15 Oct 2024 14:08:32 +0100
Subject: [PATCH 3/4] Update vignettes/FAQ.Rmd

Co-authored-by: Isaac Gravestock <83659704+gravesti@users.noreply.github.com>
Signed-off-by: Craig Gower-Page 
---
 vignettes/FAQ.Rmd | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/vignettes/FAQ.Rmd b/vignettes/FAQ.Rmd
index 63e1ba8ab..d1e72a3fe 100644
--- a/vignettes/FAQ.Rmd
+++ b/vignettes/FAQ.Rmd
@@ -36,7 +36,7 @@ It is intended to be read after the `rbmi: Quickstart` vignette.
 
 ## Is rbmi validated? 
 
-With regards to software, validation is the act of ensuring that the software meets the needs and
+With regards to software in the pharmaceutical industry, validation is the act of ensuring that the software meets the needs and
 requirements of users given the conditions of actual use. The FDA provides general principles and
 guidance for validation but leaves it to individual sponsors to define their specific validation
 processes. Therefore, no individual R package can claim to be 'validated' independently, as

From e89ed45ac408254d5fd2eb95de2a508bad57fb5c Mon Sep 17 00:00:00 2001
From: gowerc 
Date: Tue, 15 Oct 2024 14:10:01 +0100
Subject: [PATCH 4/4] updated html vignette

---
 vignettes/FAQ.html | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/vignettes/FAQ.html b/vignettes/FAQ.html
index 3283ef533..c61c9dc24 100644
--- a/vignettes/FAQ.html
+++ b/vignettes/FAQ.html
@@ -355,7 +355,7 @@ 
Alessandro Noci, Craig Gower-Page and Marcel Wolbers