clean

DESCRIPTION

@@ -3,13 +3,13 @@ Package: phase1b
 Title: Calculations for decisions on Phase 1b clinical trials
 Version: 1.0.0
 Authors@R: c(
-    person("Audrey", "Yeo", , "[email protected]", role = c("aut")),
     person("Daniel", "Sabanes Bove", , "[email protected]", role = c("aut", "cre")),
     person("Markus", "Elze", , "[email protected]", role = "aut"),
     person("Tony", "Pourmohamad", , "[email protected]", role = "aut"),
     person("Jiawen", "Zhu", , "[email protected]", role = "aut"),
     person("James", "Lymp", role = "aut"),
     person("Anastasia", "Teterina", , "[email protected]", role = "aut"),
+    person("Audrey", "Yeo", , "[email protected]", role = c("aut")),
     person("F. Hoffmann-La Roche Ltd", role = c("cph", "fnd"))
   )
 Description: The phase1b R package is intended to be used when conducting

README.md

@@ -2,34 +2,39 @@
 
 <!-- markdownlint-disable -->
 
-<img src="man/figures/hex_logo3.png" alt="hex logo" style="display: inline-block; width:200px; margin: 0 auto auto auto;" />
+<img src="man/figures/hex_logo3.png" align = "right" alt="hex logo" style="display: inline-block; width:200px; margin: 0 auto auto auto;" />
 <!-- markdownlint-enable -->
 
 The phase1b package project is a a Bayesian approach to decision making
 in early development clinical trials. As a background, the main purpose
 of early trials is to determine whether a novel treatment demonstrates
 sufficient safety and efficacy signals to warrant further investment
-(Lee & Liu, 2008). The new R package phase1b (Yeo et al, 2024) is a
-flexible toolkit that calculates many properties to this end, especially
-in the oncology therapeutic area. The primary focus of this package is
-on binary endpoints. The benefit of a Bayesian approach is the
-possibility to account for prior data (Thall & Simon, 1994) in that a
-new drug may have shown some signals of efficacy owing to its proposed
-mode of action, or similar activity based on prior data. The concept of
-the phase1b package is to evaluate the posterior probability that the
-response rate with a novel drug is better than with the current standard
-of care treatment in early phase trials such as Phase I. The phase1b
-package provides a facility for early development study teams to decide
-on further development of a drug either through designing for phase 2 or
-3, or expanding current cohorts. The prior distribution can incorporate
-any previous data via mixtures of beta distributions. Furthermore, based
-on an assumed true response rate if the novel drug was administered in
-the wider population, the package calculates the frequentist probability
-that a current clinical trial would be stopped for efficacy or futility
-conditional on true values of the response, otherwise known as operating
-characteristics. The intended user is the early clinical trial
-statistician in the design and interim stage of their study and offers a
-flexible approach to setting priors and weighting.
+(Lee & Liu, 2008).
+
+The new R package `phase1b` is a flexible toolkit that calculates many
+properties to this end, especially in the oncology therapeutic area. The
+primary focus of this package is on binary endpoints. The benefit of a
+Bayesian approach is the possibility to account for prior data (Thall &
+Simon, 1994) in that a new drug may have shown some signals of efficacy
+owing to its proposed mode of action, or similar activity based on prior
+data. The concept of the phase1b package is to evaluate the posterior
+probability that the response rate with a novel drug is better than with
+the current standard of care treatment in early phase trials such as
+Phase I.
+
+The phase1b package provides a facility for early development study
+teams to decide on further development of a drug either through
+designing for phase 2 or 3, or expanding current cohorts. The prior
+distribution can incorporate any previous data via mixtures of beta
+distributions. Furthermore, based on an assumed true response rate if
+the novel drug was administered in the wider population, the package
+calculates the frequentist probability that a current clinical trial
+would be stopped for efficacy or futility conditional on true values of
+the response, otherwise known as operating characteristics.
+
+The intended user is the early clinical trial statistician in the design
+and interim stage of their study and offers a flexible approach to
+setting priors and weighting.
 
 ## Installation
 
@@ -50,9 +55,5 @@ function in your console to access the documentation.
 
 ## Citing `phase1b`
 
-To cite `phase1b` :
-
-Yeo, A T, Sabanés Bové D, Elze M, Pourmohamad T, Zhu J, Lymp J, Teterina
-A (2024). Phase1b : Calculations for decisions on Phase 1b clinical
-trials. R package version 1.0.0, \<
-<https://genentech.github.io/phase1b/>\>
+To cite `phase1b` please see
+[here](https://genentech.github.io/phase1b/main/authors.html#citation).

README.rmd

@@ -4,11 +4,17 @@ output: github_document
 
 # phase1b
 <!-- markdownlint-disable -->
-<img src="man/figures/hex_logo3.png" alt="hex logo" style="display: inline-block; width:200px; margin: 0 auto auto auto;" />
+<img src="man/figures/hex_logo3.png" align = "right" alt="hex logo" style="display: inline-block; width:200px; margin: 0 auto auto auto;" />
 <!-- markdownlint-enable -->
 
-The `phase1b` package implements a Bayesian approach to decision making in early development clinical trials.
-As a background, the main purpose of early trials is to determine whether a novel treatment demonstrates sufficient safety and efficacy signals to warrant further investment (Lee & Liu, 2008). The new R package phase1b (Yeo et al, 2024)  is a flexible toolkit that calculates many properties to this end, especially in the oncology therapeutic area. The primary focus of this package is on binary endpoints. The benefit of a Bayesian approach is the possibility to account for prior data (Thall & Simon, 1994) in that a new drug may have shown some signals of efficacy owing to its proposed mode of action, or similar activity based on prior data. The concept of the phase1b package is to evaluate the posterior probability that the response rate with a novel drug is better than with the current standard of care treatment in early phase trials such as Phase I.  The phase1b package provides a facility for early development study teams to decide on further development of a drug either through designing for phase 2 or 3, or expanding current cohorts. The prior distribution can incorporate any previous data via mixtures of beta distributions. Furthermore, based on an assumed true response rate if the novel drug was administered in the wider population, the package calculates the frequentist probability that a current clinical trial would be stopped for efficacy or futility conditional on true values of the response, otherwise known as operating characteristics. The intended user is the early clinical trial statistician in the design and interim stage of their study and offers a flexible approach to setting priors and weighting.
+The phase1b package project is a a Bayesian approach to decision making in early development clinical trials.
+As a background, the main purpose of early trials is to determine whether a novel treatment demonstrates sufficient safety and efficacy signals to warrant further investment (Lee & Liu, 2008).
+
+The new R package `phase1b` is a flexible toolkit that calculates many properties to this end, especially in the oncology therapeutic area. The primary focus of this package is on binary endpoints. The benefit of a Bayesian approach is the possibility to account for prior data (Thall & Simon, 1994) in that a new drug may have shown some signals of efficacy owing to its proposed mode of action, or similar activity based on prior data. The concept of the phase1b package is to evaluate the posterior probability that the response rate with a novel drug is better than with the current standard of care treatment in early phase trials such as Phase I.
+
+The phase1b package provides a facility for early development study teams to decide on further development of a drug either through designing for phase 2 or 3, or expanding current cohorts. The prior distribution can incorporate any previous data via mixtures of beta distributions. Furthermore, based on an assumed true response rate if the novel drug was administered in the wider population, the package calculates the frequentist probability that a current clinical trial would be stopped for efficacy or futility conditional on true values of the response, otherwise known as operating characteristics.
+
+The intended user is the early clinical trial statistician in the design and interim stage of their study and offers a flexible approach to setting priors and weighting.
 
 ## Installation
 
@@ -27,8 +33,4 @@ An introductory vignette is currently being prepared. Use the help function in y
 
 ## Citing `phase1b`
 
-To cite `phase1b` :
-
-Yeo, A T, Sabanés Bové D, Elze M, Pourmohamad T, Zhu J, Lymp J, Teterina A (2024).
-Phase1b : Calculations for decisions on Phase 1b clinical trials. R package
-version 1.0.0, < https://genentech.github.io/phase1b/>
+To cite `phase1b` please see [here](https://genentech.github.io/phase1b/main/authors.html#citation).

inst/WORDLIST

@@ -1,7 +1,6 @@
 al
 analysed
 apriori
-AQAAQBAJ
 bA
 ba
 BayesBetaBinom