Merge pull request #367 from arfon/patch-1

Minor fixes to JOSS paper

misc/joss_manuscript/paper.md

@@ -21,15 +21,12 @@ affiliations:
    index: 1
  - name: Data and Statistical Sciences, Pharma Development, Roche, Basel, Switzerland
    index: 2
-citation_author: Gower-Page, Noci, and Wolbers
 date: \today
 bibliography: references.bib
 output: rticles::joss_article
 journal: JOSS
 ---
 
-
-
 # Summary 
 
 Many randomized controlled clinical trials compare a continuous outcome variable that is assessed longitudinally at scheduled follow-up visits between subjects assigned to a intervention treatment group and those assigned to a control group. 
@@ -44,7 +41,7 @@ The package supports both standard imputation under a missing-at-random assumpti
 # Statement of need 
 
 `rbmi` is a flexible `R` package designed to support the analysis of randomized clinical trials with continuous longitudinal endpoints. 
-Both conventional MI methods based on Bayesian posterior draws and novel methods based on maximum likelihood estimation and re-sampling (as described in @vanHippelBartlett2021 and @Wolbers2021) are implemented. `rbmi` was designed for statisticians from both academic clinical research units and pharmaceutical industry. To our knowledge, a comprehensive and fully unit-tested `R` implementation of such approaches is still lacking. An established software implementation of reference-based imputation in SAS are the so-called "five macros" [@FiveMacros]. An alternative `R` implementation which is currently under development is the R package `RefBasedMI`[@RefbasedMIpackage].
+Both conventional MI methods based on Bayesian posterior draws and novel methods based on maximum likelihood estimation and re-sampling (as described in @vanHippelBartlett2021 and @Wolbers2021) are implemented. `rbmi` was designed for statisticians from both academic clinical research units and pharmaceutical industry. To our knowledge, a comprehensive and fully unit-tested `R` implementation of such approaches is still lacking. An established software implementation of reference-based imputation in SAS are the so-called "five macros" [@FiveMacros]. An alternative `R` implementation which is currently under development is the R package `RefBasedMI` [@RefbasedMIpackage].
 
 # `rbmi` workflow
 
@@ -77,7 +74,6 @@ All production code is required to have been reviewed by an independent programm
 Additionally comparisons are made to similar software (namely the so-called "five macros" [@FiveMacros] SAS implementation) to ensure consistency of results as well as to simulated datasets with known values.
 To date, `rbmi` has been used in two simulation studies reported in @Wolbers2021 and @Noci2021.
 
-
 # Author contributions and acknowledgements
 
 Craig Gower-Page and Alessandro Noci are the primary developers of the `rbmi` package. Marcel Wolbers initiated the project (jointly with Paul Delmar), specified the statistical methods and contributed to the documentation and vignettes.