Add reference to accompanying paper

Author: aswenne

README.Rmd

@@ -20,7 +20,7 @@ knitr::opts_chunk$set(
 [![R-CMD-check](https://github.com/bips-hb/dsGamlss/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/bips-hb/dsGamlss/actions/workflows/R-CMD-check.yaml)
 <!-- badges: end -->
 
-The `dsGamlss` package is a [DataSHIELD](https://www.datashield.org) server-side package that includes the server-side functions to fit Generalized Additive Models for Location, Scale and Shape (GAMLSS) [1] using DataSHIELD. It is based on the original [gamlss](https://cran.r-project.org/package=gamlss) implementation [1] and the [dsBase](https://github.com/datashield/dsBase) package [2].
+The `dsGamlss` package is a [DataSHIELD](https://www.datashield.org) server-side package that includes the server-side functions to fit Generalized Additive Models for Location, Scale and Shape (GAMLSS) [1] using DataSHIELD. It is based on the original [gamlss](https://cran.r-project.org/package=gamlss) implementation [1] and the [dsBase](https://github.com/datashield/dsBase) package [2]. For additional methodological details, please see our accompanying paper [3].
 
 ### DataSHIELD
 DataSHIELD is a software infrastructure which allows you to do non-disclosive federated analysis on sensitive data. The [DataSHIELD website](https://www.datashield.org) has in depth descriptions of what it is, how it works and how to install it. A key point to highlight is that DataSHIELD has a client-server infrastructure, so the `dsGamlss` package needs to be used in conjunction with the [dsGamlssClient](https://github.com/bips-hb/dsGamlssClient) package - trying to use one without the other makes no sense.
@@ -29,7 +29,7 @@ Detailed instructions on how to install DataSHIELD can be found at the [DataSHIE
 
 ## Installation
 
-If you want to use the sever-less DataSHIELD implementation [DSLite](https://cran.r-project.org/package=DSLite) [3], that is used in the example, you can install the `dsGamlss` package on your local machine from [GitHub](https://github.com/) with:
+If you want to use the sever-less DataSHIELD implementation [DSLite](https://cran.r-project.org/package=DSLite) [4], that is used in the example, you can install the `dsGamlss` package on your local machine from [GitHub](https://github.com/) with:
 
 ``` r
 # install.packages("devtools")
@@ -42,7 +42,26 @@ If you are working with real [Armadillo](https://molgenis.github.io/molgenis-ser
 Direct usage of the functions in this package is not recommended. Therefore, no example is provided. Instead, you should use the functions from the corresponding client-side package [dsGamlssClient](https://github.com/bips-hb/dsGamlssClient) to fit GAMLSS models with DataSHIELD and the `dsGamlssClient` package provides examples for that.
 
 ## References
-1. Rigby RA, Stasinopoulos DM. Generalized additive models for location, scale and shape. Journal of the Royal Statistical Society: Series C (Applied Statistics). 2005;54(3):507-54.
+1. Rigby RA, Stasinopoulos DM (2005). Generalized additive models for location, scale and shape. _Journal of the Royal Statistical Society: Series C (Applied Statistics)_ *54*(3):507-54.
 2. DataSHIELD Developers (2023). _dsBaseClient: DataSHIELD Client Functions_. R package version 6.3.0.
-3. Marcon Y (2022). _DSLite: 'DataSHIELD' Implementation on Local Datasets_. R package version 1.4.0, <https://CRAN.R-project.org/package=DSLite>.
+3. Swenne A, Intemann T, Moreno LA, Pigeot I (2025). _Federated generalized additive models for location, scale and shape. BMC Medical Research Methodology_ *25*(276).
+4. Marcon Y (2022). _DSLite: 'DataSHIELD' Implementation on Local Datasets_. R package version 1.4.0, <https://CRAN.R-project.org/package=DSLite>.
+
+## Citation
+If you use this package in your research, please cite if as follows:
+
+Swenne A, Intemann T, Moreno LA, Pigeot I (2025). Federated generalized additive models for location, scale and shape. _BMC Medical Research Methodology_, *25*(276). <https://doi.org/10.1186/s12874-025-02735-7>.
+
+
+```bibtex
+@Article{,
+  author = {Annika Swenne and Timm Intemann and Luis A. Moreno and Iris Pigeot},
+  title = {Federated generalized additive models for location, scale and shape},
+  journal = {BMC Medical Research Methodology},
+  volume = {25},
+  number = {276},
+  doi = {10.1186/s12874-025-02735-7},
+  year = {2025},
+}
+```
 

README.md

@@ -14,6 +14,8 @@ Generalized Additive Models for Location, Scale and Shape (GAMLSS) \[1\]
 using DataSHIELD. It is based on the original
 [gamlss](https://cran.r-project.org/package=gamlss) implementation \[1\]
 and the [dsBase](https://github.com/datashield/dsBase) package \[2\].
+For additional methodological details, please see our accompanying paper
+\[3\].
 
 ### DataSHIELD
 
@@ -33,7 +35,7 @@ Forum](https://datashield.discourse.group/)
 ## Installation
 
 If you want to use the sever-less DataSHIELD implementation
-[DSLite](https://cran.r-project.org/package=DSLite) \[3\], that is used
+[DSLite](https://cran.r-project.org/package=DSLite) \[4\], that is used
 in the example, you can install the `dsGamlss` package on your local
 machine from [GitHub](https://github.com/) with:
 
@@ -62,11 +64,34 @@ examples for that.
 
 ## References
 
-1.  Rigby RA, Stasinopoulos DM. Generalized additive models for
-    location, scale and shape. Journal of the Royal Statistical Society:
-    Series C (Applied Statistics). 2005;54(3):507-54.
+1.  Rigby RA, Stasinopoulos DM (2005). Generalized additive models for
+    location, scale and shape. *Journal of the Royal Statistical
+    Society: Series C (Applied Statistics)* *54*(3):507-54.
 2.  DataSHIELD Developers (2023). *dsBaseClient: DataSHIELD Client
     Functions*. R package version 6.3.0.
-3.  Marcon Y (2022). *DSLite: ‘DataSHIELD’ Implementation on Local
+3.  Swenne A, Intemann T, Moreno LA, Pigeot I (2025). *Federated
+    generalized additive models for location, scale and shape. BMC
+    Medical Research Methodology* *25*(276).
+4.  Marcon Y (2022). *DSLite: ‘DataSHIELD’ Implementation on Local
     Datasets*. R package version 1.4.0,
     <https://CRAN.R-project.org/package=DSLite>.
+
+## Citation
+
+If you use this package in your research, please cite if as follows:
+
+Swenne A, Intemann T, Moreno LA, Pigeot I (2025). Federated generalized
+additive models for location, scale and shape. *BMC Medical Research
+Methodology*, *25*(276). <https://doi.org/10.1186/s12874-025-02735-7>.
+
+``` bibtex
+@Article{,
+  author = {Annika Swenne and Timm Intemann and Luis A. Moreno and Iris Pigeot},
+  title = {Federated generalized additive models for location, scale and shape},
+  journal = {BMC Medical Research Methodology},
+  volume = {25},
+  number = {276},
+  doi = {10.1186/s12874-025-02735-7},
+  year = {2025},
+}
+```

inst/CITATION

@@ -1,8 +1,16 @@
 bibentry(
-  bibtype  = "Misc",
-  title    = "dsGamlss: DataSHIELD server-side functions to fit generalized additive models for location, scale and shape",
-  author   = "Annika Swenne",
-  year     = 2025,
-  url      = "https://github.com/bips-hb/dsGamlss",
-  note     = "R package version 0.1.0"
+  bibtype  = "Article",
+  author = c(
+    person("Annika", "Swenne"),
+    person("Timm", "Intemann"),
+    person(c("Luis", "A."), "Moreno"),
+    person("Iris", "Pigeot")),
+  title = "Federated generalized additive models for location, scale and shape",
+  journal = "BMC Medical Research Methodology",
+  volume = 25,
+  number = 276,
+  doi = "10.1186/s12874-025-02735-7",
+  year = "2025",
+  textVersion = "Swenne A, Intemann T, Moreno LA, Pigeot I (2025). Federated generalized additive models for location, scale and shape. BMC Medical Research Methodology,
+  25(276). https://doi.org/10.1186/s12874-025-02735-7."
 )