diff --git a/DESCRIPTION b/DESCRIPTION index dbbbb0b..0a55cf2 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: contsurvplot Title: Visualize the Effect of a Continuous Variable on a Time-to-Event Outcome -Version: 0.2.0.9000 +Version: 0.2.1 Authors@R: person("Robin", "Denz", , "robin.denz@rub.de", role = c("aut", "cre")) Maintainer: Robin Denz diff --git a/NEWS.md b/NEWS.md index 9c79994..e4fdec0 100644 --- a/NEWS.md +++ b/NEWS.md @@ -24,3 +24,9 @@ New Features: * Added support for plotting Kaplan-Meier curves as reference in `plot_surv_area`, `plot_surv_animated`, `plot_surv_lines` * Added the `monotonic` argument in the `plot_surv_area` function to allow plotting curved relationships * Vignette now includes `plot_surv_matrix` function + +# contsurvplot 0.2.1 + +Documentation: + +* Updated citation information to include published manuscript diff --git a/codemeta.json b/codemeta.json index c68f638..0c6cf4e 100644 --- a/codemeta.json +++ b/codemeta.json @@ -2,13 +2,13 @@ "@context": "https://doi.org/10.5063/schema/codemeta-2.0", "@type": "SoftwareSourceCode", "identifier": "contsurvplot", - "description": "Graphically display the (causal) effect of a continuous variable on a time-to-event outcome using multiple different types of plots based on g-computation. Those functions include, among others, survival area plots, survival contour plots, survival quantile plots and 3D surface plots. Due to the use of g-computation, all plot allow confounder-adjustment naturally. For details, see Robin Denz, Nina Timmesfeld (2022) .", + "description": "Graphically display the (causal) effect of a continuous variable on a time-to-event outcome using multiple different types of plots based on g-computation. Those functions include, among others, survival area plots, survival contour plots, survival quantile plots and 3D surface plots. Due to the use of g-computation, all plot allow confounder-adjustment naturally. For details, see Robin Denz, Nina Timmesfeld (2023) .", "name": "contsurvplot: Visualize the Effect of a Continuous Variable on a Time-to-Event Outcome", "relatedLink": "https://robindenz1.github.io/contsurvplot/", "codeRepository": "https://github.com/RobinDenz1/contsurvplot", "issueTracker": "https://github.com/RobinDenz1/contsurvplot/issues", "license": "https://spdx.org/licenses/GPL-3.0", - "version": "0.2.0", + "version": "0.2.1", "programmingLanguage": { "@type": "ComputerLanguage", "name": "R", @@ -249,11 +249,11 @@ }, "SystemRequirements": null }, - "fileSize": "12127.977KB", + "fileSize": "15256.628KB", "citation": [ { "@type": "ScholarlyArticle", - "datePublished": "2022", + "datePublished": "2023", "author": [ { "@type": "Person", @@ -266,14 +266,16 @@ "familyName": "Timmesfeld" } ], - "name": "Visualizing the Causal Effect of a Continuous Variable on a Time-To-Event Outcome", - "description": "R package version 0.2.0", + "name": "Visualizing the (Causal) Effect of a Continuous Variable on a Time-To-Event Outcome", + "url": "https://doi.org/10.1097/EDE.0000000000001630", "isPartOf": { "@type": "PublicationIssue", - "datePublished": "2022", + "issueNumber": "5", + "datePublished": "2023", "isPartOf": { "@type": ["PublicationVolume", "Periodical"], - "name": "arXiv:2208.04644v1" + "volumeNumber": "34", + "name": "Epidemiology" } } }