10 참고문헌

참고문헌

이 책은 다음 자료들을 참고하여 작성되었습니다.

10.1 주요 참고 도서

Wickham, H., & Grolemund, G. (2017). R for Data Science. O’Reilly Media. https://r4ds.hadley.nz/
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis (3rd ed.). Springer. https://ggplot2-book.org/
Healy, K. (2018). Data Visualization: A Practical Introduction. Princeton University Press.
Moraga, P. (2019). Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny. Chapman and Hall/CRC.
Batra, N., et al. (2021). The Epidemiologist R Handbook. https://epirhandbook.com/

10.2 R 패키지

10.2.1 시각화

Wickham, H. (2016). ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. https://CRAN.R-project.org/package=ggplot2
Pedersen, T. L. (2024). patchwork: The Composer of Plots. https://CRAN.R-project.org/package=patchwork
Slowikowski, K. (2024). ggrepel: Automatically Position Non-Overlapping Text Labels. https://CRAN.R-project.org/package=ggrepel
Kassambara, A. (2023). ggpubr: ‘ggplot2’ Based Publication Ready Plots. https://CRAN.R-project.org/package=ggpubr

10.2.2 역학 분석

Jombart, T., et al. (2022). incidence2: Compute, Handle and Plot Incidence. https://CRAN.R-project.org/package=incidence2
Donegan, C. (2022). surveil: Public Health Surveillance. https://CRAN.R-project.org/package=surveil

10.2.3 공간 분석

Pebesma, E. (2018). Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal, 10(1), 439-446. https://doi.org/10.32614/RJ-2018-009
Tennekes, M. (2018). tmap: Thematic Maps in R. Journal of Statistical Software, 84(6), 1-39. https://doi.org/10.18637/jss.v084.i06

10.2.4 임상 통계

Therneau, T. (2024). survival: Survival Analysis. https://CRAN.R-project.org/package=survival
Sjoberg, D. D., et al. (2023). ggsurvfit: Flexible Time-to-Event Figures. https://CRAN.R-project.org/package=ggsurvfit
Viechtbauer, W. (2010). Conducting Meta-Analyses in R with the metafor Package. Journal of Statistical Software, 36(3), 1-48. https://doi.org/10.18637/jss.v036.i03

10.2.5 대화형 시각화

Sievert, C. (2020). Interactive Web-Based Data Visualization with R, plotly, and shiny. Chapman and Hall/CRC. https://plotly-r.com/
Chang, W., et al. (2024). shiny: Web Application Framework for R. https://CRAN.R-project.org/package=shiny

10.3 웹 리소스

10.3.1 튜토리얼

R Graph Gallery. https://r-graph-gallery.com/
From Data to Viz. https://www.data-to-viz.com/
Cedric Scherer’s ggplot2 Tutorial. https://www.cedricscherer.com/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/

10.3.2 커뮤니티

RStudio Community. https://community.rstudio.com/
Stack Overflow (R tag). https://stackoverflow.com/questions/tagged/r
R-Bloggers. https://www.r-bloggers.com/

10.3.3 데이터 소스

통계지리정보서비스(SGIS). https://sgis.kostat.go.kr/
질병관리청 감염병포털. https://npt.kdca.go.kr/
Our World in Data. https://ourworldindata.org/

10.4 학술 논문

Wilkinson, L. (2005). The Grammar of Graphics (2nd ed.). Springer.
Tufte, E. R. (2001). The Visual Display of Quantitative Information (2nd ed.). Graphics Press.
Cleveland, W. S., & McGill, R. (1984). Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. Journal of the American Statistical Association, 79(387), 531-554.
Friendly, M. (2008). A Brief History of Data Visualization. In C. Chen, W. Härdle, & A. Unwin (Eds.), Handbook of Data Visualization (pp. 15-56). Springer.

BibTeX 파일

전체 참고문헌 목록은 references.bib 파일에서 확인할 수 있습니다.

--- title: "참고문헌" --- # 참고문헌 {.unnumbered} 이 책은 다음 자료들을 참고하여 작성되었습니다. ## 주요 참고 도서 1. Wickham, H., & Grolemund, G. (2017). *R for Data Science*. O'Reilly Media. <https://r4ds.hadley.nz/> 2. Wickham, H. (2016). *ggplot2: Elegant Graphics for Data Analysis* (3rd ed.). Springer. <https://ggplot2-book.org/> 3. Healy, K. (2018). *Data Visualization: A Practical Introduction*. Princeton University Press. 4. Moraga, P. (2019). *Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny*. Chapman and Hall/CRC. 5. Batra, N., et al. (2021). *The Epidemiologist R Handbook*. <https://epirhandbook.com/> ## R 패키지 ### 시각화 - Wickham, H. (2016). ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. <https://CRAN.R-project.org/package=ggplot2> - Pedersen, T. L. (2024). patchwork: The Composer of Plots. <https://CRAN.R-project.org/package=patchwork> - Slowikowski, K. (2024). ggrepel: Automatically Position Non-Overlapping Text Labels. <https://CRAN.R-project.org/package=ggrepel> - Kassambara, A. (2023). ggpubr: 'ggplot2' Based Publication Ready Plots. <https://CRAN.R-project.org/package=ggpubr> ### 역학 분석 - Jombart, T., et al. (2022). incidence2: Compute, Handle and Plot Incidence. <https://CRAN.R-project.org/package=incidence2> - Donegan, C. (2022). surveil: Public Health Surveillance. <https://CRAN.R-project.org/package=surveil> ### 공간 분석 - Pebesma, E. (2018). Simple Features for R: Standardized Support for Spatial Vector Data. *The R Journal*, 10(1), 439-446. <https://doi.org/10.32614/RJ-2018-009> - Tennekes, M. (2018). tmap: Thematic Maps in R. *Journal of Statistical Software*, 84(6), 1-39. <https://doi.org/10.18637/jss.v084.i06> ### 임상 통계 - Therneau, T. (2024). survival: Survival Analysis. <https://CRAN.R-project.org/package=survival> - Sjoberg, D. D., et al. (2023). ggsurvfit: Flexible Time-to-Event Figures. <https://CRAN.R-project.org/package=ggsurvfit> - Viechtbauer, W. (2010). Conducting Meta-Analyses in R with the metafor Package. *Journal of Statistical Software*, 36(3), 1-48. <https://doi.org/10.18637/jss.v036.i03> ### 대화형 시각화 - Sievert, C. (2020). *Interactive Web-Based Data Visualization with R, plotly, and shiny*. Chapman and Hall/CRC. <https://plotly-r.com/> - Chang, W., et al. (2024). shiny: Web Application Framework for R. <https://CRAN.R-project.org/package=shiny> ## 웹 리소스 ### 튜토리얼 - R Graph Gallery. <https://r-graph-gallery.com/> - From Data to Viz. <https://www.data-to-viz.com/> - Cedric Scherer's ggplot2 Tutorial. <https://www.cedricscherer.com/2019/08/05/a-ggplot2-tutorial-for-beautiful-plotting-in-r/> ### 커뮤니티 - RStudio Community. <https://community.rstudio.com/> - Stack Overflow (R tag). <https://stackoverflow.com/questions/tagged/r> - R-Bloggers. <https://www.r-bloggers.com/> ### 데이터 소스 - 통계지리정보서비스(SGIS). <https://sgis.kostat.go.kr/> - 질병관리청 감염병포털. <https://npt.kdca.go.kr/> - Our World in Data. <https://ourworldindata.org/> ## 학술 논문 1. Wilkinson, L. (2005). *The Grammar of Graphics* (2nd ed.). Springer. 2. Tufte, E. R. (2001). *The Visual Display of Quantitative Information* (2nd ed.). Graphics Press. 3. Cleveland, W. S., & McGill, R. (1984). Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods. *Journal of the American Statistical Association*, 79(387), 531-554. 4. Friendly, M. (2008). A Brief History of Data Visualization. In C. Chen, W. Härdle, & A. Unwin (Eds.), *Handbook of Data Visualization* (pp. 15-56). Springer. --- ::: {.callout-note} ## BibTeX 파일 전체 참고문헌 목록은 `references.bib` 파일에서 확인할 수 있습니다. :::