21 參考文獻

本書參考的主要文獻與延伸閱讀資源列於下方。

21.1 統計學經典教材

Casella, G., & Berger, R. L. (2002). Statistical Inference (2nd ed.). Duxbury Press.
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). Chapman and Hall/CRC.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer.

21.2 醫學統計專書

Collett, D. (2015). Modelling Survival Data in Medical Research (3rd ed.). Chapman and Hall/CRC.
Hosmer, D. W., Lemeshow, S., & May, S. (2008). Applied Survival Analysis: Regression Modeling of Time-to-Event Data (2nd ed.). Wiley.
Armitage, P., Berry, G., & Matthews, J. N. S. (2001). Statistical Methods in Medical Research (4th ed.). Blackwell Science.

21.3 微積分教材

Stewart, J. (2015). Calculus: Early Transcendentals (8th ed.). Cengage Learning.
Thomas, G. B., Weir, M. D., & Hass, J. R. (2018). Thomas’ Calculus (14th ed.). Pearson.

21.4 R 語言與資料視覺化

Wickham, H., & Grolemund, G. (2016). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media.
Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis (2nd ed.). Springer.
Chang, W. (2018). R Graphics Cookbook: Practical Recipes for Visualizing Data (2nd ed.). O’Reilly Media.

21.5 線上資源

ggplot2 官方文件：https://ggplot2.tidyverse.org/
R for Data Science 線上版：https://r4ds.had.co.nz/
The Comprehensive R Archive Network (CRAN)：https://cran.r-project.org/
Quarto 官方文件：https://quarto.org/

21.6 統計軟體與工具

R Core Team (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
RStudio Team (2024). RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA.

21.7 補充讀物

McElreath, R. (2020). Statistical Rethinking: A Bayesian Course with Examples in R and Stan (2nd ed.). CRC Press.
Kleinbaum, D. G., & Klein, M. (2012). Survival Analysis: A Self-Learning Text (3rd ed.). Springer.
Rosner, B. (2015). Fundamentals of Biostatistics (8th ed.). Cengage Learning.

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title: "參考文獻"
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本書參考的主要文獻與延伸閱讀資源列於下方。

## 統計學經典教材

1. Casella, G., & Berger, R. L. (2002). *Statistical Inference* (2nd ed.). Duxbury Press.

2. Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). *Bayesian Data Analysis* (3rd ed.). Chapman and Hall/CRC.

3. Hastie, T., Tibshirani, R., & Friedman, J. (2009). *The Elements of Statistical Learning: Data Mining, Inference, and Prediction* (2nd ed.). Springer.

## 醫學統計專書

4. Collett, D. (2015). *Modelling Survival Data in Medical Research* (3rd ed.). Chapman and Hall/CRC.

5. Hosmer, D. W., Lemeshow, S., & May, S. (2008). *Applied Survival Analysis: Regression Modeling of Time-to-Event Data* (2nd ed.). Wiley.

6. Armitage, P., Berry, G., & Matthews, J. N. S. (2001). *Statistical Methods in Medical Research* (4th ed.). Blackwell Science.

## 微積分教材

7. Stewart, J. (2015). *Calculus: Early Transcendentals* (8th ed.). Cengage Learning.

8. Thomas, G. B., Weir, M. D., & Hass, J. R. (2018). *Thomas' Calculus* (14th ed.). Pearson.

## R 語言與資料視覺化

9. Wickham, H., & Grolemund, G. (2016). *R for Data Science: Import, Tidy, Transform, Visualize, and Model Data*. O'Reilly Media.

10. Wickham, H. (2016). *ggplot2: Elegant Graphics for Data Analysis* (2nd ed.). Springer.

11. Chang, W. (2018). *R Graphics Cookbook: Practical Recipes for Visualizing Data* (2nd ed.). O'Reilly Media.

## 線上資源

12. ggplot2 官方文件：[https://ggplot2.tidyverse.org/](https://ggplot2.tidyverse.org/)

13. R for Data Science 線上版：[https://r4ds.had.co.nz/](https://r4ds.had.co.nz/)

14. The Comprehensive R Archive Network (CRAN)：[https://cran.r-project.org/](https://cran.r-project.org/)

15. Quarto 官方文件：[https://quarto.org/](https://quarto.org/)

## 統計軟體與工具

16. R Core Team (2024). *R: A Language and Environment for Statistical Computing*. R Foundation for Statistical Computing, Vienna, Austria.

17. RStudio Team (2024). *RStudio: Integrated Development Environment for R*. Posit Software, PBC, Boston, MA.

## 補充讀物

18. McElreath, R. (2020). *Statistical Rethinking: A Bayesian Course with Examples in R and Stan* (2nd ed.). CRC Press.

19. Kleinbaum, D. G., & Klein, M. (2012). *Survival Analysis: A Self-Learning Text* (3rd ed.). Springer.

20. Rosner, B. (2015). *Fundamentals of Biostatistics* (8th ed.). Cengage Learning.