Modern Survival Analysis in Clinical Research: Cox Regressions Versus Accelerated Failure Time Models

Preface
Contents
Chapter 1: Regression Analysis
	1.1 Introduction
	1.2 History
	1.3 Methodologies of Regression Analysis
		1.3.1 Linear Regression
		1.3.2 Logistic Regression
		1.3.3 Cox Regression
	1.4 Conclusion
	References
Chapter 2: Cox Regressions
	2.1 Introduction
	2.2 History of Cox Regressions
	2.3 Principles of Cox Regressions
	2.4 Conclusion
	References
Chapter 3: Accelerated Failure Time Models
	3.1 Introduction
	3.2 History of Failure Time Models
	3.3 Methodology of Failure Time Models
	3.4 Graphs of Successful Functions to Analyze Accelerated Failure Time Models
	3.5 Conclusion
	References
Chapter 4: Simple Dataset with Event as Outcome and Treatment as Predictor
	4.1 Introduction
	4.2 Data Example
	4.3 Data Analysis in SPSS Statistical Software Version 29
	4.4 Cox Regression
	4.5 Accelerated Failure Time with Weibull Distribution
	4.6 Accelerated Failure Time Model with Exponential Distribution
	4.7 Accelerated Failure Time Model with Log Normal Distribution
	4.8 Accelerated Failure Time Model with Log Logistic Distribution
	4.9 Conclusion
	References
Chapter 5: Simple Dataset with Death as Outcome and Treatment Modality, Cholesterol, and Age as Predictors
	5.1 Introduction
	5.2 Data Example
	5.3 Data Analysis in SPSS Statistical Software Version 29
	5.4 Three Predictors Cox Regression
	5.5 Three Predictors Accelerated Failure Time (AFT) with Weibull Distribution
	5.6 Three Predictors Accelerated Failure Time Model with Exponential Distribution
	5.7 Three Predictors Accelerated Failure Time with Log Normal Distribution
	5.8 Three Predictors Accelerated Failure Time with Log Logistic Distribution
	5.9 Conclusion
	References
Chapter 6: Glioma Brain Cancer
	6.1 Introduction
	6.2 Data Example
	6.3 Data Analysis in SPSS Statistical Software Version 29
	6.4 Cox Regression
	6.5 Accelerated Failure Time (AFT) Model with Weibull Distribution
	6.6 The Accelerated Failure Time (AFT) with Exponential Distribution
	6.7 Accelerated Failure Time (AFT) with Log Normal Distribution
	6.8 Accelerated Failure Time with Log-logistic Distribution
	6.9 Conclusion
	References
Chapter 7: Linoleic Acid for Colonic Carcinoma
	7.1 Introduction
	7.2 Data Example
	7.3 Data Analysis in SPSS Statistical Software Version 29
	7.4 Cox Regression
	7.5 Accelerated Failure Time (AFT) with Weibull Distribution
	7.6 Accelerated Failure Time (AFT) with Exponential Distribution
	7.7 Accelerated Failure Time (AFT) with Log Normal Distribution
	7.8 Accelerated Failure Time (AFT) with Log Logistic Distribution
	7.9 Conclusion
	References
Chapter 8: The Effect on Survival of Maintained Chemotherapy with Acute Myelogenous Leucemia
	8.1 Introduction
	8.2 Data Example
	8.3 Data Analysis in SPSS Statistical Software Version 29
	8.4 Cox Regression
	8.5 Accelerated Failure Time (AFT) with Weibull Distribution
	8.6 Accelerated Failure Time (AFT) with Exponential Distribution
	8.7 Accelerated Failure Time (AFT) with Log Normal Distribution
	8.8 Accelerated Failure Time (AFT) with Log Logistic Distribution
	8.9 Conclusion
	References
Chapter 9: Eighty Four Month Parallel Group Mortality Study
	9.1 Introduction
	9.2 Data Example
	9.3 Data Analysis in SPSS Statistical Software Version 29
	9.4 Cox Regression
	9.5 Accelerated Failure Time (AFT) Model with the Weibull Distribution
	9.6 Accelerated Failure Time (AFT) Model with the Exponential Distribution
	9.7 Accelerated Failure Time (AFT) Model with the Log Normal Distribution
	9.8 Accelerated Failure Time (AFT) Model with Log Logistic Distribution
	9.9 Conclusion
	References
Chapter 10: The Effect on Survival from Stages 1 and 2 Histiocytic Lymphoma
	10.1 Introduction
	10.2 Data Example
	10.3 Data Analysis Using SPSS Statistical Software Version 29
	10.4 Cox Regression
	10.5 Accelerated Failure Time (AFT) with Weibull Distribution
	10.6 Accelerated Failure Time (AFT) with Exponential Distribution
	10.7 Accelerated Failure Time (AFT) with Log Normal Distribution
	10.8 Accelerated Failure Time (AFT) with Log Logistic Distribution
	10.9 Conclusion
	References
Chapter 11: Survival of 64 Lymphoma Patients with or Without B Symptoms
	11.1 Introduction
	11.2 Data Example
	11.3 Data Analysis in SPSS Statistical Software Version 29
	11.4 Cox Regression
	11.5 Accelerated Failure Time (AFT) Model with Weibull Distribution
	11.6 Accelerated Failure Time (AFT) Model with Exponential Distribution
	11.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution
	11.8 Accelerated Failure Time (AFT) Model with Log Logistic Distribution
	11.9 Conclusion
	References
Chapter 12: Effect on Time-to-Event of Group Membership
	12.1 Introduction
	12.2 Data Example
	12.3 Data Analysis Using SPSS Statistical Software Version 29
	12.4 Cox Regression
	12.5 Accelerated Failure Time (AFT) Model with Weibull Distribution
	12.6 Accelerated Failure Time (AFT) with Exponential Distribution
	12.7 Accelerated Failure Time (AFT) with Log Normal Distribution
	12.8 Accelerated Failure Time (AFT) with Log Logistic Distribution
	12.9 Conclusion
	References
Chapter 13: The Effect on Survival of Group Membership
	13.1 Introduction
	13.2 Data Example
	13.3 Data Analysis Using SPSS Statistical Software Version 29
	13.4 Cox Regression
	13.5 Accelerated Failure Time (AFT) Models with Weibull Distribution
	13.6 Accelerated Failure Time (AFT) Models with Exponential Distribution
	13.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution
	13.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution
	13.9 Conclusion
	References
Chapter 14: Deaths from Carcinoma After Exposure to Carcinogens in Rats
	14.1 Introduction
	14.2 Data Example
	14.3 Data Analysis Using SPSS Statistical Software Version 29
	14.4 Cox Regression
	14.5 Accelerated Failure Time (AFT) Model with Weibull Distribution
	14.6 Accelerated Failure Time (AFT) Model with Exponential Distribution
	14.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution
	14.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution
	14.9 Conclusion
	References
Chapter 15: Effect of Group Membership on Survival
	15.1 Introduction
	15.2 Data Example
	15.3 Data Analysis Using SPSS Statistical Software Version 29
	15.4 Cox Regression
	15.5 Accelerated Failure Time (AFT) Models with Weibull Distribution
	15.6 Accelerated Failure Time (AFT) Model with Exponential Distribution
	15.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution
	15.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution
	15.9 Conclusion
	References
Chapter 16: Multiple Variables Regression Study of 2421 Stroke Patients Assessed for Time to Second Stroke
	16.1 Introduction and Data Example
	16.2 Data Analysis in SPSS Statistical Software Version 29
	16.3 Cox Regression
	16.4 Accelerated Failure Time (AFT) with Weibull Distribution
	16.5 Accelerated Failure Time (AFT) with Exponential Distribution
	16.6 Accelerated Failure Time (AFT) with Log Normal Distribution
	16.7 Accelerated Failure Time (AFT) with Log Logistic Distribution
	16.8 Conclusion
	References
Chapter 17: Hypothesized 55 Patient Study of Effect of Treatment Modality on Survival
	17.1 Introduction
	17.2 Data Example
	17.3 Data Analysis Using SPSS Statistical Software Version 29
	17.4 Cox Regression
	17.5 Accelerated Failure Time (AFT) with Weibull’s Distribution
	17.6 Accelerated Failure Time (AFT) with Exponential Distribution
	17.7 Acccelerated Failure Time (AFT) with Log Normal Distribution
	17.8 Accelerated Failure Time (AFT) with Log Logistic Distribution
	17.9 Conclusion
	References
Chapter 18: One Year Follow-Up Study with Many Censored Patients
	18.1 Introduction
	18.2 Data Example
	18.3 Data Analysis Using SPSS Statistical Software Version 29
	18.4 Cox Regression
	18.5 Accelerated Failure Time (AFT) with Weibull Distribution
	18.6 Accelerated Failure Time (AFT) Model with Exponential Distribution
	18.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution
	18.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution
	18.9 Conclusion
	References
Chapter 19: Alcohol Relapse After Detox Program Treated with or Without a Personal Coach
	19.1 Introduction
	19.2 Data Example
	19.3 Data Analysis Using SPSS Statistical Software Version 29
	19.4 Cox Regression
	19.5 Accelerated Failure Time (AFT) Models with Weibull Distribution
	19.6 Accelerated Failure Times (AFT) Model with Exponential Distribution
	19.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution
	19.8 Accelerated Failure Times (AFT) Model with Log Logistics Distribution
	19.9 Conclusion
	References
Chapter 20: Alcohol Relapse After Detox Program with 3 Predictors
	20.1 Introduction
	20.2 Data Example
	20.3 Data Analysis Using SPSS Statistical Software Version 29
	20.4 Cox Regression
	20.5 Accelerated Failure Time (AFT) Model with Weibull Distribution
	20.6 Accelerated Failure Time Model with Exponential Distribution
	20.7 Accelerated Failure Time (AFT) with Log Normal Distribution
	20.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution
	20.9 Conclusion
	References
Chapter 21: Ayurvedic Therapy for Human Immunodeficiency Virus
	21.1 Introduction
	21.2 Data Example
	21.3 Data Analysis Using SPSS Statistical Software Version 29
	21.4 Cox Regression
	21.5 Accelerated Failure Time (AFT) Model with Weibull Distribution
	21.6 Accelerated Failure Time (AFT) Model with Exponential Distribution
	21.7 Accelerated Failure Time (AFT) Model with Log Normal Distribution
	21.8 Accelerated Failure Time (AFT) Model with Log Logistics Distribution
	21.9 Conclusion
	References
Chapter 22: Time to Event Regressions Other Than Cox Regressions
	22.1 Introduction
	22.2 Cox with Time Dependent Predictors
	22.3 Segmented Cox
	22.4 Interval Censored Regressions
	22.5 Autocorrelations
	22.6 Polynomial Regressions
	22.7 Conclusion
	References
Chapter 23: Abstracts of the Chapters 1 to 22
	References