Quantile Regression in Clinical Research: Complete analysis for data at a loss of homogeneity

Preface
Contents
Chapter 1: General Introduction
	1.1 Summary
	1.2 Introduction
	1.3 Principle of Regression Analysis
	1.4 Principle of Quantile Regression
	1.5 History and Background of Quantile Regression
	1.6 Data Example
	1.7 Separating Quantiles, Traditional and Quantile-wise
	1.8 Special Case
	1.9 Quantile Regression Both for Continuous and Discrete Outcome Variables
	1.10 References
Chapter 2: Mathematical Models for Separating Quantiles from One Another
	2.1 Summary
	2.2 Introduction
	2.3 Maximizing Linear Functions with the Help of Support Vectors
	2.4 Lagrangian Multiplier Method
	2.5 Maximizing Linear Functions with the Help of Rectangles
	2.6 Maximizing Linear Functions with the Help of Simplex Algorithms
	2.7 The Intuition of Quantile Regression
	2.8 Special Case
	2.9 Traditional Statistical Methods Applied in This Edition
	2.10 Conclusions
	2.11 References
Part I: Simple Univariate Regressions Versus Quantile
	Chapter 3: Traditional and Robust Regressions Versus Quantile
		3.1 Summary
		3.2 Introduction
		3.3 Traditional and Robust Regression
		3.4 Quantile Regressions
		3.5 Conclusion
		3.6 References
	Chapter 4: Autocorrelations Versus Quantile Regressions
		4.1 Summary
		4.2 Introduction
		4.3 Autoregression Analysis
		4.4 Quantile Regressions
		4.5 Conclusions
		4.6 References
	Chapter 5: Discrete Trend Testing Versus Quantile Regression
		5.1 Summary
		5.2 Introduction
		5.3 Discrete Trend Analysis
		5.4 Quantile Regressions
		5.5 Conclusion
		5.6 References
	Chapter 6: Continuous Trend Testing Versus Quantile Regression
		6.1 Summary
		6.2 Introduction
		6.3 Linear Trend Testing of Continuous Data
		6.4 Quantile Regressions
		6.5 Conclusion
		6.6 References
	Chapter 7: Binary Poisson/Negative Binomial Regressions Versus Quantile
		7.1 Summary
		7.2 Introduction
		7.3 Binary Poisson and Negative Binomial Regressions
		7.4 Quantile Regressions
		7.5 Conclusion
		7.6 References
	Chapter 8: Robust Standard Errors Regressions Versus Quantile
		8.1 Summary
		8.2 Introduction
		8.3 Robust Standard Errors
		8.4 Quantile Regressions
		8.5 Conclusion
		8.6 References
	Chapter 9: Optimal Scaling Versus Quantile Regression
		9.1 Summary
		9.2 Introduction
		9.3 Optimal Scaling
		9.4 Quantile Regression
		9.5 Conclusions
		9.6 References
	Chapter 10: Intercept only Poisson Regression Versus Quantile
		10.1 Summary
		10.2 Introduction
		10.3 Poisson Intercept Only
		10.4 Quantile Regressions
		10.5 Conclusion
		10.6 References
Part II: Multiple Variables Regressions Versus Quantile
	Chapter 11: Four Predictors Regressions Versus Quantile
		11.1 Summary
		11.2 Introduction
		11.3 Four Predictors Regressions
		11.4 Quantile Regressions
		11.5 Conclusion
		11.6 References
	Chapter 12: Gene Expressions Regressions, Traditional Versus Quantile
		12.1 Summary
		12.2 Introduction
		12.3 Gene Expressions Regression
		12.4 Quantile Regressions
		12.5 Conclusion
		12.6 References
	Chapter 13: Koenker´s Multiple Variables Analysis with Quantile Modeling
		13.1 Summary
		13.2 Introduction
		13.3 SAS Statistical Software Graphs Interpreted
		13.4 First Four Graphs
		13.5 The Second Set of Four Graphs
		13.6 The Third Set of Four Graphs
		13.7 The Fourth Set of Four Graphs
		13.8 Conclusion
		13.9 References
	Chapter 14: Interaction Adjusted Regression Versus Quantile
		14.1 Summary
		14.2 Introduction
		14.3 Interaction Adjusted Regression
		14.4 Quantile Regressions
		14.5 Conclusion
		14.6 References
	Chapter 15: Quantile Regression to Study Corona Deaths
		15.1 Summary
		15.2 Introduction
		15.3 Methods and Main Results
		15.4 Conclusion
		15.5 References
	Chapter 16: Laboratory Values Predict Survival Sepsis, Traditional Regression Versus Quantile
		16.1 Summary
		16.2 Introduction
		16.3 Traditional Regression
		16.4 Quantile Regressions
		16.5 Conclusion
		16.6 References
	Chapter 17: Multinomial Regression Versus Quantile
		17.1 Summary
		17.2 Introduction
		17.3 Multinomial Regressions and More
		17.4 Quantile Regressions
		17.5 Conclusions
		17.6 References
	Chapter 18: Regressions with Inconstant Variability, Traditional and Weighted Least Squares Analysis Versus Quantile
		18.1 Summary
		18.2 Introduction
		18.3 Regressions with Inconstant Variability
		18.4 Quantile Regressions
		18.5 Conclusion
		18.6 References
	Chapter 19: Restructuring Categories into Multiple Binary Variables Versus Quantile Regressions
		19.1 Summary
		19.2 Introduction
		19.3 Traditional Multiple Regression After Restructuring Predictive Categories into Multiple Binary Variables
		19.4 Quantile Regressions
		19.5 Conclusion
		19.6 References
	Chapter 20: Poisson Events per Person per Period of Time Versus Quantile Regression
		20.1 Summary
		20.2 Introduction
		20.3 3. Poisson Events per Person per Period of Time
		20.4 Quantile Regression
		20.5 Conclusion
		20.6 References
Part III: Special Regressions Versus Quantile
	Chapter 21: Two Stage Least Squares Analysis Versus Quantile
		21.1 Summary
		21.2 Introduction
		21.3 Two Stage Least Squares (SLS)
		21.4 Quantile Regressions
		21.5 Conclusion
		21.6 References
	Chapter 22: Partial Correlations Versus Quantile Regressions
		22.1 Summary
		22.2 Introduction
		22.3 Partial Correlations
		22.4 Quantile Regressions
		22.5 Conclusions
		22.6 References
	Chapter 23: Random Intercepts Regression Versus Quantile
		23.1 Summary
		23.2 Introduction
		23.3 Random Intercept Regression
		23.4 Quantile Regressions
		23.5 Quantile Regression with Intercept Included
		23.6 Conclusion
		23.7 References
	Chapter 24: Regression Trees Versus Quantile Regression
		24.1 Summary
		24.2 Introduction
		24.3 Regression Trees
		24.4 Quantile Regressions
		24.5 Conclusions
		24.6 References
	Chapter 25: Kernel Regression Versus Quantile Regression
		25.1 Summary
		25.2 Introduction
		25.3 Kernel Regression
		25.4 Quantile Regressions
		25.5 Conclusions
		25.6 References
	Chapter 26: Quasi-likelihood Regressions vs Quantile
		26.1 Summary
		26.2 Introduction
		26.3 Quasi-likelihood Regressions
		26.4 Quantile Regressions
		26.5 Conclusion
		26.6 References
	Chapter 27: Summaries
Index