Regression analysis in medical research: for starters and 2nd levelers / Ton J.Cleophas, Aeilko H.Zwinderman

Includes Chapter references

Includes Index

Continuous Outcome Regressions -- Dichotomous Outcome Regressions -- Confirmative Regressions -- Dichotomous Regressions Other Than Logistic and Cox -- Polytomous Outcome Regressions -- Time to Event Regressions Other Than Traditional Cox -- Analysis of Variance -- Repeated Outcomes Regression Methods -- Methodologies for Better Fit of Categorical Predictors -- Laplace Regressions, Multi-instead of Mono-exponential Regressions -- Regressions for Making Extrapolations -- Standardized Regression Coefficients -- Multi-Multivariate Analysis of Variance and Canonical Regression -- More on Poisson Regressions -- Regression Trend Testing -- Optimal Scaling and Automatic Linear Regression -- Spline Regression Modeling -- More on Nonlinear Regressions -- Special Forms of Continuous Outcomes Regressions -- Regressions for Quantitative Diagnostic Testing -- Regressions, a Panacee or at Least a Widespread Help for Data Analyses -- Regression Trees -- Regressions with Latent Variables -- Partial Correlations -- Functional Data Analysis I -- Functional Data Analysis II -- References -- Index

This edition is a pretty complete textbook and tutorial for medical and health care students, as well as a recollection/update bench, and help desk for professionals. Novel approaches already applied in published clinical research will be addressed: matrix analyses, alpha spending, gate keeping, kriging, interval censored regressions, causality regressions, canonical regressions, quasi-likelihood regressions, novel non-parametric regressions. Each chapter can be studied as a stand-alone, and covers one field in the fast growing world of regression analyses.
The authors, as professors in statistics and machine learning at European universities, are worried, that their students find regression-analyses harder than any other methodology in statistics. This is serious, because almost all of the novel methodologies in current data mining and data analysis include elements of regression-analysis.