Regression Analysis in Medical Research : for Starters and 2nd Levelers / by Ton J. Cleophas, Aeilko H. Zwinderman.

Format:

Book

Author/Creator:

Cleophas, Ton J., Author.

Zwinderman, Aeilko H., Author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Language:

English

Subjects (All):

Biometry.

Medical sciences.

Biostatistics.

Health Sciences.

Local Subjects:

Biostatistics.

Health Sciences.

Physical Description:

1 online resource (XV, 475 pages) : 482 illustrations, 72 illustrations in color.

Edition:

2nd ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

Regression analysis of cause effect relationships is increasingly the core of medical and health research. This work is a 2nd edition of a 2017 pretty complete textbook and tutorial for students as well as recollection / update bench and help desk for professionals. It came to the authors' attention, that information of history, background, and purposes, of the regression methods addressed were scanty. Lacking information about all of that has now been entirely covered. The editorial art work of the first edition, however pretty, was less appreciated by some readerships, than were the original output sheets from the statistical programs as used. Therefore, the editorial art work has now been systematically replaced with original statistical software tables and graphs for the benefit of an improved usage and understanding of the methods. In the past few years, professionals have been flooded with big data. The Covid-19 pandemic gave cause for statistical software companies to foster novel analytic programs better accounting outliers and skewness. Novel fields of regression analysis adequate for such data, like sparse canonical regressions and quantile regressions, have been included. .

Contents:

Preface

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 (ANOVA)

Repeated Outcomes Regression Methods

Methodologies for Better Fit of Categorical Predictors

Laplace Regressions, Multi- instead of Mono-Exponential Models

Regressions For Making Extrapolations.

Standardized Regression Coefficients

Multivariate Analysis of Variance and Canonical Regression

More on Poisson Regressions

Regression Trend Testing

Optimal Scaling and Automatic Linear Regression

Spline Regressions

More on Nonlinear Regressions

Special Forms of Continuous Outcome 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 Basis

Functional Data Analysis Advanced

Quantile Regression

Index. .

Other Format:

Printed edition:

ISBN:

978-3-030-61394-5

9783030613945

Access Restriction:

Restricted for use by site license.