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Regression analysis in medical resea...

Cleophas, Ton J.

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Regression analysis in medical research = for Starters and 2nd Levelers /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Regression analysis in medical research/ by Ton J. Cleophas, Aeilko H. Zwinderman.
其他題名:	for Starters and 2nd Levelers /
作者:	Cleophas, Ton J.
其他作者:	Zwinderman, Aeilko H.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xv, 475 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Biometry. -
電子資源:	https://doi.org/10.1007/978-3-030-61394-5
ISBN:	9783030613945

Regression analysis in medical research = for Starters and 2nd Levelers /
Cleophas, Ton J.

Regression analysis in medical researchfor Starters and 2nd Levelers /[electronic resource] :by Ton J. Cleophas, Aeilko H. Zwinderman. - Second edition. - Cham :Springer International Publishing :2021. - xv, 475 p. :ill. (some col.), digital ;24 cm.

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.

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.

ISBN: 9783030613945

Standard No.: 10.1007/978-3-030-61394-5doiSubjects--Topical Terms:

531975
Biometry.

LC Class. No.: QA278.2 / .C54 2021

Dewey Class. No.: 519.536

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