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Basic principles of applied medical statistics = a practical guide /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Basic principles of applied medical statistics/ by Jos W. R. Twisk.
Reminder of title:	a practical guide /
Author:	Twisk, Jos W. R.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xii, 268 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	- 1. Introduction -- 2. Descriptive Statistics -- 3. Basic Principles of Explanatory Statistics -- 4. The Analysis of a Continuous Outcome Variable -- 5. The Analysis of a Dichotomous Outcome Variable -- 6. The Analysis of Survival Data -- 7. Multiple Regression Analysis - Association Models and Prediction Models -- 8. Machine Learning -- 9. Other Outcome Variables -- 10. Missing Data -- 11. Pitfalls in (Multiple) Regression Analysis -- 12. Miscellaneous -- 13. Overview -- 14. Example Datasets.
Contained By:	Springer Nature eBook
Subject:	Medical statistics. -
Online resource:	https://doi.org/10.1007/978-3-031-86278-6
ISBN:	9783031862786

Basic principles of applied medical statistics = a practical guide /
Twisk, Jos W. R.

Basic principles of applied medical statisticsa practical guide /[electronic resource] :by Jos W. R. Twisk. - Cham :Springer Nature Switzerland :2025. - xii, 268 p. :ill. (some col.), digital ;24 cm.

- 1. Introduction -- 2. Descriptive Statistics -- 3. Basic Principles of Explanatory Statistics -- 4. The Analysis of a Continuous Outcome Variable -- 5. The Analysis of a Dichotomous Outcome Variable -- 6. The Analysis of Survival Data -- 7. Multiple Regression Analysis - Association Models and Prediction Models -- 8. Machine Learning -- 9. Other Outcome Variables -- 10. Missing Data -- 11. Pitfalls in (Multiple) Regression Analysis -- 12. Miscellaneous -- 13. Overview -- 14. Example Datasets.

This book describes the basic principles of medical statistics. Although there are many texts on this topic, this one is different in that it limits the mathematics to an absolute minimum. It will therefore be extremely useful for non-mathematical researchers who need to use statistical methods in their work. Here, they will learn how to choose the appropriate statistical method and how to interpret the results obtained from statistical software. An important feature of the book is that it highlights the common thread throughout the statistical methods. By understanding this common thread, the analyses become much easier to comprehend. Each chapter contains multiple examples, and because the example datasets are available, the readers can reanalyze them and practice how to perform a particular statistical analysis.

ISBN: 9783031862786

Standard No.: 10.1007/978-3-031-86278-6doiSubjects--Topical Terms:

533219
Medical statistics.

LC Class. No.: RA409

Dewey Class. No.: 610.21

Basic principles of applied medical statistics = a practical guide /
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245 1 0 $a Basic principles of applied medical statistics $h [electronic resource] : $b a practical guide / $c by Jos W. R. Twisk.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xii, 268 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a - 1. Introduction -- 2. Descriptive Statistics -- 3. Basic Principles of Explanatory Statistics -- 4. The Analysis of a Continuous Outcome Variable -- 5. The Analysis of a Dichotomous Outcome Variable -- 6. The Analysis of Survival Data -- 7. Multiple Regression Analysis - Association Models and Prediction Models -- 8. Machine Learning -- 9. Other Outcome Variables -- 10. Missing Data -- 11. Pitfalls in (Multiple) Regression Analysis -- 12. Miscellaneous -- 13. Overview -- 14. Example Datasets.
520 $a This book describes the basic principles of medical statistics. Although there are many texts on this topic, this one is different in that it limits the mathematics to an absolute minimum. It will therefore be extremely useful for non-mathematical researchers who need to use statistical methods in their work. Here, they will learn how to choose the appropriate statistical method and how to interpret the results obtained from statistical software. An important feature of the book is that it highlights the common thread throughout the statistical methods. By understanding this common thread, the analyses become much easier to comprehend. Each chapter contains multiple examples, and because the example datasets are available, the readers can reanalyze them and practice how to perform a particular statistical analysis.
650 0 $a Medical statistics. $3 533219
650 1 4 $a Biostatistics. $3 1002712
650 2 4 $a Methodology of Data Collection and Processing. $3 3598081
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-86278-6
950 $a Mathematics and Statistics (SpringerNature-11649)