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Leung

Using and Understanding Medical Statistics

Medium: Buch
ISBN: 978-1-394-44623-0
Verlag: John Wiley & Sons Inc
Erscheinungstermin: 26.11.2026
vorbestellbar, Erscheinungstermin ca. November 2026

A visual guide to interpreting medical research statistics

Many clinicians lack the statistical training needed to critically appraise published research, yet evidence-based practice demands exactly that skill. Using and Understanding Medical Statistics takes a deliberately visual, clinician-centred approach, using over 200 figures and real-world journal article examples to build intuitive understanding of the methods encountered in medical literature.

Coverage spans descriptive statistics, inferential statistics and confidence intervals, linear and logistic regression, survival analysis, and advanced observational techniques including propensity score matching and interrupted time series. Each chapter closes with simulation-based exercises that mirror genuine medical research scenarios, reinforcing practical application of each technique.

The book also features: - "Key Concepts" summaries at the end of each section that scaffold understanding and prepare readers for subsequent topics
- Technical sections marked by a chili icon at subheadings, allowing readers to skip advanced material without losing continuity
- Chapter summaries providing high-level overviews that support rapid review and consolidation of statistical methods covered
- Examples inspired by published journal articles rather than generic datasets, grounding every technique in authentic clinical contexts
- Mathematical notation kept to an absolute minimum, connecting high-school mathematics to the statistical sophistication of modern research

Designed for postgraduate healthcare researchers, PhD students in medical sciences, and clinicians pursuing continuing professional development or transitioning into academia, this book builds the statistical literacy required to evaluate study reliability and apply research findings confidently to patient care.


Produkteigenschaften


  • Artikelnummer: 9781394446230
  • Medium: Buch
  • ISBN: 978-1-394-44623-0
  • Verlag: John Wiley & Sons Inc
  • Erscheinungstermin: 26.11.2026
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2026
  • Produktform: Kartoniert
  • Seiten: 320
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

Part I: Introduction

1 Introduction
1.1 Purpose of and approach used in this book
1.2 Why statistics in medical research?
1.3 Fundamental reasoning in medical research: causation and association
1.4 Road map of the book
1.5 Summary
1.6 Exercise

2 Brief overview of medical research
2.1 Biases and confounding
2.2 Types of study designs
2.3 Reading a medical research paper
2.4 Summary
2.5 Exercise

Part II. Fundamentals of statistics

3 Level of measurement
3.1 Numerical variables
3.2 Ordinal variables
3.3 Categorical variables
3.4 Data conversion
3.5 Summary
3.6 Exercise

4 Descriptive statistics
4.1 Central tendency
4.2 Dispersion
4.3 Correlation
4.4 Other measure of association
4.5 Summary
4.6 Exercise

5 Inferential statistics
5.1 Population, sample, and hypothetical repeated sampling
5.2 Confidence intervals
5.3 Hypothesis testing
5.4 Summary
5.5 Exercise

Part III: Regression analysis

6 Linear regression
6.1 Underlying principles
6.2 The regression model and interpretation
6.3 Confidence intervals and hypothesis tests
6.4 Goodness-of-fit
6.5 Partial R²
6.6 Categorical data and multicollinearity
6.7 Interaction effect
6.8 Joint tests
6.9 Assumptions of linear regression
6.10 Drawback of linear regression
6.11 Summary
6.12 Exercise

7 Logistic regression
7.1 Underlying principles
7.2 The regression model and interpretation
7.3 Confidence intervals and hypothesis tests
7.4 Goodness-of-fit
7.5 Assumptions of logistic regression
7.6 Drawback of logistic regression
7.7 Summary
7.8 Exercises

8 Cox regression
8.1 Underlying principles
8.2 The regression model and interpretation
8.3 Confidence intervals and hypothesis tests
8.4 Goodness-of-fit
8.5 Assumptions of Cox regression
8.6 Drawback of Cox regression
8.7 Summary
8.8 Exercises

Part IV: Advanced topics

9 Multi-group comparison
9.1 Testing the difference between multiple groups
9.2 Post hoc and a-priori tests
9.3 Summary
9.4 Exercise

10 Propensity score matching
10.1 Propensity scores
10.2 Matching methods
10.3 Mahalanobis distance
10.4 Assumptions
10.5 Summary
10.6 Exercise

11 Interrupted time series analysis
11.1 Time-dependent structure
11.2 Segmented regression
11.3 Autoregressive integrated moving average (ARIMA) models
11.4 Summary
11.5 Exercise

12 Meta-analysis
12.1 Repeated sampling principle
12.2 Fixed-effect model
12.3 Random-effect model
12.4 Assessing heterogeneity
12.5 Assessing and adjusting for publication bias
12.6 Summary
12.7 Exercise

13 Beyond the basics: extensions and advanced approaches
13.1 Other measures of correlation and association
13.2 Nonlinear regression
13.3 Multinomial logistic regression
13.4 Other models in survival analysis: non-proportional hazard and competing risk model
13.5 Multi-group multivariate comparison
13.6 Multi-group interrupted time series analysis
13.7 Further topics in meta-analysis: addressing heterogeneity and network meta-analysis (NMA)
13.8 Regression models for count data
13.9 Principal component analysis (PCA) and factor analysis (FA)
13.10. E-value: addressing the impact of unmeasured confounding
13.11. Summary
13.12. Exercise

Glossaries
Index