바이오사이언스 - Using and Understanding Medical Statistics

Preface to the Fifth Edition

Prefaces to the Previous Editions

1 Basic Concepts

1.1 Introduction

1.2 Random Variables, Probability Distributions and Some Standard Notation

1.3 Characteristics of a Distribution: Mean, Median and Variance

1.4 Statistical Calculations Using the Software Package Called R

2 Tests of Significance

2.1 Introduction

2.2 An Example

2.3 Common Features of Significance Tests

3 Fisher’s Test for 2 × 2 Contingency Tables

3.1 Introduction

3.2 Details of the Test

3.3 Additional Examples of Fisher’s Test

3.4 Sample R Code for Chapter 3

4 Approximate Significance Tests for Contingency Tables

4.1 Introduction

4.2 The χ² Test for 2 × 2 Tables

4.3 The χ² Test for Rectangular Contingency Tables

4.4 Sample R Code for Chapter 4

5 Some Warnings concerning 2 × 2 Tables

5.1 Introduction

5.2 Combining 2 × 2 Tables

5.3 Matched Pairs Binary Data

5.4 Multiple Comparisons and False Discovery Rates

5.5 Sample R Code for Chapter 5

6 Kaplan-Meier or ‘Actuarial’ Survival Curves

6.1 Introduction

6.2 General Features of the K-M Estimate

6.3 A Novel Use of the K-M Estimator

6.4 Confidence Bands for the K-M Estimator

6.5 Sample R Code for Chapter 6

7 The Log-Rank or Mantel-Haenszel Test for Comparing Survival Curves

7.1 Introduction

7.2 Details of the Test

7.3 Several Examples of the Log-Rank Test

7.4 Sample R Code for Chapter 7

8 An Introduction to the Normal Distribution

8.1 Introduction

8.2 Basic Features of the Normal Distribution

8.3 The Normal Distribution and Significance Testing

8.4 The Normal Distribution and Confidence Intervals

8.5 Sample R Code for Chapter 8

9 Analyzing Normally Distributed Data

9.1 Introduction

9.2 Some Preliminary Considerations

9.3 Analyzing a Single Sample

9.4 Comparisons Based on the Normal Distribution

9.5 Testing the Equality of Variances

9.6 Sample R Code for Chapter 9

10 Linear Regression Models for Medical Data

10.1 Introduction

10.2 A Historical Note

10.3 Multiple Linear Regression

10.4 Graphical Tools for Model Checking

10.5 Correlation

10.6 The Analysis of Variance

10.7 Sample R Code for Chapter 10

11 Binary Logistic Regression

11.1 Introduction

11.2 Logistic Regression

11.3 Estimation in 2 × 2 Tables

11.4 Reanalysis of a Previous Example

11.5 The Analysis of Dose-Response Data

11.6 Global Tests and a Previous Example

11.7 Sample R Code for Chapter 11

12 Regression Models for Count Data

12.1 Introduction

12.2 The Model for Poisson Regression

12.3 An Experimental Study of Cellular Differentiation

12.4 Overdispersion

12.5 Zero-Inflated Poisson Models

12.6 Sample R Code for Chapter 12

13 Proportional Hazards Regression

13.1 Introduction

13.2 A Statistical Model for the Death Rate

13.3 The Lymphoma Example

13.4 The Use of Time-Dependent Covariates

13.5 Sample R Code for Chapter 13

14 The Analysis of Longitudinal Data

14.1 Introduction

14.2 Liang-Zeger Regression Models

14.3 Random Effects Models

14.4 Multi-State Models

14.5 Sample R Code for Chapter 14

15 Analysis of Variance

15.1 Introduction

15.2 Representing Categorical Information in Regression Models

15.3 Understanding Two-Factor Interactions

15.4 Revisiting the INR Study

15.5 Sample R Code for Chapter 15

16 Data Analysis

16.1 Introduction

16.2 Quality Data

16.3 Initial or Exploratory Analysis

16.4 Primary Analysis

16.5 Secondary Analyses

16.6 Sample R Code for Chapter 16

17 The Question of Sample Size

17.1 Introduction

17.2 General Aspects of Sample Size Calculations

17.3 Two Examples of Sample Size Calculations

17.4 Some Hazards of Small Studies

17.5 Sample R Code for Chapter 17

18 The Design of Clinical Trials

18.1 Introduction

18.2 General Considerations

18.3 Trial Organization

18.4 Randomized versus Historical Controls

18.5 Intention to Treat

18.6 Factorial Designs

18.7 Repeated Significance Testing

18.8 Sequential Analysis

19 Further Comments regarding Clinical Trials

19.1 Introduction

19.2 Surrogate Endpoints

19.3 Active Control or Equivalence Trials

19.4 Other Designs

19.5 Multiple Outcomes

19.6 Multiple Treatment Arms

19.7 Stochastic Curtailment

20.3 Study Heterogeneity

20.4 An Illustrative Example

20.5 Graphical Displays

20.6 Using Funnel Plots to Detect Publication Bias

20.7 Sensitivity

20.8 Sample R Code for Chapter 20

21 Epidemiological Applications

21.1 Introduction

21.2 Epidemiological Studies

21.3 Relative Risk Models

21.4 Odds Ratio Models

21.5 Confounding and Effect Modification

21.6 Mantel-Haenszel Methodology

21.7 Poisson Regression Modelling of Cohort Studies

21.8 Clinical Epidemiology

21.9 Sample R Code for Chapter 21

22 Diagnostic Tests

22.1 Introduction

22.2 Some General Considerations

22.3 Sensitivity, Specificity, and Post-Test Probabilities

22.4 Likelihood Ratios and Related Issues

23 Agreement and Reliability

23.1 Introduction

23.2 Intraclass Correlation Coefficient

23.3 Assessing Agreement

23.4 Bland-Altman Plots

23.5 The Kappa Coefficient

23.6 Weighted κ

23.7 Measures of Agreement for Discrete Data

23.8 The Dependence of κ on Prevalence

23.9 Sample R Code for Chapter 23

References

Subject Index

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상품정보고시

제품명	Using and Understanding Medical Statistics
판매가격	60,000원
제조사	S. Karger Publishing

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