Statistics in Medicine, 2nd Edition

Author: Robert H. Riffenburgh 公卫考场
Publisher: Elsevier
Copyright: 2005
ISBN-10: 0-1208-8770-3
ISBN-13: 978-0-12-088770-5
Pages: 672; hardcover
Price: $52.50
Statistics in Medicine is an excellent book for the health professional. It focuses on understanding statistical concepts and not on the mathematical and theoretical underpinnings. The author covers a broad range of statistical techniques with adequate depth and with an appreciation of the problems faced by health professionals. 公卫百科

The text consists of two parts. The first resembles a textbook for an introductory course in biostatistics for the medical sciences. Basic concepts, such as summary statistics, confidence intervals, tests, and two-way tables, are covered in a mostly traditional fashion. The second part of the text, however, is meant to serve as a reference for researchers wanting to learn the basic ideas behind more sophisticated techniques, for example, those you would find being used in medical journals or government reports. As such, many topics are covered, such as advanced regressions, survival analysis, equivalence, and experimental design, but no one topic is covered very deeply. 公卫百科

Foreword to the Second Edition
Foreword to the First Edition
Acknowledgments
Databases
Part I A Study Course of Fundamentals
1 Data, Notation, and Some Basic Terms
1.1. About This Book
1.2. Stages of Scientific Knowledge
1.3. Quantification and Accuracy
1.4. Data Types
1.5. Notation (or Symbols)
1.6. Samples, Populations, and Randomness

2 Distributions
2.1. Frequency Distributions
2.2. Relative Frequencies and Probabilities

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2.3. Characteristics of a Distribution
2.4. What Is Typical?
2.5. The Spread about the Typical
2.6. The Shape
2.7. Statistical Inference
2.8. Distributions Commonly Used in Statistics
2.9. Standard Error of the Mean
2.10. Joint Distributions of Two Variables

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Chapter Exercises

3 Summary Statistics
3.1. Numerical Summaries, One Variable
3.2. Numerical Summaries, Two Variables
3.3. Pictorial Summaries, One Variable
3.4. Pictorial Summaries, Two Variables
3.5. Good Graphing Practices 公卫人

4 Confidence Intervals and Probability
4.1. Overview
4.2. The Normal Distribution
4.3. Confidence Interval on an Observation from an Individual Patient
4.4. Concept of a Confidence Interval on a Descriptive Statistic
4.5. Confidence Interval on a Mean, Known Standard Deviation 公卫家园
4.6. The t Distribution
4.7. Confidence Interval on a Mean, Estimated Standard Deviation
4.8. The Chi-Square Distribution
4.9. Confidence Interval on a Variance or Standard Deviation
4.10. Other Frequently Seen Confidence Intervals and Probabilities

5 Hypothesis Testing: Concept and Practice
5.1. Hypotheses in Inference
5.2. Error Probabilities
5.3. Two Policies of Testing
5.4. Organizing Data for Inference
5.5. Evolving a Way to Answer Your Data Question

6 Statistical Testing, Risks, and Odds in Medical Decisions

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6.1. Overview 6.2. Categorical Data: Basics
6.3. Categorical Data: Tests on 2 x 2 Tables
6.4. Categorical Data: Risks and Odds
6.5. Rank Data: Basics
6.6. Rand Data: The Rank-Sum Test to Compare Two Samples
6.7. Continuous Data: Basics of Means 公卫人
6.8. Continuous Data: Normal (z) and t Tests to Compare Two Sample Means
6.9. Other Tests of Hypotheses

7 Sample Size Required for a Study
7.1. Overview
7.2. Is the Estimate of Minimum Required Sample Size Adequate?
7.3. Sample Size in Means Testing 公卫考场
7.4. Minimum Sample Size Estimation for a Test of Two Means
7.5. Other Situations in Which Minimum Sample Size Estimation Is Used

8 Statistical Prediction
8.1. What Is a "Model"?
8.2. Straight Line Models
8.3. What Is "Regression" (and Its Relation to Correlation)? 公卫百科
8.4. Assessing and Predicting Relationships by Regression
8.5. Other Questions That Can Be Answered by Regression
8.6. Clinical Decisions and Outcomes Analysis

9 Epidemiology
9.1. The Nature of Epidemiology
9.2. Some Key Stages in the History of Epidemiology 公卫考场
9.3. Concept of Disease Transmission
9.4. Descriptive Measures
9.5. Types of Epidemiologic Studies
9.6. An Informal Approach to Public Health Problems
9.7. Analysis of Survival and Causal Factors

10 Reading Medical Articles
10.1. Assessing Medical Information from an Article

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10.2. Keep in Mind How a Study Is Constructed
10.3. Study Types
10.4. Sampling Bias
10.5. Statistical Aspects Where Articles May Fall Short
10.6. Evolving Terms: Meta-analysis, Multivariate Analysis, and Others
10.7. Selection of Statistical Tests to Use in a Study

Answers to Chapter Exercises, Part I
Part II A Reference Guide
11 Using the Reference Guide
11.1. How to Use This Guide
11.2. Basic Concepts Needed to Use This Guide

12 Planning Medical Studies
12.1. The Science Underlying Clinical Decision Making 公卫人
12.2. The Objective of Statistics
12.3. Concepts in Study Design
12.4. Sampling Schemes
12.5. How to Randomize a Sample
12.6. How to Plan and Conduct a Study
12.7. Mechanisms to Improve Your Study Plan
12.8. How to Manage Data
12.9. Setting Up a Test Within a Study 公卫人
12.10. Choosing the Right Test
12.11. Statistical Ethics in Medical Studies

13 Finding Probabilities of Error
13.1. Introduction
13.2. The Normal Distribution
13.3. The t Distribution
13.4. The Chi-Square Distribution
13.5. The F Distribution 公卫家园
13.6. The Binomial Distribution
13.7. The Poisson Distribution

14 Confidence Intervals
14.1. Overview
14.2. Confidence Interval on a Mean, Known Standard Deviation
14.3. Confidence Interval on a Mean, Estimated Standard Deviation
14.4. Confidence Interval on a Variance or Standard Deviation
14.5. Confidence Interval on a Proportion
14.6. Confidence Interval on a Correlation Coefficient

15 Tests on Categorical Data
15.1. Categorical Data Summary
15.2. 2 x 2 Tables: Contingency Tests
15.3. r x c Tables: Contingency Tests
15.4. Risks and Odds in Medical Decisions
15.5. 2 x 2 Tables: Tests of Association
15.6. Tests of a Proportion
15.7. Tests of a Small Proportion (Proportion Close to 0)
15.8. Matched Pair Sample (McNemar's Test) 公卫家园

16 Common Tests on Ranked Data
16.1. Basics of Ranks
16.2. Single or Paired Small Samples: The Signed-Rank Test
16.3. Two Small Samples: The Rank-Sum Test
16.4. Three or More Independent Samples: The Kruskal–Wallis Test
16.5. Three or More Matched Samples: The Friedman Test 公卫家园
16.6. Single Large Samples: Normal Approximation to Signed-Rank Test
16.7. Two Large Samples: Normal Approximation to Rank-Sum Test

17 Tests on Means of Continuous Data
17.1. Summary of Means Testing
17.2. Normal (z) and t Tests for Single or Paired Means
17.3. Post Hoc Confidence and Power
17.4. Normal (z) and t Tests for Two Means
17.5. Three or More Means: One-Way Analysis of Variance

18 Multifactor Tests on Means of Continuous Data
18.1. Concepts of Experimental Design
18.2. Two-Factor Analysis of Variance
18.3. Repeated-Measures Analysis of Variance
18.4. Analysis of Covariance
18.5. Three- and Higher-Factor Analysis of Variance
18.6. More Specialized Designs and Techniques

19 Tests on Variances of Continuous Data
19.1. Basics of Tests on Variability

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19.2. Single Samples
19.3. Two Samples
19.4. Three or More Samples

20 Tests on the Distribution Shape of Continuous Data
20.1. Objectives of Tests on Distributions
20.2. Test of Normality of a Distribution
20.3. Test of Equality of Two Distributions 公卫人

21 Equivalence Testing
21.1. Concepts and Terms
21.2. Basics Underlying Equivalence Testing
21.3. methods for Nonsuperiority Testing
21.4. Methods for Equivalence Testing

22 Sample Size Required in a Study
22.1. Overview

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22.2. Relation of Sample Size Calculated to Sample Size Needed
22.3. Sample Size for Tests on Means
22.4. Sample Size for Confidence Intervals on Means
22.5. Sample Size for Tests on Rates (Proportions)
22.6. Sample Size for a Confidence Interval on a Rate (Proportion)

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22.7. Sample Size for Significance of a Correlation Coefficient
22.8. Sample Size for Tests on Ranked Data
22.9. Sample Size for Tests on Variances, Analysis of Variance, and Regression

23 Modeling and Clinical Decisions
23.1. Overview of Modeling 公卫百科
23.2. Straight-Line Models
23.3. Curved Models
23.4. Constants of Fit for Any Model
23.5. Multiple-Variable Models
23.6. Clinical Decision Based on Recursive Partitioning
23.7. Screening and Number Needed to Treat or to Benefit
23.8. Clinical Decision Based on Measures of Effectiveness: Outcomes Analysis 公卫考场

24 Regression and Correlation Methods
24.1. Regression Concepts and Assumptions
24.2. Correlation Concepts and Assumptions
24.3. Simple Regression
24.4. Correlation Coefficients
24.5. Tests and Confidence Intervals on Regression Parameters

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24.6. Tests and Confidence Intervals on Correlation Coefficients
24.7. Curved Regression
24.8. Multiple Regression
24.9. Types of Regression
24.10. Logistic Regression

25 Survival and Time-Series Analysis
25.1. Time-Dependent Data

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25.2. Survival Curves: Estimation
25.3. Survival Curves: Testing
25.4. Sequential Analysis
25.5. Time-Series Data: Detecting Patterns
25.6. Time-Series Data: Testing

26 Methods You Might Meet, But Not Every Day
26.1. Overview

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26.2. Analysis of Variance Issues
26.3. Regression Issues
26.4. Multivariate Issues
26.5. Nonparametric Tests
26.6. Imputation of Missing Data
26.7. Resampling Methods
26.8. Agreement Measures and Correlation
26.9. Bonferroni "Correction"

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26.10. Logit and Probit
26.11. Adjusting for Outliers
26.12. Curve Fitting to Data
26.13. Tests of Normality

Chapter Summaries
References and Data Sources
Tables of Probability Distributions
I. Normal Distribution
II. t Distribution
III. Chi-Square Distribution, Right Tail
IV. Chi-Square Distribution, Left Tail
V. F Distribution
VI. Binomial Distribution
VII. Poisson Distribution
VIII. Signed-Rank Probabilities
IX. Rank-Sum U Probabilities

Symbol Index

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Subject Index
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