We are currently upgrading our print fulfillment systems. Print book orders placed between Sept 22 and Oct 9 will be delayed. Delivery of these orders will start on Oct 10, with purchases being fulfilled in the order received. Buy the Print and get eBook immediately for FREE. Use Code BOGO. Or save up to 40% on all orders with code: DELTA. Exclusions apply. Click here for terms and conditions.
 
 

Biostatistics, 2nd Edition

A Guide to Design, Analysis and Discovery.

 
Biostatistics, 2nd Edition,Ronald Forthofer,Eun Lee,Mike Hernandez,ISBN9780123694928
 
 
 

  &      &      

Academic Press

9780123694928

9780080467726

528

260 X 184

Print Book + eBook

USD 121.20
USD 202.00

Buy both together and save 40%

Print Book

Hardcover

In Stock

Estimated Delivery Time
USD 101.00

eBook
eBook Overview

PDF format

VST format

USD 101.00
Add to Cart
 
 

Key Features

* Includes access to a companion website with further examples and a full explanation of computer packages
* Over 40% new material with modern real-life examples, exercises and references
* New chapters on Logistic Regression; Analysis of Survey Data; and Study Designs
* Introduces strategies for analyzing complex sample survey data
* Written in a conversational style more accessible to students with real data

Description

Today, mathematics, biology, medicine, and statistics are closing the interdisciplinary gap in an unprecedented way and many of the important unanswered questions now emerge at the interface of these disciplines. Now in its Second Edition, this user-friendly guide on biostatistics focuses on the proper use and interpretation of statistical methods. This textbook does not require extensive background in mathematics, making it user-friendly for all students in the public health sciences field. Instead of highlighting derivations of formulas, the authors provide rationales for the formulas, allowing students to grasp a better understanding of the link between biology and statistics. The material on life tables and survival analysis allows students to better understand the recent literature in the health field, particularly in the study of chronic disease treatment. Biostatistics now includes a companion website to demonstrate the different applications of computer packages for performing the various analyses presented in this text.

Readership

Students in the health sciences, public health professionals, practitioners.

Ronald Forthofer

Affiliations and Expertise

Boulder County, Colorado, U.S.A.

Eun Lee

Affiliations and Expertise

Oregon Health Science University, Portland, U.S.A.

Mike Hernandez

Affiliations and Expertise

Anderson Cancer Center, Houston, Texas, U.S.A.

Biostatistics, 2nd Edition

1. INTRODUCTION

1.1 What is Biostatistics?
1.2 Data – The Key Component of a Study
1.3 Design – The Road to Relevant Data
1.4 Replication – Part of the Scientific Method
1.5 Applying Statistical Methods
Concluding Remarks
Exercises
References


2. DATA AND NUMBERS

2.1 Data: Numerical Representation
2.2 Observations and Variables
2.3 Scales Used with Variables
2.4 Reliability and Validity
2.5 Randomized Response Technique
2.6 Common Data Problems
Concluding Remarks
Exercises
References


3. DESCRIPTIVE METHODS

3.1 Introduction to Descriptive Methods
3.2 Tabular and Graphic Presentation of Data
3.2.1 Frequency Tables
3.2.2 Line Graphs
3.2.3 Bar Charts
3.2.4 Histograms
3.2.5 Stem-and-Leaf Plots
3.2.6 Dot Plots
3.2.7 Scatter Plots
3.3 Measures of Central Tendency
3.3.1 Mean, Median, and Mode
3.3.2 Use of the Measures of Central Tendency
3.3.3 The Geometric Mean
3.4 Measures of Variability
3.4.1 Ranges and Percentiles
3.4.2 Box Plots
3.4.3 Variance and Standard Deviation
3.5 Rates and Ratios
3.5.1 Crude and Specific Rates
3.5.2 Adjusted Rates
3.6 Measures of Change Over Time
3.6.1 Linear Growth
3.6.2 Geometric Growth
3.6.3 Exponential Growth
3.7 Correlation Coefficients
3.7.1 Pearson Correlation Coefficient
3.7.2 Spearman Rank Correlation Coefficient
Concluding Remarks
Exercises
References


4. PROBABILITY AND LIFE TABLES

4.1 A Definition of Probability
4.2 Rules for Calculating Probabilities
4.2.1 Addition Rule for Probabilities
4.2.2 Conditional Probabilities
4.2.3 Independent Events
4.3 Definitions from Epidemiology
4.3.1 Rates and Probabilities
4.3.2 Sensitivity, Specificity, and Predicted Value Positive and Negative
4.3.3 Receiver Operating Characteristic Plot
4.4 Bayes’ Theorem
4.5 Probability in Sampling
4.5.1 Sampling With Replacement
4.5.2 Sampling Without Replacement
4.6 Estimating Probabilities by Simulation
4.7 Probability and the Life Table
4.7.1 The First Four Columns of the Life Table
4.7.2 Some Uses of the Life Table
4.7.3 Expected Values in the Life Table
4.7.4 Other Expected Values in the Life Table
Concluding Remarks
Exercises
References


5. PROBABILITY DISTRIBUTIONS

5.1 The Binomial Distribution
5.1.1 Binomial Probabilities
5.1.2 Mean and Variance of the Binomial Distribution
5.1.3. Shapes of the Binomial Distribution
5.2 The Poisson Distribution
5.2.1 Poisson Probabilities
5.2.2 Mean and Variance of the Poisson Distribution
5.2.3 Finding Poisson Probabilities
5.3 The Normal Distribution
5.3.1 Normal Probabilities
5.3.2 Transforming to the Standard Normal Distribution
5.3.3 Calculation of Normal Probabilities
5.3.4 Normal Probability Plot
5.4 The Central Limit Theorem
5.5 Approximations to the Binomial and Poisson Distributions
5.5.1 Normal Approximation to the Binomial Distribution
5.5.2 Normal Approximation to the Poisson Distribution
Concluding Remarks
Exercises
References

6. STUDY DESIGNS

6.1 Design: Putting Chance to Work
6.2 Sample Surveys and Experiments
6.3 Sampling and Sample Designs
6.3.1 Sampling Frame
6.3.2 Importance of Probability Sampling
6.3.3 Simple Random Sampling
6.3.4 Systematic Sampling
6.3.5 Stratified Random Sampling
6.3.6 Cluster Sampling
6.3.7 Problems Due to Unintended Sampling
6.4 Designed Experiments
6.4.1 Comparison Groups and Randomization
6.4.2 Random Assignment
6.4.3 Sample Size
6.4.4 Single and Double Blind Experiments
6.4.5 Blocking and Extraneous Variables
6.4.6 Limitations of Experiments
6.5 Variations in Study Designs
6.5.1 The Cross-Over Design
6.5.2 The Case Control Design
6.5.3 The Cohort Study Design
Concluding Remarks
Exercises
References


7. INTERVAL ESTIMATION

7.1 Prediction, Confidence, and Tolerance Intervals
7.2 Distribution-Free Intervals
7.2.1 Prediction Interval
7.2.2 Confidence Interval
7.2.3 Tolerance Interval
7.3 Confidence Intervals Based on the Normal Distribution
7.3.1 Confidence Interval for the Mean
7.3.2 Confidence Interval for a Proportion
7.3.3 Confidence Interval for Crude and Adjusted Rates
7.4 Confidence Interval for the Difference of Two Means and Proportions
Difference of Two Independent Means
7.4.1 Difference of Two Dependent Means
7.4.2 Difference of Two Independent Proportions
7.4.3 Difference of Two Dependent Proportions
7.5 Confidence Interval and Sample Size
7.6 Confidence Interval for Other Measures
7.6.1 Confidence Interval for the Variance
7.6.2 Confidence Interval for Pearson Correlation Coefficient
7.7 Prediction and Tolerance Intervals Based on the Normal Distribution
7.7.1 Prediction Interval
7.7.2 Tolerance Interval
Concluding Remarks
Exercises
References


8. TESTS OF HYPOTHESES

8.1 Preliminaries in Tests of Hyppotheses
8.1.1 Definitions of Terms Used in Hypothesis Testing
8.1.2 Determination of Decision Rule
8.1.3 Relationship of the Decision Rule, á and â
8.1.4 Conducting the Test
8.2 Testing Hypotheses about the Mean
8.2.1 Known Variance
8.2.2 Unknown Varinace
8.3 Testing Hypotheses about the Proportion and Rates
8.4 Testing Hypotheses about the Variance
8.5 Testing Hypotheses about the Pearson Correlation Coefficient
8.6 Testing Hypotheses about the Difference of Two Means
8.6.1 Difference of Two Independent Means
8.6.2 Difference of Two Dependent Means
8.7 Testing Hypotheses about the Difference of Two Proportions
8.7.1 Difference of Two Independent Proportions
8.7.2 Difference of Two Dependent Means
8.8 Tests of Hypotheses and Sample Size
8.9 Statistical and Practical Significance
Concluding Remarks
Exercises
References


9. NONPARAMETRIC TESTS

9.1 Why Nonparametric Tests?
9.2 The Sign Test
9.3 The Wilcoxon Signed Rank Test
9.4 The Wilcoxon Rank Sum Test
9.5 The Kruskal-Wallis Test
9.6 The Friedman Test
Concluding Remarks
Exercises
References


10. ANALYSIS OF CATEGORICAL DATA

10.1 Goodness-of-Fit Test
10.2 The 2 by 2 Contingency Table
10.2.1 Comparing Two Independent Binomial Proportions
10.2.2 Expected Cell Counts Assuming No Association
10.2.3 The Odds Ratio – a Measure of Association
10.2.4 The Fisher’s Exact Test
10.2.5 Analysis of Paired Data: The McNemar Test
10.3 The r by c Contingency Table
10.3.1 Testing Hypothesis of Non Association: The Chi-Square Test
10.3.2 Testing Hypothesis of No Trend
10.4 Multiple 2 by 2 Tables
10.4.1 Analyzing the Tables Separately
10.4.2 The Cochran-Mantel-Haenszel Test
104.3 The Mantel-Haenszel Common Odds Ratio
Concluding Remarks
Exercises
References


11. ANALYSIS OF SURVIVAL DATA

11.1 Data Collection in Follow-Up Studies
11.2 The Life Table Method
11.3 The Product-Limit Method
11.4 Comparison of Two Survival Distributions
11.4.1 The Cochran-Mantel-Haenszel Test
11.4.2 The Log-Rank Test
Concluding Remarks
Exercises
References


12. ANALYSIS OF VARIANCE

12.1 Assumptions for the Use of the ANOVA
12.2 One-Way ANOVA
12.2.1 Sums of Squares and Mean Squares
12.2.2 The F Statistics
12.2.3 The ANOVA Table
12.3 Multiple Comparisons
12.3.1 Error Rates: Individual and Family
12.3.2 Tukey-Kramer Method
12.3.3 Fisher’s Least Significant Difference Method
12.3.4 Dunnett’s Method
12.4 Two-Way ANOVA for the Randomized Block Design with m Replicates
12.5 Two-Way ANOVA with Interaction
12.6 Linear Model Representation of the ANOVA
12.6.1 The Completely Randomized Design
12.6.2 The Randomized Block Design with m Replicates
12.6.3 Two-Way ANOVA with Interaction
12.7 ANOVA with Unequal Numbers of Observations in Subgroups
Concluding Remarks
Exercises
References


13. LINEAR REGRESSION

13.1 Simple Linear Regression
13.1.1 Estimation of Coefficients
13.1.2 The Variance of Y|X
13.1.3 The Coefficient of Determination (R2)
13.2 Inference about the Coefficients
13.2.1 Assumptions for Inference in Linear Regression
13.2.2 Regression Diagnostics
13.2.3 The Slope Coefficient
13.2.4 The Y-Intercept Coefficient
13.2.5 The ANOVA Summary Table
13.3 Interval Estimation for and
13.3.1 Confidence Interval for
13.3.2 Prediction Interval for
13.4 Multiple Linear Regression
13.4.1 The Multiple Linear Regression Model
13.4.2 Specification of a Multiple Linear Regression Model
13.4.3 The Parameter Estimates, ANOVA, and Diagnostics
13.4.4 Multicollinearity Problems
13.4.5 Extending the Regression Model: Dummy Variables
Concluding Remarks
Exercises
References


14. LOGISTIC AND PROPORTIONAL HAZARD REGRESSION

14.1 Introduction to Logistic Regression
14.2 Simple Logistic Regression
14.3 Multiple Logistic Regression
14.4 Ordered Logistic Regression
14.5 Introduction to Proportional Hazard Regression
Concluding Remarks
Exercises
References


15. ANALYSIS OF SURVEY DATA

15.1 Introduction to Design-Based Inference
15.2 Complex Design and Unequal Selection Probability
15.2.1 Sample Weight
15.2.2 Poststratification
15.2.3 The Design Effect
15.3 Strategies for Variance Estimation
15.3.1 Replicated Sampling: A General Approach
15.3.2 Balanced Repeated Replication
15.3.3 Jackknife Repeated Replication
15.3.4 Linearization Method
15.4 Strategies for Analysis
15.4.1 Preliminary Analysis
15.4.2 Subpopulation Analysis
15.4.3 Descriptive Analysis
15.4.4 Contingency Table Analysis
15.4.5 Linear and Logistic Regression Analysis
Concluding Remarks
Exercises
References



Appendices

A. BASIC MATHEMATIC CONCEPTS

B. STATISTICAL TABLES

B1. Random Digits
B2. Binomial Probabilities
B3. Poisson Probabilities
B4. Critical Values for the t Distribution
B6. Charts for Confidence Intervals for the Proportion
B7. Critical Values for the Chi-Square Distribution
B8. Factors, k, for Two-Sided Tolerance Limits for Normal Distribution
B9. Critical Values for the Wilcoxon Signed Rank Test
B10. Critical Values for the Wilcoxon Rank Sum Test
B11. Critical Values for the F Distribution
B12. The Studentized Range for the Kramer-Tukey Procedure
B13. The Studentized Range for the Dunnett Procedure


C. SELECTED GOVERNMENTAL BIOSTATISTICAL DATA

C1. Population Census Data
C2. Vital Statistics
C3. Sample Surveys
C4. Life Tables


D. SOLUTIONS TO SELECTED EXERCISES

Quotes and reviews

"This book succeeds in all aspects: It is clearly written, it has excellent coverage of the fundamentals of statistical methodology...and it is informative through its novel statistical presentation...." - Journal of the American Statistical Association
 
 
Shop with Confidence

Free Shipping around the world
▪ Broad range of products
▪ 30 days return policy
FAQ