DESCRIPTION:
Maintaining the same accessible and hands-on presentation, Introductory Biostatistics, Second Edition continues to provide an organized introduction to basic statistical concepts commonly applied in research across the health sciences. With plenty of real-world examples, the new edition provides a practical, modern approach to the statistical topics found in the biomedical and public health fields.
Beginning with an overview of descriptive statistics in the health sciences, the book delivers topical coverage of probability models, parameter estimation, and hypothesis testing. Subsequently, the book focuses on more advanced topics with coverage of regression analysis, logistic regression, methods for count data, analysis of survival data, and designs for clinical trials.
This extensive update of Introductory Biostatistics, Second Edition includes:
- A new chapter on the use of higher order Analysis of Variance (ANOVA) in factorial and block designs
- A new chapter on testing and inference methods for repeatedly measured outcomes including continuous, binary, and count outcomes
- R incorporated throughout along with SAS®, allowing readers to replicate results from presented examples with either software
- Multiple additional exercises, with partial solutions available to aid comprehension of crucial concepts
- Notes on Computations sections to provide further guidance on the use of software
- A related website that hosts the large data sets presented throughout the book
Introductory Biostatistics, Second Edition is an excellent textbook for upper-undergraduate and graduate students in introductory biostatistics courses. The book is also an ideal reference for applied statisticians working in the fields of public health, nursing, dentistry, and medicine.
CONTENTS:
1 Descriptive Methods for Categorical Data
1.1 Proportions
1.1.1 Comparative Studies
1.1.2 Screening Tests
1.1.3 Displaying Proportions
1.2 Rates
1.2.1 Changes
1.2.2 Measures of Morbidity and Mortality
1.2.3 Standardization of Rates
1.3 Ratios
1.3.1 Relative Risk
1.3.2 Odds and Odds Ratio
1.3.3 Generalized Odds for Ordered 2 × k Tables
1.3.4 Mantel-Haenszel Method
1.3.5 Standardized Mortality Ratio
1.4 Notes on Computations
Exercises
2 Descriptive Methods for Continuous Data
2.1 Tabular and Graphical Methods
2.1.1 One ]way Scatter Plots
2.1.2 Frequency Distribution
2.1.3 Histogram and Frequency Polygon
2.1.4 Cumulative Frequency Graph and Percentiles
2.1.5 Stem and Leaf Diagrams
2.2 Numerical Methods
2.2.1 Mean
2.2.2 Other Measures of Location
2.2.3 Measures of Dispersion
2.2.4 Box Plots
2.3 Special Case of Binary Data
2.4 Coefficients of Correlation
2.4.1 Pearson""s Correlation Coefficient
2.4.2 Nonparametric Correlation Coefficients
2.5 Notes on Computations
Exercises
3 Probability and Probability Models
3.1 Probability
3.1.1 Certainty of Uncertainty
3.1.2 Probability
3.1.3 Statistical Relationship
3.1.4 Using Screening Tests
3.1.5 Measuring Agreement
3.2 Normal Distribution
3.2.1 Shape of the Normal Curve
3.2.2 Areas Under the Standard Normal Curve
3.2.3 Normal Distribution as a Probability Model
3.3 Probability Models for Continuous Data
3.4 Probability Models for Discrete Data
3.4.1 Binomial Distribution
3.4.2 Poisson Distribution
3.5 Brief Notes on the Fundamentals
3.5.1 Mean and Variance
3.5.2 Pair ]Matched Case-Control Study
3.6 Notes on Computations
Exercises
4 Estimation of Parameters
4.1 Basic Concepts
4.1.1 Statistics as Variables
4.1.2 Sampling Distributions
4.1.3 Introduction to Confidence Estimation
4.2 Estimation of Means
4.2.1 Confidence Intervals for a Mean
4.2.2 Uses of Small Samples
4.2.3 Evaluation of Interventions
4.3 Estimation of Proportions
4.4 Estimation of Odds Ratios
4.5 Estimation of Correlation Coefficients
4.6 Brief Notes on the Fundamentals
4.7 Notes on Computations
Exercises
5 Introduction to Statistical tests of Significance
5.1 Basic Concepts
5.1.1 Hypothesis Tests
5.1.2 Statistical Evidence
5.1.3 Errors
5.2 Analogies
5.2.1 Trials by Jury
5.2.2 Medical Screening Tests
5.2.3 Common Expectations
5.3 Summaries and Conclusions
5.3.1 Rejection Region
5.3.2 p Values
5.3.3 Relationship to Confidence Intervals
5.4 Brief Notes on the Fundamentals
5.4.1 Type I and Type II Errors
5.4.2 More about Errors and p Values
Exercises
6 Comparison of Population Proportions
6.1 One ]Sample Problem with Binary Data
6.2 Analysis of Pair ]Matched Data
6.3 Comparison of Two Proportions
6.4 Mantel-Haenszel Method
6.5 Inferences for General Two ]Way Tables
6.6 Fisher""s Exact Test
6.7 Ordered 2 × K Contingency Tables
6.8 Notes on Computations
Exercises
7 Comparison of Population Means
7.1 One ]Sample Problem with Continuous Data
7.2 Analysis of Pair ]Matched Data
7.3 Comparison of Two Means
7.4 Nonparametric Methods
7.4.1 Wilcoxon Rank ]Sum Test
7.4.2 Wilcoxon Signed ]Rank Test
7.5 One ]Way Analysis of Variance
7.5.1 One ]way Analysis of Variance Model
7.5.2 Group Comparisons
7.6 Brief Notes on the Fundamentals
7.7 Notes on Computations
Exercises
8 Analysis of Variance
8.1 Factorial Studies
8.1.1 Two Crossed Factors
8.1.2 Extensions to More Than Two Factors
8.2 Block Designs
8.2.1 Purpose
8.2.2 Fixed Block Designs
8.2.3 Random Block Designs
8.3 Diagnostics
Exercises
9 Regression Analysis
9.1 Simple Regression Analysis
9.1.1 Correlation and Regression
9.1.2 Simple Linear Regression Model
9.1.3 Scatter Diagram
9.1.4 Meaning of Regression Parameters
9.1.5 Estimation of Parameters and Prediction
9.1.6 Testing for Independence
9.1.7 Analysis of Variance Approach
9.1.8 Some Biomedical Applications
9.2 Multiple Regression Analysis
9.2.1 Regression Model with Several Independent Variables
9.2.2 Meaning of Regression Parameters
9.2.3 Effect Modifications
9.2.4 Polynomial Regression
9.2.5 Estimation of Parameters and Prediction
9.2.6 Analysis of Variance Approach
9.2.7 Testing Hypotheses in Multiple Linear Regression
9.2.8 Some Biomedical Applications
9.3 Graphical and Computational Aids
Exercises
10 Logistic Regression
10.1 Simple Regression Analysis
10.1.1 Simple Logistic Regression Model
10.1.2 Measure of Association
10.1.3 Effect of Measurement Scale
10.1.4 Tests of Association
10.1.5 Use of the Logistic Model for Different Designs
10.1.6 Overdispersion
10.2 Multiple Regression Analysis
10.2.1 Logistic Regression Model with Several Covariates
10.2.2 Effect Modifications
10.2.3 Polynomial Regression
10.2.4 Testing Hypotheses in Multiple Logistic Regression
10.2.5 Receiver Operating Characteristic Curve
10.2.6 ROC Curve and Logistic Regression
10.3 Brief Notes on the Fundamentals
10.4 Notes on Computing
Exercises
11 Methods for Count Data
11.1 Poisson Distribution
11.2 Testing Goodness of Fit
11.3 Poisson Regression Model
11.3.1 Simple Regression Analysis
11.3.2 Multiple Regression Analysis
11.3.3 Overdispersion
11.3.4 Stepwise Regression
Exercises
12 Methods for Repeatedly Measured Responses
12.1 Extending Regression Methods Beyond Independent Data
12.2 Continuous Responses
12.2.1 Extending Regression using the Linear Mixed Model
12.2.2 Testing and Inference
12.2.3 Comparing Models
12.2.4 Special Cases: Random Block Designs and Multi ]level Sampling
12.3 Binary Responses
12.3.1 Extending Logistic Regression using Generalized Estimating Equations
12.3.2 Testing and Inference
12.4 Count Responses
12.4.1 Extending Poisson Regression using Generalized Estimating Equations
12.4.2 Testing and Inference
12.5 Computational Notes
Exercises
13 Analysis of Survival Data and Data from Matched Studies
13.1 Survival Data
13.2 Introductory Survival Analyses
13.2.1 Kaplan-Meier Curve
13.2.2 Comparison of Survival Distributions
13.3 Simple Regression and Correlation
13.3.1 Model and Approach
13.3.2 Measures of Association
13.3.3 Tests of Association
13.4 Multiple Regression and Correlation
13.4.1 Proportional Hazards Model with Several Covariates
13.4.2 Testing Hypotheses in Multiple Regression
13.4.3 Time ]Dependent Covariates and Applications
13.5 Pair ]Matched Case-Control Studies
13.5.1 Model
13.5.2 Analysis
13.6 Multiple Matching
13.6.1 Conditional Approach
13.6.2 Estimation of the Odds Ratio
13.6.3 Testing for Exposure Effect
13.7 Conditional Logistic Regression
13.7.1 Simple Regression Analysis
13.7.2 Multiple Regression Analysis
Exercises
14 Study Designs
14.1 Types of Study Designs
14.2 Classification of Clinical Trials
14.3 Designing Phase I Cancer Trials
14.4 Sample Size Determination for Phase II Trials and Surveys
14.5 Sample Sizes for Other Phase II Trials
14.5.1 Continuous Endpoints
14.5.2 Correlation Endpoints
14.6 About Simon""s Two ]Stage Phase II Design
14.7 Phase II Designs for Selection
14.7.1 Continuous Endpoints
14.7.2 Binary Endpoints
14.8 Toxicity Monitoring in Phase II Trials
14.9 Sample Size Determination for Phase III Trials
14.9.1 Comparison of Two Means
14.9.2 Comparison of Two Proportions
14.9.3 Survival Time as the Endpoint
14.10 Sample Size Determination for Case-Control Studies
14.10.1 Unmatched Designs for a Binary Exposure
14.10.2 Matched Designs for a Binary Exposure
14.10.3 Unmatched Designs for a Continuous Exposure