Medical Biostatistics shows how biostatistical methods are important tools in managing uncertainties in medicine and the health sciences.

• Provides comprehensive coverage of the wide range of biostatistical methods used in evidence-based patient management, medical research, and health administration
• Demonstrates how biostatistics helps manage many types of medical uncertainties
• Explains various statistical methods step-by-step
• Contains a large number of real-world examples that elucidate the medical meaning of the results
• Includes guide charts in the beginning of the book to enable immediate retrieval of statistical procedures

Requiring only high school algebra, Medical Biostatistics enables a solid understanding of the statistical concepts required to critically examine medical literature, scientifically plan and carry out medical investigations, and meaningfully analyze data.

Contents

Medical Uncertainties

1. Uncertainties in Health and Disease
2. Uncertainties in Medical Research
3. Uncertainties in Health Planning and Evaluation
4. Management of Uncertainties: About This Book

Basics of Medical Studies

1. Study Protocol
2. Types of Medical Studies
3. Data Collection
4. Nonsampling Errors and Other Biases

Sampling Methods

1. Sampling Concepts
2. Common Methods of Random Sampling
3. Some Other Methods of Sampling
4. Some Examples of Sample Surveys

Designs for Observational Studies

1. Prospective Studies
2. Retrospective Studies
3. Cross-Sectional Studies
4. Comparative Performance of Prospective, Retrospective, and Cross-Sectional Studies

Medical Experiments

1. Basic Features of Medical Experiments
2. Design of Experiments
3. Choice and Sampling of Units for Laboratory Experiments

Clinical Trials

1. Therapeutic Trials
2. Issues in Clinical Trials
3. Trials Other Than for Therapeutics

Numerical Methods for Representing Variation

1. Types of Measurement
2. Tabular Presentation
3. Rates and Ratios
4. Central and Other Locations
5. Measuring Variability

Presentation of Variation by Figures

1. Graphs for Frequency Distribution
2. Pie, Bar, and Line Diagrams
3. Special Diagrams in Health and Medicine
4. Charts and Maps

Some Quantitative Aspects of Medicine

1. Some Epidemiological Measures of Health and Disease
2. Reference Values
3. Measurement of Uncertainty: Probability
4. Validity of Medical Tests

Clinimetrics and Evidence-Based Medicine

1. Indicators, Indexes, and Scores
2. Clinimetrics
3. Evidence-Based Medicine

Measurement of Community Health

1. Indicators of Mortality
2. Measures of Morbidity
3. Indicators of Social and Mental Health
4. Composite Indexes of Health

Confidence Intervals, Principles of Tests of Significance, and Sample Size

1. Sampling Distributions
2. Confidence Intervals
3. P-Values and Statistical Significance
4. An Initial Debate on Statistical Significance
5. Sample Size Determination in Some Cases

Inference from Proportions

1. One Qualitative Variable
2. Proportions in 2 × 2 Tables
3. Analysis of R × C Tables (Large n)
4. Three-Way Tables

Relative Risk and Odds Ratio

1. Relative and Attributable Risks (Large n)
2. Odds Ratio
3. Stratified Analysis and Sample Size

Inference from Means

1. Comparison of Means in One and Two Groups (Gaussian Conditions): Student’s t-Test
2. Comparison of Means in Three or More Groups (Gaussian Conditions): ANOVA F-Test
3. Non-Gaussian Conditions: Nonparametric Tests for Location
4. When Significant Is Not Significant

Relationships: Quantitative Data

1. Some General Features of a Regression Setup
2. Linear Regression Models
3. Some Issues in Regression
4. Measuring the Strength of a Quantitative Relationship
5. Assessment of Agreement

Relationships: Qualitative Dependent

1. Binary Dependent: Logistic Regression (Large n)
2. Inference from Logistic Coefficients
3. Issues in Logistic Regression
4. Some Models for Qualitative Data
5. Strength of Relationship in Quantitative Variables

Survival Analysis

1. Life Expectancy
2. Analysis of Survival Data
3. Issues in Survival Analysis

Simultaneous Consideration of Several Variables

1. Scope of Multivariate Methods
2. Dependent and Independent Sets of Variables
3. Identification of Structure in the Observations

Quality Considerations

1. Statistical Quality Control in Medical Care
2. Quality of Measurements
3. Quality of Statistical Models: Robustness
4. Quality of Data

Statistical Fallacies

1. Problems with the Sample
2. Errors in Presentation of Findings
3. Inadequate Analysis
4. Misinterpretation

Index

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