482. Biostatistics & Epidemiology

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482. Biostatistics & Epidemiology

 

 

CATEGORY: Medical & Medicine – 500 Courses

COURSE NUMBER: 482

FEES: 555/- INR only

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BOOKS/ MANUALS: Pages

Syllabus

PREFACE TO THE FOURTH EDITION vii
ACKNOWLEDGEMENTS xi
AUTHOR BIOGRAPHY xix
CHAPTER 1. THE SCIENTIFIC METHOD 1
1.1 The Logic of Scientific Reasoning 1
1.2 Variability of Phenomena Requires Statistical Analysis 6
1.3 Inductive Inference: Statistics as the Technology
of the Scientific Method 7
1.4 Design of Studies 8
1.5 How to Quantify Variables 10
1.6 The Null Hypothesis 10
1.7 Why Do We Test the Null Hypothesis? 11
1.8 Types of Errors 13
1.9 Significance Level and Types of Error 15
1.10 Consequences of Type I and Type II Errors 15
CHAPTER 2. A LITTLE BIT OF PROBABILITY 17
2.1 What Is Probability? 17
2.2 Combining Probabilities 18
2.3 Conditional Probability 20
2.4 Bayesian Probability 21
2.5 Odds and Probability 22
2.6 Likelihood Ratio 23
2.7 Summary of Probability 24
CHAPTER 3. MOSTLY ABOUT STATISTICS 27
3.1 Chi-Square for 2 2 Tables 27
3.2 McNemar Test 31
3.3 Kappa 33
3.4 Description of a Population: Use of the Standard
Deviation 34

3.5 Meaning of the Standard Deviation: The Normal
Distribution 37
3.6 The Difference Between Standard Deviation
and Standard Error 39
3.7 Standard Error of the Difference Between Two Means 42
3.8 Z Scores and the Standardized Normal Distribution 44
3.9 The t Statistic 47
3.10 Sample Values and Population Values Revisited 48
3.11 A Question of Confidence 49
3.12 Confidence Limits and Confidence Intervals 51
3.13 Degrees of Freedom 52
3.14 Confidence Intervals for Proportions 52
3.15 Confidence Intervals Around the Difference
Between Two Means 53
3.16 Comparisons Between Two Groups 54
3.17 Z-Test for Comparing Two Proportions 55
3.18 t-Test for the Difference Between Means
of Two Independent Groups: Principles 57
3.19 How to Do a t-Test: An Example 58
3.20 Matched Pair t-Test 60
3.21 When Not to Do a Lot of t-Tests: The Problem
of Multiple Tests of Significance 61
3.22 Analysis of Variance: Comparison Among
Several Groups 63
3.23 Principles Underlying Analysis of Variance 63
3.24 Bonferroni Procedure: An Approach to Making
Multiple Comparisons 66
3.25 Analysis of Variance When There Are Two Independent
Variables: The Two-Factor ANOVA 68
3.26 Interaction Between Two Independent Variables 69
3.27 Example of a Two-Way ANOVA 70
3.28 Kruskal–Wallis Test to Compare Several Groups 71
3.29 Association and Causation: The Correlation Coefficient 71
3.30 Some Points to Remember About Correlation 74
3.31 Causal Pathways 75

3.32 Regression 76
3.33 The Connection Between Linear Regression
and the Correlation Coefficient 79
3.34 Multiple Linear Regression 79
3.35 Summary So Far 81
CHAPTER 4. MOSTLY ABOUT EPIDEMIOLOGY 83
4.1 The Uses of Epidemiology 83
4.2 Some Epidemiologic Concepts: Mortality Rates 84
4.3 Age-Adjusted Rates 86
4.4 Incidence and Prevalence 88
4.5 Standardized Mortality Ratio 90
4.6 Person-Years of Observation 90
4.7 Dependent and Independent Variables 92
4.8 Types of Studies 92
4.9 Cross-Sectional Versus Longitudinal Looks at Data 93
4.10 Measures of Relative Risk: Inferences from Prospective
Studies (the Framingham Study) 97
4.11 Calculation of Relative Risk from Prospective Studies 99
4.12 Odds Ratio: Estimate of Relative Risk from
Case–Control Studies 100
4.13 Attributable Risk 103
4.14 Response Bias 105
4.15 Confounding Variables 108
4.16 Matching 108
4.17 Multiple Logistic Regression 110
4.18 Survival Analysis: Life Table Methods 112
4.19 Cox Proportional Hazards Model 115
4.20 Overlapping Confidence Intervals and Statistical
Significance 117
4.21 Confounding by Indication 117
4.22 Propensity Analysis 118
4.23 Selecting Variables for Multivariate Models 123
4.24 Interactions: Additive and Multiplicative Models 125
4.25 Nonlinear Relationships: J Shape or U Shape 129

CHAPTER 5. MOSTLY ABOUT SCREENING 133
5.1 Sensitivity, Specificity, and Related Concepts 133
5.2 Cutoff Point and Its Effects on Sensitivity and Specificity 140
CHAPTER 6. MOSTLY ABOUT CLINICAL TRIALS 143
6.1 Features of Randomized Clinical Trials 143
6.2 Purposes of Randomization 145
6.3 How to Perform Randomized Assignment 146
6.4 Two-Tailed Test Versus One-Tailed Test 147
6.5 Clinical Trial as “Gold Standard” 148
6.6 Regression Toward the Mean 149
6.7 Intention-to-Treat Analysis 152
6.8 How Large Should the Clinical Trial Be? 153
6.9 What Is Involved in Sample Size Calculation? 155
6.10 How to Calculate Sample Size for the Difference Between
Two Proportions 159
6.11 How to Calculate Sample Size for Testing the Difference
Between Two Means 160
CHAPTER 7. MOSTLY ABOUT QUALITY OF LIFE 163
7.1 Scale Construction 164
7.2 Reliability 164
7.3 Validity 166
7.4 Responsiveness 167
7.5 Some Potential Pitfalls 169
CHAPTER 8. MOSTLY ABOUT GENETIC EPIDEMIOLOGY 171
8.1 A New Scientific Era 171
8.2 Overview of Genetic Epidemiology 173
8.3 Twin Studies 175
8.4 Linkage and Association Studies 176
8.5 LOD Score: Linkage Statistic 179
8.6 Association Studies 180
8.7 Candidate Gene Association Studies 182
8.8 Population Stratification or Population Structure 183

8.9 Family-Based Association and the Transmission
Disequilibrium Test (TDT) 186
8.10 Genomewide Association Studies: GWAS 189
8.11 GWAS Quality Control and Hardy–Weinberg Equilibrium 191
8.12 Quantile by Quantile Plots or Q-Q Plots 192
8.13 Problem of False Positives 195
8.14 Problem of False Negatives 197
8.15 Manhattan Plots 198
8.16 Polygene Scores 199
8.17 Rare Variants and Genome Sequencing 200
8.18 Analysis of Rare Variant Studies 202
8.19 What’s in a Name? SNPs and Genes 203
CHAPTER 9. RISK PREDICTION AND RISK

CLASSIFICATION 205
9.1 Risk Prediction 205
9.2 Additive Value of a Biomarker: Calculation
of Predicted Risk 207
9.3 The Net Reclassification Improvement Index 212
9.4 The Category-Less NRI 213
9.5 Integrated Discrimination Improvement (IDI) 214
9.6 C-Statistic 215
9.7 Caveats 216
9.8 Summary 216
CHAPTER 10. RESEARCH ETHICS AND STATISTICS 217
10.1 What Does Statistics Have to Do with It? 217
10.2 Protection of Human Research Subjects 218
10.3 Informed Consent 220
10.4 Equipoise 222
10.5 Research Integrity 222
10.6 Authorship Policies 223
10.7 Data and Safety Monitoring Boards 224
10.8 Summary 224

Postscript A FEW PARTING COMMENTS ON THE
IMPACT OF EPIDEMIOLOGY ON HUMAN
LIVES 225
Appendix 1. CRITICAL VALUES OF CHI-SQUARE,
Z, AND t 227
Appendix 2. FISHER’S EXACT TEST 229
Appendix 3. KRUSKAL–WALLIS NONPARAMETRIC
TEST TO COMPARE SEVERAL GROUPS 231
Appendix 4. HOW TO CALCULATE A CORRELATION
COEFFICIENT 233
Appendix 5. AGE-ADJUSTMENT 235
Appendix 6. DETERMINING APPROPRIATENESS
OF CHANGE SCORES 239
REFERENCES 243
SUGGESTED READINGS 249
INDEX 253

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