Rent 9781449623944 | Essentials of Biostatistics In Public Health

Biostatistics

Essentials of Biostatistics in Public Health, Second Edition provides a fundamental and engaging background for students learning to apply and appropriately interpret biostatistics applications in the field of public health.Many examples are drawn directly from the author's remarkable clinical experiences with the renowned Framingham Heart Study, making this text practical, interesting, and accessible for those with little mathematical background. The examples are real, relevant, and manageable in siz... MORE

Acknowledgments	p. vii
Preface	p. ix
Prologue	p. xi
About the Author	p. xiii
Introduction	p. 1
What Is Biostatistics?	p. 2
What Are the Issues?	p. 2
Summary	p. 4
Study Designs	p. 7
Vocabulary	p. 8
Observational Study Designs	p. 8
Randomized Study Designs	... MOREp. 13
The Framingham Heart Study	p. 17
More on Clinical Trials	p. 17
Sample Size Implications	p. 20
Summary	p. 20
Practice Problems	p. 20
Quantifying the Extent of Disease	p. 23
Prevalence	p. 23
Incidence	p. 24
Relationships Between Prevalence and Incidence	p. 26
Comparing the Extent of Disease Between Groups	p. 27
Summary	p. 30
Practice Problems	p. 30
Summarizing Data Collected in the Sample	p. 35
Dichotomous Variables	p. 36
Ordinal and Categorical Variables	p. 40
Continuous Variables	p. 49
Summary	p. 60
Practice Problems	p. 62
The Role of Probability	p. 67
Sampling	p. 67
Basic Concepts	p. 69
Conditional Probability	p. 70
Independence	p. 73
Bayes' Theorem	p. 74
Probability Models	p. 75
Summary	p. 96
Practice Problems	p. 96
Confidence Interval Estimates	p. 101
Introduction to Estimation	p. 101
Confidence Intervals for One Sample, Continuous Outcome	p. 103
Confidence Intervals for One Sample, Dichotomous Outcome	p. 104
Confidence Intervals for Two Independent Samples, Continuous Outcome	p. 106
Confidence Intervals for Matched Samples, Continuous Outcome	p. 110
Confidence Intervals for Two Independent Samples, Dichotomous Outcome	p. 113
Summary	p. 117
Practice Problems	p. 118
Hypothesis Testing Procedures	p. 123
Introduction to Hypothesis Testing	p. 123
Tests with One Sample, Continuous Outcome	p. 130
Tests with One Sample, Dichotomous Outcome	p. 133
Tests with One Sample, Categorical and Ordinal Outcomes	p. 134
Tests with Two Independent Samples, Continuous Outcome	p. 138
Tests with Matched Samples, Continuous Outcome	p. 141
Tests with Two Independent Samples, Dichotomous Outcome	p. 144
Tests with More Than Two Independent Samples, Continuous Outcome	p. 147
Tests for Two or More Independent Samples, Categorical and Ordinal Outcomes	p. 156
Summary	p. 160
Practice Problems	p. 162
Power and Sample Size Determination	p. 169
Issues in Estimating Sample Size for Confidence Intervals Estimates	p. 170
Issues in Estimating Sample Size for Hypothesis Testing	p. 176
Summary	p. 185
Practice Problems	p. 185
Multivariable Methods	p. 189
Confounding and Effect Modification	p. 190
The Cochran-Mantel-Haenszel Method	p. 197
Introduction to Correlation and Regression Analysis	p. 198
Multiple Linear Regression Analysis	p. 206
Multiple Logistic Regression Analysis	p. 210
Summary	p. 213
Practice Problems	p. 214
Nonparametric Tests	p. 219
Introduction to Nonparametric Testing	p. 221
Tests with Two Independent Samples	p. 223
Tests with Matched Samples	p. 229
Tests with More Than Two Independent Samples	p. 236
Summary	p. 240
Practice Problems	p. 241
Survival Analysis	p. 243
Introduction to Survival Data	p. 245
Estimating the Survival Function	p. 247
Comparing Survival Curves	p. 252
Cox Proportional Hazards Regression Analysis	p. 260
Extensions	p. 264
Summary	p. 265
Practice Problems	p. 267
Appendix	p. 271
Glossary	p. 289
Index	p. 299
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