- ISBN: 9780470248799 | 0470248793
- Cover: Hardcover
- Copyright: 7/27/2009
The late Olive Jean Dunn, PhD, was Professor Emerita of Biostatistics and Biomathematics at the University of California, Los Angeles. Dr. Dunn's academic career spanned over forty years and included significant contributions to statistical research. She was a Fellow of the American Statistical Association, the American Association for the Advancement of Science, and the American Public Health Association, as well as coauthor of Applied Statistics: Analysis of Variance and Regression, Third Edition (Wiley). VIRGINIA A. CLARK, PhD, is Professor Emerita of Biostatistics and Biomathematics at the University of California, Los Angeles. A Fellow of the American Statistical Association, Dr. Clark has coauthored over ninety journal articles and is coauthor of Applied Statistics: Analysis of Variance and Regression, Third Edition (Wiley).
Preface to the Fourth Edition | p. xiii |
Initial Steps | p. 1 |
Reasons for Studying Biostatistics | p. 1 |
Initial Steps in Designing a Biomedical Study | p. 2 |
Setting Objectives | p. 2 |
Making a Conceptual Model of the Disease Process | p. 3 |
Estimating the Number of Persons with the Risk Factor or Disease | p. 4 |
Common Types of Biomedical Studies | p. 5 |
Surveys | p. 6 |
Experiments | p. 7 |
Clinical Trials | p. 7 |
Field Trials | p. 9 |
Prospective Studies | p. 9 |
Case/Control Studies | p. 10 |
Other Types of Studies | p. 10 |
Rating Studies by the Level of Evidence | p. 11 |
Consort | p. 11 |
Problems | p. 12 |
References | p. 12 |
Populations and Samples | p. 13 |
Basic Concepts | p. 13 |
Definitions of Types of Samples | p. 15 |
Simple Random Samples | p. 15 |
Other Types of Random Samples | p. 15 |
Reasons for Using Simple Random Samples | p. 17 |
Methods of Selecting Simple Random Samples | p. 17 |
Selection of a Small Simple Random Sample | p. 17 |
Tables of Random Numbers | p. 17 |
Sampling With and Without Replacement | p. 19 |
Application of Sampling Methods in Biomedical Studies | p. 19 |
Characteristics of a Good Sampling Plan | p. 19 |
Samples for Surveys | p. 20 |
Samples for Experiments | p. 21 |
Samples for Prospective Studies | p. 23 |
Samples for Case/Control Studies | p. 23 |
Problems | p. 25 |
References | p. 26 |
Collecting and Entering Data | p. 27 |
Initial Steps | p. 27 |
Decide What Data You Need | p. 28 |
Deciding How to Collect the Data | p. 29 |
Testing the Collection Process | p. 30 |
Data Entry | p. 31 |
Screening the Data | p. 33 |
Code Book | p. 33 |
Problems | p. 34 |
References | p. 34 |
Frequency Tables and Their Graphs | p. 35 |
Numerical Methods of Organizing Data | p. 36 |
An Ordered Array | p. 36 |
Stem and Leaf Tables | p. 36 |
The Frequency Table | p. 38 |
Relative Frequency Tables | p. 40 |
Graphs | p. 40 |
The Histogram: Equal Class Intervals | p. 41 |
The Histogram: Unequal Class Intervals | p. 41 |
Areas Under the Histogram | p. 43 |
The Frequency Polygon | p. 44 |
Histograms with Small Class Intervals | p. 45 |
Distribution Curves | p. 45 |
Problems | p. 47 |
References | p. 47 |
Measures of Location and Variability | p. 49 |
Measures of Location | p. 50 |
The Arithmetic Mean | p. 50 |
The Median | p. 51 |
Other Measures of Location | p. 52 |
Measures of Variability | p. 52 |
The Variance and the Standard Deviation | p. 52 |
Other Measures of Variability | p. 54 |
Sampling Properties of the Mean and Variance | p. 55 |
Considerations in Selecting Appropriate Statistics | p. 57 |
Relating Statistics and Study Objectives | p. 57 |
Relating Statistics and Data Quality | p. 58 |
Relating Statistics to the Type of Data | p. 58 |
A Common Graphical Method for Displaying Statistics | p. 60 |
Problems | p. 61 |
References | p. 62 |
The Normal Distribution | p. 63 |
Properties of the Normal Distribution | p. 64 |
Areas Under the Normal Curve | p. 65 |
Computing the Area Under a Normal Curve | p. 66 |
Linear Interpolation | p. 68 |
Interpreting Areas as Probabilities | p. 70 |
Importance of the Normal Distribution | p. 70 |
Examining Data for Normality | p. 72 |
Using Histograms and Box Plots | p. 72 |
Using Normal Probability Plots or Quantile-Quantile Plots | p. 72 |
Transformations | p. 75 |
Finding a Suitable Transformation | p. 76 |
Assessing the Need for a Transformation | p. 77 |
Problems | p. 77 |
References | p. 78 |
Estimation of Population Means: Confidence Intervals | p. 79 |
Confidence Intervals | p. 80 |
An Example | p. 80 |
Definition of Confidence Interval | p. 81 |
Choice of Confidence Level | p. 82 |
Sample Size Needed for a Desired Confidence Interval | p. 83 |
The t Distribution | p. 83 |
Confidence Interval for the Mean Using the t Distribution | p. 85 |
Estimating the Difference Between Two Means: Unpaired Data | p. 86 |
The Distribution of &Xbar;1 - &Xbar;2 | p. 86 |
Confidence Intervals for ¿1 - ¿2: Known Variance | p. 87 |
Confidence Intervals for ¿1 - ¿2: UnKnown Variance | p. 88 |
Estimating the Difference Between Two Means: Paired Comparison | p. 89 |
Problems | p. 91 |
References | p. 93 |
Tests of Hypotheses on Population Means | p. 95 |
Tests of Hypotheses for a Single Mean | p. 96 |
Test for a Single Mean When ¿ Is Known | p. 96 |
One-Sided Tests When ¿ Is Known | p. 99 |
Summary of Procedures for Test of Hypotheses | p. 100 |
Test for a Single Mean When ¿ Is Unknown | p. 101 |
Tests for Equality of two Means: Unpaired Data | p. 103 |
Testing for Equality of Means When ¿ Is Known | p. 103 |
Testing for Equality of Means When ¿ Is Unknown | p. 104 |
Testing for Equality of Means: Paired Data | p. 107 |
Concepts Used in Statistical Testing | p. 108 |
Decision to Accept or Reject | p. 108 |
Two Kinds of Error | p. 109 |
An Illustration of ß | p. 110 |
Sample Size | p. 111 |
Confidence Intervals Versus Tests | p. 113 |
Correcting for Multiple Testing | p. 114 |
Reporting the Results | p. 115 |
Problems | p. 115 |
References | p. 116 |
Variances: Estimation and Tests | p. 117 |
Point Estimates for Variances and Standard Deviations | p. 118 |
Testing Whether Two Variances Are Equal: F Test | p. 118 |
Approximate t Test | p. 121 |
Other Tests | p. 122 |
Problems | p. 123 |
References | p. 123 |
Categorical Data: Proportions | p. 125 |
Single Population Proportion | p. 126 |
Graphical Displays of Proportions | p. 126 |
Samples from Categorical Data | p. 128 |
The Normal Approximation to the Binomial | p. 129 |
Use of the Normal Approximation to the Binomial | p. 129 |
Continuity Correction | p. 130 |
Confidence Intervals for a Single Population Proportion | p. 130 |
Confidence Intervals for the Difference in Two Proportions | p. 131 |
Tests of Hypothesis for Population Proportions | p. 133 |
Tests of Hypothesis for a Single Population Proportion | p. 133 |
Testing the Equality of Two Population Proportions | p. 134 |
Sample Size for Testing Two Proportions | p. 136 |
Data Entry and Analysis Using Statistical Programs | p. 137 |
Problems | p. 138 |
References | p. 139 |
Categorical Data: Analysis of Two-Way Frequency Tables | p. 141 |
Different Types of Tables | p. 142 |
Tables Based on a Single Sample | p. 142 |
Tables Based on Two Samples | p. 143 |
Tables Based on Matched or Paired Samples | p. 144 |
Relationship Between Type of Study Design and Type of Table | p. 145 |
Relative Risk and Odds Ratio | p. 146 |
Relative Risk | p. 146 |
Odds Ratios | p. 147 |
Chi-Square Tests for Frequency Tables: Two-by-Two Tables | p. 150 |
Chi-Square Test for a Single Sample: Two-by-Two Tables | p. 150 |
Chi-Square Test for Two Samples: Two-by-Two Tables | p. 154 |
Chi-Square Test for Matched Samples: Two-by-Two Tables | p. 155 |
Assumptions for the Chi-Square Test | p. 156 |
Necessary Sample Size: Two-by-Two Tables | p. 156 |
The Continuity Correction: Two-by-Two Tables | p. 157 |
Chi-Square Tests for Larger Tables | p. 158 |
Chi-Square for Larger Tables: Single Sample | p. 158 |
Interpreting a Significant Test | p. 159 |
Chi-Square Test for Larger Tables; More Than Two Samples or Outcomes | p. 161 |
Necessary Sample Size for Large Tables | p. 161 |
Remarks | p. 162 |
Problems | p. 162 |
References | p. 164 |
Regression and Correlation | p. 165 |
The Scatter Diagram: Single Sample | p. 166 |
Linear Regression: Single Sample | p. 168 |
Least-Squares Regression Line | p. 168 |
Interpreting the Regression Coefficients | p. 170 |
Plotting the Regression Line | p. 170 |
The Meaning of the Least-Squares Line | p. 170 |
The Variance of the Residuals | p. 171 |
Model Underlying Single-Sample Linear Regression | p. 172 |
Confidence Intervals in Single-Sample Linear Regression | p. 174 |
Tests of Hypotheses for Regression Line from a Single Sample | p. 176 |
The Correlation Coefficient for Two Variables From a Single Sample | p. 177 |
Calculation of the Correlation Coefficient | p. 177 |
The Meaning of the Correlation Coefficient | p. 177 |
The Population Correlation Coefficient | p. 179 |
Confidence Intervals for the Correlation Coefficient | p. 179 |
Test of Hypothesis that ¿ = 0 | p. 179 |
Interpreting the Correlation Coefficient | p. 180 |
Linear Regression Assuming the Fixed-X Model | p. 180 |
Model Underlying the Fixed-X Linear Regression | p. 181 |
Linear Regression Using the Fixed-X Model | p. 181 |
Other Topics in Linear Regression | p. 183 |
Use of Transformations in Linear Regression | p. 183 |
Effect of Outliers from the Regression Line | p. 184 |
Multiple Regression | p. 184 |
Problems | p. 184 |
References | p. 187 |
Nonparametric Statistics | p. 189 |
The Sign Test | p. 190 |
Sign Test for Large Samples | p. 190 |
Sign Test When the Sample Size Is Small | p. 191 |
The Wilcoxon Signed Ranks Test | p. 192 |
Wilcoxon Signed Ranks Test for Large Samples | p. 192 |
Wilcoxon Signed Ranks Test for Small Samples | p. 194 |
The Wilcoxon-Mann-Whitney Test | p. 195 |
Wilcoxon Rank Sum Test for Large Samples | p. 195 |
Wilcoxon Rank Sum Test for Small Samples | p. 197 |
Spearman's Rank Correlation | p. 198 |
Problems | p. 199 |
References | p. 199 |
Introduction to Survival Analysis | p. 201 |
Survival Analysis Data | p. 202 |
Describing Time to an Event | p. 202 |
Example of Measuring Time to an Event | p. 202 |
Survival Functions | p. 204 |
The Death Density Function | p. 204 |
The Cumulative Death Distribution Function | p. 205 |
The Survival Function | p. 206 |
The Hazard Function | p. 207 |
Computing Estimates of f(t), S(t), and h(t) | p. 208 |
Clinical Life Tables | p. 209 |
Kaplan-Meier Estimate | p. 212 |
Comparison of Clinical Life Tables and the Kaplan-Meier Method | p. 214 |
Additional Analyses Using Survival Data | p. 215 |
Comparing the Equality of Survival Functions | p. 215 |
Regression Analysis of Survival Data | p. 216 |
Problems | p. 216 |
References | p. 216 |
Statistical Tables | p. 219 |
Answers to Selected Problems | p. 235 |
Computer Statistical Program Resources | p. 243 |
Computer Systems for Biomedical Education and Research | p. 243 |
A Brief Indication of Statistics Computer Program Advances and Some Relevant Publications Since 2000 | p. 244 |
Choices of Computer Statistical Software | p. 248 |
Bibliography | p. 249 |
Index | p. 253 |
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