Basic Statistics A Primer for the Biomedical Sciences

by Dunn, Olive Jean; Clark, Virginia A.

Edition: 4th

ISBN13: 9780470248799

ISBN10: 0470248793

Format: Hardcover

Pub. Date: 2009-07-27

Publisher(s): Wiley

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Summary

There have been significant changes in the way statistics are applied in the biomedical fields over the last decade. Emphasizing biomedical research methodology, this fully updated Fourth Edition of Basic Statistics clearly explains the use of exploratory data analysis, multiple regression, data collection, and nonparametric tests in contemporary studies. Through short, concise, nontechnical presentations, upper undergraduate and graduate students and practicing biostatisticians learn how to interpret and examine data from biomedical studies and apply such tools as sampling, random assignment, and biostatistical analyses in their own research.

Author Biography

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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