Applied biostatistics for the health sciences:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, N.J.
Wiley
2010
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | XV, 648 S. Ill., graph. Darst. |
| ISBN: | 9780470147641 |
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| 100 | 1 | |a Rossi, Richard J. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Applied biostatistics for the health sciences |c Richard J. Rossi |
| 264 | 1 | |a Hoboken, N.J. |b Wiley |c 2010 | |
| 300 | |a XV, 648 S. |b Ill., graph. Darst. | ||
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| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Includes bibliographical references and index | ||
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| 650 | 4 | |a Medical statistics | |
| 650 | 4 | |a Statistics | |
| 650 | 4 | |a Biometry | |
| 650 | 4 | |a Biometry |x methods | |
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Datensatz im Suchindex
| _version_ | 1804141223194132480 |
|---|---|
| adam_text | Titel: Applied biostatistics for the health sciences
Autor: Rossi, Richard J
Jahr: 2010
CONTENTS
PREFACE xi
CHAPTER 1 INTRODUCTION TO
BI0STATIST1CS 1
1.1 What is Biostatistics? 1
1.2 Populations, Samples, and Statistics 2
1.2.1 The Basic Biostatistical Terminology 3
1.2.2 Biomedical Studies 5
1.2.3 Observational Studies Versus
Experiments 7
1.3 Clinical Trials 9
1.3.1 Safety and Ethical Considerations in a
Clinical Trial 9
1.3.2 Types of Clinical Trials 10
1.3.3 The Phases of a Clinical Trial it
1.4 Data Set Descriptions 12
1.4.1 Birth Weight Data Set 12
1.4.2 Body Fat Data Set 12
1.4.3 Coronary Heart Disease Data Set 12
1.4.4 Prostate Cancer Study Data Set 13
1.4.5 Intensive Care Unit Data Set 14
1.4.6 Mammography Experience Study Data
Set 14
1.4.7 Benign Breast Disease Study 15
Glossary 17
Exercises 18
CHAPTER 2 DESCRIBING POPULATIONS 23
2.1 Populations and Variables 23
2.1.1 Qualitative Variables 24
2.1.2 Quantitative Variables 25
2.1.3 Multivariate Data 27
2.2 Population Distributions and Parameters 28
2.2.1 Distributions 29
2.2.2 Describing a Population with
Parameters 33
2.2.3 Proportions and Percentiles 33
2.2.4 Parameters Measuring Centrality
2.2.5 Measures of Dispersion 38
2.2.6 The Coefficient of Variation 41
2.2.7 Parameters for Bivariate
Populations 43
2.3 Probability 46
2.3.1 Basic Probability Rules 48
2.3.2 Conditional Probability 50
2.3.3 Independence 52
2.4 Probability Models 53
2.4.1 The Binomial Probability Model 54
2.4.2 The Normal Probability Model 57
2.4.3 Z Scores 63
Glossary 64
Exercises 65
CHAPTER 3 RANDOM SAMPLING 76
3.1 Obtaining Representative Data 76
3.1.1 The Sampling Plan 78
3.1.2 Probability Samples 78
3.2 Commonly Used Sampling Plans 80
3.2.1 Simple Random Sampling 80
3.2.2 Stratified Random Sampling 84
3.2.3 Cluster Sampling 86
3.2.4 Systematic Sampling 88
3.3 Determining the Sample Size 89
3.3.1 The Sample Size for a Simple Random
Sample 89
3.3.2 The Sample Size for a Stratified
Random Sample 93
3.3.3 Determining the Sample Size in a
Systematic Random Sample 99
Glossary 1oo
Exercises 102
CHAPTER 4 SUMMARIZING RANDOM
SAMPLES_109
4.1 Samples and Inferential Statistics 109
4.2 Inferential Graphical Statistics 110
35 4.2.1 Bar and Pie Charts 111
4.2.2 Boxplots 114
vii
Vlii CONTENTS
4.2.3 Histograms 120
4.2.4 Normal Probability Plots 126
4.3 Numerical Statistics for Univariate Data
Sets 129
4.3.1 Estimating Population Proportions 129
4.3.2 Estimating Population Percentiles 136
4.3.3 Estimating the Mean, Median, and
Mode 137
4.3.4 Estimating the Variance and Standard
Deviation 143
4.3.5 Linear Transformations 148
4.3.6 The Plug-in Rule for Estimation 151
4.4 Statistics for Multivariate Data Sets 153
4.4.1 Graphical Statistics for Bivariate Data
Sets 154
4.4.2 Numerical Summaries for Bivariate
Data Sets 156
4.4.3 Fitting Lines to Scatterplots 161
Glossary 163
Exercises 166
chapter 5 MEASURING THE RELIABILITY OF
STATISTICS 181
5.1 Sampling Distributions 181
5.1.1 Unbiased Estimators 183
5.1.2 Measuring the Accuracy of an
Estimator 184
5.1.3 The Bound on the Error of
Estimation 186
5.2 The Sampling Distribution of a Sample
Proportion 187
5.2.1 The Mean and Standard Deviation of the
Sampling Distribution of p 187
5.2.2 Determining the Sample Size for a
Prespecified Value of the Bound on the
Error Estimation 190
5.2.3 The Central Limit Theorem for p 191
5.2.4 Some Final Notes on the Sampling
Distribution of p 192
5.3 The Sampling Distribution of x 193
5.3.1 The Mean and Standard Deviation of the
Sampling Distribution of 3c 193
5.3.2 Determining the Sample Size for a
Prespecified Value of the Bound on the
Error Estimation 196
5.3.3 The Central Limit Theorem for x 197
5.3.4 The r Distribution 199
5.3.5 Some Final Notes on the Sampling
Distribution of x 201
5.4 Comparisons Based on Two Samples 202
5.4.1 Comparing Two Population
Proportions 203
5.4.2 Comparing Two Population Means 209
5.5 Bootstrapping the Sampling Distribution of a
Statistic 215
Glossary 218
Exercises 219
CHAPTER 6 CONFIDENCE INTERVALS 229
6.1 Interval Estimation 229
6.2 Confidence Intervals 230
6.3 Single Sample Confidence Intervals 232
6.3.1 Confidence Intervals for
Proportions 233
6.3.2 Confidence Intervals for a Mean 236
6.3.3 Large Sample Confidence Intervals
for /J. 237
6.3.4 Small Sample Confidence Intervals
for fx 238
6.3.5 Determining the Sample Size for a
Confidence Interval for the Mean 241
6.4 Bootstrap Confidence Intervals 243
6.5 Two Sample Comparative Confidence
Intervals 244
6.5.1 Confidence Intervals for Comparing
Two Proportions 244
6.5.2 Confidence Intervals for the Relative
Risk 249
Glossary 252
Exercises 253
CHAPTER 7 TESTING STATISTICAL
HYPOTHESES_265
7.1 Hypothesis Testing 265
7.1.1 The Components of a Hypothesis
Test 265
7.1.2 P- Values and Significance Testing 272
7.2 Testing Hypotheses about Proportions 276
7.2.1 Single Sample Tests of a Population
Proportion 276
7.2.2 Comparing Two Population
Proportions 282
7.2.3 Tests of Independence 287
7.3 Testing Hypotheses about Means 295
7.3.1 t-Tests 295
7.3.2 {-Tests for the Mean of a
Population 298
CONTENTS ix
7.3.3 Paired Comparison /-Tests 302
7.3.4 Two Independent Sample /-Tests 307
7.4 Some Final Comments on Hypothesis
Testing 313
Glossary 314
Exercises 315
CHAPTERS SIMPLE LINEAR REGRESSION 333
8.1 Bivariate Data, Scatterplots, and
Correlation 333
8.1.1 Scatterplots 333
8.1.2 Correlation 336
8.2 The Simple Linear Regression Model 340
8.2.1 The Simple Linear Regression
Model 341
8.2.2 Assumptions of the Simple Linear
Regression Model 343
8.3 Fitting a Simple Linear Regression Model 344
8.4 Assessing the Assumptions and Fit of a Simple
Linear Regression Model 347
8.4.1 Residuals 348
8.4.2 Residual Diagnostics 348
8.4.3 Estimating a and Assessing the Strength
of the Linear Relationship 355
8.5 Statistical Inferences based on a Fitted
Model 358
8.5.1 Inferences about/So 359
8.5.2 Inferences about /Si 360
8.6 Inferences about the Response Variable 363
8.6.1 Inferences About fiY X 363
8.6.2 Inferences for Predicting Values
of Y 365
8.7 Some Final Comments on Simple Linear
Regression 366
Glossary 369
Exercises 371
CHAPTER 9 MULTIPLE REGRESSION 383
9.1 Investigating Multivariate Relationships 385
9.2 The Multiple Linear Regression Model 387
9.2.1 The Assumptions of a Multiple
Regression Model 388
9.3 Fitting a Multiple Linear Regression
Model 390
9.4 Assessing the Assumptions of a Multiple
Linear Regression Model 390
9.4.1 Residual Diagnostics 394
9.4.2 Detecting Multivariate Outliers and
Influential Observations 399
9.5 Assessing the Adequacy of Fit of a Multiple
Regression Model 401
9.5.1 Estimating a 401
9.5.2 The Coefficient of Determination 401
9.5.3 Multiple Regression Analysis of
Variance 403
9.6 Statistical Inferences-Based Multiple
Regression Model 406
9.6.1 Inferences about the Regression
Coefficients 406
9.6.2 Inferences about the Response
Variable 408
9.7 Comparing Multiple Regression Models 41 o
9.8 Multiple Regression Models with Categorical
Variables 413
9.8.1 Regression Models with Dummy
Variables 415
9.8.2 Testing the Importance of Categorical
Variables 418
9.9 Variable Selection Techniques 421
9.9.1 Model Selection Using Maximum
*adj 422
9.9.2 Model Selection using BIC 424
9.10 Some Final Comments on Multiple
Regression 425
Glossary 427
Exercises 429
CHAPTER 10 LOGISTIC REGRESSION 446
10.1 Odds and Odds Ratios 447
10.2 The Logistic Regression Model 450
10.2.1 Assumptions of the Logistic
Regression Model 452
10.3 Fitting a Logistic Regression Model 454
10.4 Assessing the Fit of a Logistic Regression
Model 456
10.4.1 Checking the Assumptions of a
Logistic Regression Model 456
10.4.2 Testing for the Goodness of Fit of a
Logistic Regression Model 458
10.4.3 Model Diagnostics 459
10.5 Statistical Inferences Based on a Logistic
Regression Model 465
10.5.1 Inferences about the Logistic
Regression Coefficients 465
10.5.2 Comparing Models 467
10.6 Variable Selection 470
X CONTENTS
10.7 Some Final Comments on Logistic
Regression 473
Glossary 474
Exercises 476
CHAPTER 11 DESIGN OF EXPERIMENTS
487
11.1 Experiments versus Observational
Studies 487
11.2 The Basic Principles of Experimental
Design 490
11.2.1 Terminology 490
11.2.2 Designing an Experiment 491
11.3 Experimental Designs 493
11.3.1 The Completely Randomized
Design 495
11.3.2 The Randomized Block Design 498
11.4 Factorial Experiments 500
11.4.1 Two-Factor Experiments 502
11.4.2 Three-Factor Experiments 504
11.5 Models for Designed Experiments 506
11.5.1 The Model for a Completely
Randomized Design 506
11.5.2 The Model for a Randomized Block
Design 508
11.5.3 Models for Experimental Designs
with a Factorial Treatment
Structure 509
11.6 Some Final Comments of Designed
Experiments 511
Glossary 511
Exercises 513
12.3
12.4
12.5
12.2.1 The ANOV Table for the Randomized
Block Design 534
12.2.2 The Model Assumptions 536
12.2.3 TheF-test 538
12.2.4 Separating the Treatment Means 539
Multifactor Analysis of Variance 542
12.3.1 Two-factor Analysis of Variance 542
12.3.2 Three-factor Analysis of
Variance 550
Selecting the Number of Replicates in
Analysis of Variance 555
12.4.1 Determining the Number of
Replicates from the Power 555
12.4.2 Determining the Number of
Replicates from D 556
Some Final Comments on Analysis of
Variance 557
Glossary 558
Exercises 559
chapter 13 SURVIVAL ANALYSIS
575
13.1 The Kaplan-Meier Estimate of the Survival
Function 576
13.2 The Proportional Hazards Model 582
13.3 Logistic Regression and Survival
Analysis 586
13.4 Some Final Comments on Survival
Analysis 588
Glossary 589
Exercises 590
CHAPTER 12 ANALYSIS OF VARIANCE
520
12.1 Single-Factor Analysis of Variance 521
12.1.1 Partitioning the Total Experimental
Variation 523
12.1.2 The Model Assumptions 524
12.1.3 TheF-test 527
12.1.4 Comparing Treatment Means 528
12.2 Randomized Block Analysis of Variance 533
REFERENCES
APPENDIX A
PROBLEM SOLUTIONS
INDEX
599
605
613
643
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| title | Applied biostatistics for the health sciences |
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| title_full_unstemmed | Applied biostatistics for the health sciences Richard J. Rossi |
| title_short | Applied biostatistics for the health sciences |
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