John Wiley & Sons Biostatistics Decoded Cover Biostatistics Decoded covered a large number of statistical methods that are mainly applied to clini.. Product #: 978-1-119-58420-9 Regular price: $103.81 $103.81 Auf Lager

Biostatistics Decoded

Oliveira, A. Gouveia

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2. Auflage Oktober 2020
496 Seiten, Hardcover
Handbuch/Nachschlagewerk

ISBN: 978-1-119-58420-9
John Wiley & Sons

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Biostatistics Decoded covered a large number of statistical methods that are mainly applied to clinical and epidemiological research, as well as a comprehensive discussion of study designs for observational research and clinical trials, two important concerns for the clinical researcher.

In this second edition, new material is included covering statistical methods and study designs that are used to analyse research. Following the same methodology used in the first edition, the chapters are presented in two levels of detail, one for the reader who wishes only to understand the rationale behind each statistical method, and one for the reader who wishes to understand the computations

Key features include:
* Extensive coverage of the design and analysis of experiments for basic science research
* Experimental designs are presented together with the statistical methods
* The rationale of all forms of ANOVA is explained with simple mathematics
* A comprehensive presentation of statistical tests for multiple comparisons
* Calculations for all statistical methods are illustrated with examples and explained step-by-step.

This book presents biostatistical concepts and methods in a way that is accessible to anyone, regardless of his or her knowledge of mathematics. The topics selected for this book cover will meet the needs of clinical professionals to readers in basic science research.

1. Populations and samples 1

1.1 The object of biostatistics 1

1.2 Scales of measurement 3

1.3 Central tendency measures 6

1.4 Sampling 9

1.5 Inferences from samples 12

1.6 Measures of location and dispersion 15

1.7 The standard deviation 17

1.8 The n - 1 divisor 18

1.9 Degrees of freedom 21

1.10 Variance of binary variables 21

1.11 Properties of means and variances 21

1.12 Descriptive statistics 24

1.13 Sampling variation 28

1.14 The normal distribution 30

1.15 The central limit theorem 32

1.16 Properties of the normal distribution 32

1.17 Probability distribution of sample means 35

1.18 The standard error of the mean 36

1.19 The value of the standard error 40

1.20 Distribution of sample proportions 41

1.21 Convergence of binomial to normal distribution 44

2. Descriptive studies 47

2.1 Designing a research 47

2.2 Study design 48

2.3 Classification of descriptive studies 50

2.4 Cross-sectional studies 52

2.5 Inferences from means 53

2.6 Confidence intervals 55

2.7 Statistical tables 56

2.8 The case of small samples 58

2.9 Student's t distribution 61

2.10 Statistical tables of the t distribution 64

2.11 Inferences from proportions 66

2.12 Statistical tables of the binomial distribution 68

2.13 Sample size requirements 69

2.14 Longitudinal studies 72

2.15 Incidence studies 74

2.16 Cohort studies 75

2.17 Inference from incidence studies 79

2.18 Standardization 82

2.19 Time-to-event cohort studies 85

2.20 The actuarial method 87

2.21 The Kaplan-Meier method 90

2.22 Probability sampling 94

2.23 Simple random sampling 95

2.24 Replacement in sampling 96

2.25 Stratified sampling 99

2.26 Multistage sampling 104

3. Analytical studies 111

3.1 Objectives of analytical studies 111

3.2 Measures of association 112

3.3 Odds, logits and odds-ratios 113

3.4 Attributable risk 115

3.5 Classification of analytical studies 117

3.6 Uncontrolled analytical studies 118

3.7 Comparative analytical studies 120

3.8 Hybrid analytical studies 124

3.9 Non-probability sampling in analytical studies 126

3.10 Comparison of two means 127

3.11 Comparison of two means from small samples 130

3.12 Comparison of two proportions 133

4. Statistical tests 137

4.1 The null and alternative hypotheses 137

4.2 The z-test 138

4.3 The p-value 141

4.4 Student's t-test 143

4.5 The binomial test 146

4.6 The chi-square test 148

4.7 The table of the chi-square distribution 152

4.8 Analysis of variance 154

4.9 Partitioning the sum of squares 157

4.10 Statistical tables of the F distribution 162

4.11 The ANOVA table 163

5. Aspects of statistical tests 165

5.1 One-sided tests 165

5.2 Power of a statistical test 169

5.3 Sample size estimation 171

5.4 Multiple comparisons 175

5.5 Scale transformation 177

5.6 Non-parametric tests 178

6. Cross-sectional studies 183

6.1 Linear regression 183

6.2 The least squares method 185

6.3 Linear regression estimates 189

6.4 Regression and correlation 194

6.5 The F-test in linear regression 197

6.6 Interpretation of regression analysis results 200

6.7 Multiple regression 201

6.8 Regression diagnostics 205

6.9 Selection of predictor variables 209

6.10 Independent nominal variables 211

6.11 Interaction 213

6.12 Nonlinear regression 217

7. Case-control studies 219

7.1 Analysis of case-control studies 219

7.2 Logistic regression 220

7.3 The method of maximum likelihood 223

7.5 Estimation of the logistic regression model 225

7.5 The likelihood ratio test 228

7.6 Interpreting the results of logistic regression 229

7.7 Regression coefficients and odds ratios 230

7.8 Applications of logistic regression 231

7.9 The ROC curve 233

7.10 Model validation 236

8. Cohort studies 241

8.1 Repeated measurements 241

8.2 The paired t-test 241

8.3 McNemar's test 244

8.4 Generalized linear models 245

8.5 The logrank test 248

8.6 The adjusted logrank test 251

8.7 The incidence rate ratio 253

8.8 The Cox proportional hazards model 254

8.9 Assumptions of the Cox model 259

8.10 Interpretation of Cox regression 261

9. Measurement 265

9.1 Construction of clinical questionnaires 265

9.2 Factor analysis 266

9.3 Interpretation of factor analysis 270

9.4 Factor rotation 272

9.5 Factor scores 275

9.6 Reliability 276

9.7 Concordance 282

9.8 Validity 289

9.9 Validation of diagnostic tests 290

10. Experimental studies 293

10.1 Main design features and classification 293

10.2 Experimental controls 296

10.3 Replicates 297

10.4 Classification of experimental designs 299

10.5 Completely Randomized Design 300

10.6 Interaction 306

10.7 Full factorial design 307

10.8 The random effects model 312

10.9 Components of variance 315

10.10 ANOVA model II and model III 317

10.11 Rules for the definition of the error terms 323

10.12 ANOVA with ranks 324

11. Blocking 327

11.1 Randomized Block Design 327

11.2 Generalized Randomized Block design 331

11.3 Incomplete Block Design 333

11.4 Factorial Design with Randomized Blocks 335

11.5 Latin and Greco-Latin Square Design 337

12. Simultaneous inference 341

12.1 Multiple comparisons 341

12.2 Generalist methods 342

12.3 Multiple comparisons of group means 348

12.4 Pairwise comparison of means 349

12.5 Different variances 358

12.6 Comparison to a control 359

12.7 Comparison of post hoc tests 362

12.8 Complex comparisons 362

12.9 Tests of multiple contrasts 367

12.10 A posteriori contrasts 372

12.11 The size of an experiment 375

13. Factorial ANOVA 379

13.1 The n-way ANOVA 379

13.2 The 2k factorial design 381

13.3 The 2k factorial design with blocking 386

13.4 The fractional factorial design 388

14. Nested designs 391

14.1 Split-plot design 391

14.2 Nested (hierarchical) design 396

14.3 Mixed model nested ANOVA 398

14.4 Mixed model nested ANOVA with three sublevels 402

14.5 Pure model II nested ANOVA 406

15. Repeated measures 409

15.1 Repeated measures ANOVA 409

15.2 Repeated measures ANOVA with two factors 414

15.3 ANOVA with several repeated measures 416

15.4 Multivariate tests 418

16. Clinical trials 419

16.1 Classification of clinical trials 419

16.2 The clinical trial population 421

16.3 The efficacy criteria 422

16.4 Controlled clinical trials 424

16.5 The control group 426

16.6 Blinding 427

16.7 Randomization 428

16.8 Non-comparative clinical trials 433

16.9 Regression toward the mean 436

16.10 Non-randomized controlled clinical trials 438

16.11 Classical randomized clinical trial designs 440

16.12 Alternative clinical trial designs 444

16.13 Pragmatic clinical trials 446

16.14 Cluster randomized trials 449

16.15 The size of a clinical trial 454

16.16 Non-inferiority clinical trials 459

16.17 Adaptive clinical trials 465

16.18 Group sequential plans 467

16.19 The alpha spending function 470

16.20 The clinical trial protocol 473

16.21 The data record 474

17. Analysis of clinical trials 477

17.1 General analysis plan 477

17.2 Data preparation 478

17.3 Study populations 480

17.4 Primary efficacy analysis 483

17.5 Analysis of multiple endpoints 485

17.6 Secondary analyses 488

17.7 Safety analysis 490

18. Meta-analysis 493

18.1 Purpose of meta-analysis 493

18.2 Measures of effect 494

18.3 The inverse variance method 496

18.4 The random effects model 503

18.5 Heterogeneity 507

18.6 Publication bias 510

18.7 The forest plot 513

References 515

Index 523
Antonio Gouveia Oliveira is a M.D. with a Ph.D. in Biostatistics from the University of Lisbon, Portugal. For the last 20 years, he has been dedicated to clinical and basic research. He was Professor of Biostatistics in the Medical Schools of the two Universities of Lisbon, Portugal, in the Department of Biostatistics and Bioinformatics of the Medical University of South Carolina, Charleston, USA, and is currently in the Department of Pharmacy of the Federal University of Rio Grande do Norte, Natal, Brazil. He was the founder and C.E.O. of Datamedica, a full-service Contract Research Organization based in Lisbon, Portugal, where he has designed, conducted and analyzed a large number of epidemiologic studies and clinical trials for all the major pharmaceutical companies. He is the author or co-author of over 100 papers published in leading scientific journals.

A. G. Oliveira, Federal University of Rio Grande do Norte, Brazil