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Biostatistics Decoded

Biostatistics Decoded

Autorzy
Wydawnictwo John Wiley and Sons Ltd
Data wydania 21/06/2019
Liczba stron 400
Forma publikacji książka w twardej oprawie
Poziom zaawansowania Dla profesjonalistów, specjalistów i badaczy naukowych
ISBN 9781119584209
Kategorie Epidemiologia i statystyka medyczna, Prawdopodobieństwo i statystyka
557.00 PLN (z VAT)
$149.07 / €124.39 / £111.86 /
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Dostawa 14 dni
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Opis książki

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.

Biostatistics Decoded

Spis treści

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

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