Statistical Methods in Medical Research 4ed

vi Contents
9.3 Factorial designs, 246
9.4 Latin squares, 257
9.5Other incomplete designs, 261
9.6 Split-unit designs, 256
10 Analysing non-normal data, 272
10.1 Distribution-free methods, 272
10.2 One-sample tests for
location, 273
10.3 Comparison of two
independent groups, 277
10.4 Comparison of several groups, 285
10.5Rank correlation, 289
10.6 Permutation and Monte
Carlo tests, 292
10.7 The bootstrap and the
jackknife, 298
10.8 Transformations, 306
11 Modelling continuous data, 312
11.1 Analysis of variance
applied to regression, 312
11.2 Errors in both variables, 317
11.3 Straight lines through the
origin, 320
11.4 Regression in groups, 322
11.5Analysis of covariance, 331
11.6 Multiple regression, 337
11.7 Multiple regression in
groups, 347
11.8 Multiple regression in the
analysis of non-orthogonal
data, 354
11.9 Checking the model, 356
11.10 More on data
transformation, 375
12 Further regression models for a
continuous response, 378
12.1 Polynomial regression, 378
12.2 Smoothing and
non-parametric
regression, 387
12.3 Reference ranges, 397
12.4 Non-linear regression, 408
12.5Multilevel models, 418
12.6 Longitudinal data, 430
12.7 Time series, 449
13 Multivariate methods, 455
13.1 General, 455
13.2 Principal components, 456
13.3 Discriminant analysis, 464
13.4 Cluster analysis, 481
13.5Concluding remarks, 483
14 Modelling categorical data, 485
14.1 Introduction, 485
14.2 Logistic regression, 488
14.3 Polytomous regression, 496
14.4 Poisson regression, 499
15Empirical methods for
categorical data, 503
15.1 Introduction, 503
15.2 Trends in proportions, 504
15.3 Trends in larger
contingency tables, 509
15.4 Trends in counts, 511
15.5 Other components of x 2 ,512
15.6 Combination of 2 2
tables, 516
15.7 Combination of larger
tables, 521
15.8 Exact tests for
contingency tables, 524
16 Further Bayesian methods, 528
16.1 Background, 528
16.2 Prior and posterior
distributions, 529
16.3 The Bayesian linear
model, 538
16.4 Markov chain Monte
Carlo methods, 548
16.5Model assessment and
model choice, 560
17 Survival analysis, 568
17.1 Introduction, 568
17.2 Life-tables, 569
17.3 Follow-up studies, 571
17.4 Sampling errors in the
life-table, 574
17.5The Kaplan±Meier
estimator, 575
17.6 The logrank test, 576
17.7 Parametric methods, 582
17.8 Regression and
proportional-hazards
models, 583
17.9 Diagnostic methods, 588