Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.
Author(s): D. R. Cox, Christl A. Donnelly
Edition: 1
Publisher: Cambridge University Press
Year: 2011
Language: English
Pages: 213
Tags: Математика;Теория вероятностей и математическая статистика;Математическая статистика;Прикладная математическая статистика;
Contents......Page 6
Preface......Page 10
1.1 Preliminaries......Page 12
1.2 Components of investigation......Page 13
1.4 Relationship between design and analysis......Page 16
1.5 Experimental and observational studies......Page 17
1.6 Principles of measurement......Page 19
1.7 Types and phases of analysis......Page 20
1.9 Probability models......Page 21
1.10 Prediction......Page 22
1.11 Synthesis......Page 23
Notes......Page 24
2.1 Introduction......Page 25
2.2 Unit of analysis......Page 29
2.3 Types of study......Page 31
2.4 Avoidance of systematic error......Page 32
2.5 Control and estimation of random error......Page 35
2.6 Scale of effort......Page 36
2.7 Factorial principle......Page 37
Notes......Page 39
3.1 Preliminaries......Page 40
3.2.1 Sampling frame......Page 41
3.2.2 Precision enhancement......Page 43
3.2.3 Multi-stage and temporal sampling......Page 45
3.2.4 Less standard sampling methods......Page 46
3.3.1 Primary formulation......Page 48
3.3.2 Precision improvement......Page 51
3.3.3 Factorial experiments......Page 56
3.4 Cross-sectional observational study......Page 57
3.6 Retrospective observational study......Page 59
Notes......Page 62
4.1 Criteria for measurements......Page 64
4.2 Classification of measurements......Page 66
4.3 Scale properties......Page 67
4.4 Classification by purpose......Page 69
4.5 Censoring......Page 72
4.6 Derived variables......Page 73
4.7.1 Generalities......Page 75
4.7.2 Role in model formulation......Page 76
4.7.3 Latent structure and latent class models......Page 79
4.7.4 Measurement error in regression......Page 80
Notes......Page 85
5.1 Introduction......Page 86
5.2 Data auditing......Page 87
5.3 Data screening......Page 88
5.4 Preliminary graphical analysis......Page 93
5.5 Preliminary tabular analysis......Page 97
5.6 More specialized measurement......Page 98
5.7 Discussion......Page 99
6.1 Preliminaries......Page 101
6.2 Nature of probability models......Page 103
6.3 Types of model......Page 108
6.4 Interpretation of probability......Page 115
6.5.1 Generalities......Page 119
6.5.2 Systematic variation......Page 120
6.5.3 Variational structure......Page 123
6.5.4 Unit of analysis......Page 125
Notes......Page 128
7.1.1 Preliminaries......Page 129
7.1.2 Parameters of interest......Page 130
7.2 Nonspecific effects......Page 135
7.2.1 Preliminaries......Page 136
7.2.2 Stable treatment effect......Page 137
7.2.3 Unstable effect......Page 140
7.3 Choice of a specific model......Page 141
Notes......Page 150
8.1 Preliminaries......Page 151
8.2 Confidence limits......Page 152
8.3 Posterior distributions......Page 153
8.4.1 Types of null hypothesis......Page 156
8.4.2 Test of atomic null hypothesis......Page 157
8.4.3 Application and interpretation of p-values......Page 158
8.4.4 Simulation-based procedures......Page 159
8.4.5 Tests of model adequacy......Page 160
8.4.6 Tests of model simplification......Page 161
8.5.1 Generalities......Page 163
8.5.3 Multi-stage formulation......Page 164
8.5.4 Bonferroni correction......Page 165
8.6 Estimates and standard errors......Page 167
8.6.1 A final assessment......Page 168
Notes......Page 169
9.1 Introduction......Page 170
9.2.1 Preliminaries......Page 171
9.2.2 Causality and randomized experiments......Page 172
9.2.3 Observational parallel......Page 175
9.2.4 Qualitative guidelines......Page 176
9.2.5 A further notion......Page 177
9.3 Generality and specificity......Page 178
9.4 Data-generating models......Page 180
9.5.1 Preliminaries......Page 182
9.5.2 Interpretation of interaction......Page 184
9.5.3 Interaction in contingency tables......Page 186
9.5.4 Three-factor and higher-order interactions......Page 187
9.6.1 Types of data......Page 188
9.6.2 Time series analysis......Page 189
9.6.3 Longitudinal data......Page 190
9.7 Publication bias......Page 191
9.8 Presentation of results which inform public policy......Page 192
Notes......Page 194
10.1 Historical development......Page 195
10.2 Some strategic issues......Page 196
10.3 Some tactical considerations......Page 197
10.4 Conclusion......Page 198
References......Page 200
Index......Page 209
