Applied Biostatistical Principles and Concepts. Clinicians’ Guide to Data Analysis and Interpretation

Contents......Page 3
Foreword......Page 7
Preface......Page 10
value, and statistical significance......Page 13
Confounding......Page 20
Null hypothesis and types of errors......Page 22
References......Page 26
Design Process......Page 27
Introduction......Page 28
Why conduct clinical research?......Page 30
Subject  selection......Page 31
Generalization......Page 32
Screening (detection) and diagnostic  (confirmation) tests......Page 33
Balancing benefits and harmful effects in medicine......Page 46
Summary......Page 47
Questions for discussion......Page 49
References......Page 50
Introduction......Page 52
Epidemiologic study designs......Page 53
Nonexperimental  designs......Page 55
Experimental designs (clinical trials)......Page 57
Nonexperimental versus experimental design......Page 59
Measures of disease association or effect......Page 61
Precision, random error, and bias......Page 62
Confounding, covariates, effect measure  modifier, interaction......Page 64
Summary......Page 66
Questions for discussion......Page 67
References......Page 68
Introduction......Page 69
Populations......Page 70
Sample and sampling strategies......Page 71
Biostatistical  reasoning......Page 72
Measures of central tendency and dispersion......Page 73
score statistic......Page 92
Simple and unconditional probability......Page 93
Conditional  probability......Page 94
Independence and conditional probability......Page 95
Summary......Page 96
Questions for discussion......Page 97
References......Page 98
--- Biostatistical Modeling......Page 99
Introduction......Page 100
Variables and sources of variation (variability)......Page 105
Sampling, sample size, and power......Page 107
Research questions, hypothesis testing,  and statistical inference......Page 110
Summary......Page 123
Questions for discussion......Page 124
References......Page 125
Introduction......Page 129
Sample size computation......Page 132
Sample size estimation for single- or one-sample  proportion hypothesis testing......Page 136
One-sample estimation of sample size with outcome mean......Page 138
Two independent samples: Proportions......Page 139
Two independent group means......Page 141
Prospective cohort or two-group comparison  in clinical trials......Page 142
Case–control  study......Page 143
Summary......Page 144
References......Page 145
Introduction......Page 146
Test  statistic......Page 151
test......Page 157
tests......Page 159
Summary......Page 166
References......Page 169
Introduction......Page 171
test)......Page 172
Test for two independent proportions......Page 182
Chi-square test of proportions in two groups......Page 184
Summary......Page 188
Questions for discussion......Page 189
References......Page 190
Statistical inference in 3 or more samples......Page 191
Analysis of variance (ANOVA)?......Page 193
Other hypothesis tests based on ANOVA......Page 202
Summary......Page 208
Questions for discussion......Page 209
References......Page 210
Statistical inference involving relationships or associations......Page 211
Correlation and correlation coefficients......Page 222
Simple linear regression......Page 229
Multiple/multivariable linear regression......Page 237
Logistic regression technique......Page 239
Model building and interpretation......Page 242
Survival analysis: Time-to-event method......Page 249
Poisson  regression......Page 257
Summary......Page 261
References......Page 263
Introduction......Page 266
Big data and implication in evidence discovery......Page 267
Reality in statistical modeling of translational  and clinical science data......Page 270
Tabulation versus regression analysis: When and when not  to use regression......Page 273
Questions for discussion......Page 281
References......Page 282
Appendix......Page 283
Index......Page 287