Statistical Concepts and Applications in Clinical Medicine

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ISBN: 9781584882084 | 1584882085
Cover: Hardcover
Copyright: 10/28/2004

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Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment. The authors present each consultative problem in its original form, then describe the process of problem formulation, develop the appropriate statistical models, and interpret the statistical analysis in the context of the real problem. Their treatment provides clear, accessible explanations of statistical methods. The text includes end-of-chapter exercises that help develop formulatory, analytic, and interpretative skills.

1 The Field of Application

(30)

1.1 The role of the consulting statistician

(1)

1.2 A challenging problem in differential diagnosis

(4)

1.3 Identifying the problem

(2)

1.4 Communication with practitioners

(1)

1.5 Components of the medical process

(4)

1.6 Experience

(3)

1.7 Observation

(1)

1.8 Direct measurement

(1)

1.9 Indirect measurement

(2)

1.10 Diagnosis

(3)

1.11 Prognosis

(1)

1.12 Bibliographic notes

(1)

1.13 Problems

(6)

2 Relating the Present Patient to Past Experience

(14)

2.1 Introduction

(1)

2.2 The referred patient

(1)

2.3 Data set of past experience

(1)

2.4 Incomplete data sets

(1)

2.5 Measurement problems

(1)

2.6 Referral and selection

(1)

2.7 Referral of the present patient R

(1)

2.8 Selection on the basis of v

(2)

2.9 Selection independently with respect to v and u

(1)

2.10 Referral and selection for assay

(1)

2.11 Referral and selection for genetic counselling

(1)

2.12 Bibliographic notes

(1)

2.13 Problems

(4)

3 A Review of Statistical Methodology

(32)

3.1 Introduction

(1)

3.2 Maximal parametric modelling

(1)

3.3 Standard distributions

(2)

3.4 Multivariate normal regression model

(2)

3.5 Recursive formulae

(2)

3.6 Categorical regression modelling

(5)

3.6.1 Alternative models

(1)

3.6.2 The d-category model

(2)

3.7 Lattice testing towards a working model

(1)

3.8 Testing a single hypothesis

(2)

3.9 The lattice of hypotheses

(1)

3.10 Testing within a lattice

(3)

3.11 Measures of atypicality

(6)

3.11.1 The multivariate normal model

(1)

3.11.2 Extrapolation index

(1)

3.11.3 The logistic regression model

(4)

3.12 Concordance of data and model

(4)

3.12.1 Tests of normality

(1)

3.12.2 Transformations to normality

(2)

3.12.3 Atypicality

(1)

3.12.4 Regression diagnostics

(1)

3.12.5 Influence in terms of Kullback-Liebler divergences

(1)

3.13 Bibliographic notes

(2)

3.14 Problems

(3)

4 Further Statistical Methodology

(36)

4.1 Introduction

(1)

4.2 Compositional regression analysis

(4)

4.2.1 The nature of compositional data

(1)

4.2.2 Covariance structures for compositions

(2)

4.2.3 Parametric classes of distributions on the simplex

(1)

4.2.4 A methodology for compositional data analysis

(1)

4.2.5 Assessment of conditional distributions for the compositional regression model

(1)

4.3 The complete separation problem

(4)

4.3.1 Construction of a fair prior

(3)

4.4 Diagnosis with tree-structured types

(3)

4.5 Mixed-effects models

(1)

4.6 Gibbs sampling

(5)

4.7 Biplots

(11)

4.7.1 Unconstrained multivariate data

(4)

4.7.2 Compositional data

(3)

4.7.3 Coincident vertices and proportionality

101

(1)

4.7.4 Subsets of vertices and subcompositional analysis

101

(1)

4.7.5 Orthogonal links and subcoinpositional independence

102

(1)

4.7.6 Composition markers

102

(2)

4.7.7 Differences between unconstrained and compositional biplots

104

(1)

4.8 Non-parametric modelling

105

(4)

4.8.1 Introduction

105

(1)

4.8.2 Kernel density estimation of an unconditional density function

105

(1)

4.8.3 Computation of atypicality indices

106

(2)

4.8.4 Some typical kernels

108

(1)

4.8.5 Kernel density estimation of a conditional kernel density function

108

(1)

4.9 Bibliographic notes

109

(1)

4.10 Problems

109

(4)

5 Experience

113

(50)

5.1 Introduction

113

(1)

5.2 Single measurement variability

113

(9)

5.2.1 Plasma concentration of potassium

114

(4)

5.2.2 Urinary excretion rate of pregnenetriol

118

(4)

5.3 Multiple measurement variability

122

(19)

5.3.1 Cortisol-cortisone variability in bilateral hyperplasia

122

(6)

5.3.2 Coagulation measurements in genetic counselling in haemophilia

128

(6)

5.3.3 Experience of adenoma in Conn's syndrome

134

(7)

5.4 Conditional variability

141

(9)

5.4.1 Anti-diuretic hormone variability in healthy persons

141

(4)

5.4.2 Calcium content of bones

145

(5)

5.5 Compositional variability

150

(4)

5.5.1 Ulcerative colitis and Crohn's disease

151

(1)

5.5.2 Comparison of steroid metabolite concentrations in normal adults and children

152

(2)

5.6 Multivariate binary data

154

(1)

5.6.1 Describing experience in Keratoconjunctivitis sicca

154

(1)

5.7 Bibliographic notes

155

(1)

5.8 Problems

156

(7)

6 Observation and Measurement

163

(24)

6.1 Introduction

163

(1)

6.2 The components of an observational problem

163

(4)

6.3 An observer error study of a diagnostic ratio

167

(5)

6.4 An observer error study of multivariate heart measurements

172

(1)

6.5 An observer error study of cell counts

173

(2)

6.6 A comparison of large and small X-rays for diagnosis

175

(5)

6.7 Bacteria counts

180

(1)

6.8 Bibliographic notes

181

(1)

6.9 Problems

182

(5)

7 Indirect Measurement: Assay and Calibration

187

(26)

7.1 Introduction

187

(3)

7.1.1 Simple linear calibration

188

(1)

7.1.2 Non-linear calibration

189

(1)

7.2 Calibration of methods for aldosterone

190

(3)

7.3 Glucose calibration

193

(2)

7.4 Calibration of foetal age by crown rump length

195

(4)

7.5 Radioinnnumoassay of angiotensin II

199

(3)

7.6 Calibration of tobramycin

202

(4)

7.7 Imprecision

206

(2)

7.8 Bibliographic notes

208

(1)

7.9 Problems

208

(5)

8 Diagnosis

213

(30)

8.1 Introduction

213

(1)

8.2 Differential diagnosis in Conn's syndrome

214

(9)

8.2.1 Logistic form of binary regression analysis

215

(2)

8.2.2 Influential cases

217

(2)

8.2.3 Normal form of binary regression analysis

219

(1)

8.2.4 Diagnostic assessments for new cases

220

(2)

8.2.5 Reliability curves for new cases

222

(1)

8.2.6 General comments on the effectiveness of the diagnostic system

222

(1)

8.3 Screening of rheumatoid arthritis patients

223

(8)

8.3.1 Logistic binary regression model

224

(4)

8.3.2 Weighted kernel diagnostic assessments

228

(3)

8.3.3 Multivariate binary kernel diagnostic assessments

231

(1)

8.3.4 Diagnostic assessments for new cases

231

(1)

8.4 Genetic counselling and haemophilia

231

(3)

8.4.1 Analysis of the family tree

232

(1)

8.4.2 Analysis of the data set of coagulation measurement

233

(1)

8.5 Cushing's syndrome

234

(1)

8.6 Bibliographic notes

235

(1)

8.7 Problems

235

(8)

9 Special Aspects of Diagnosis

243

(36)

9.1 Introduction

243

(1)

9.2 Diagnostic system transfer

244

(6)

9.3 Clinic amalgamation

250

(5)

9.4 Imprecision in the feature vector

255

(6)

9.4.1 Parametric modelling for two types

256

(5)

9.5 Missing features: non-toxic goitre

261

(3)

9.6 Uncertainty of type

264

(4)

9.7 Cushing's syndrome

268

(3)

9.8 Bibliographic notes

271

(1)

9.9 Problems

271

(8)

10 Prognosis and Treatment

279

(18)

10.1 Introduction

279

(3)

10.2 A prognostic study of paediatric head injury

282

(2)

10.3 Prognosis and cervical cancer

284

(1)

10.4 Kidney function

285

(2)

10.4.1 Prediction of NEP Dose

286

(1)

10.4.2 Incidence of side effects

287

(1)

10.5 Cutaneous malignant melanoma

287

(5)

10.5.1 Five-year survival

288

(2)

10.5.2 Survival prospects

290

(2)

10.6 Bibliographic notes

292

(1)

10.7 Problems

293

(4)

11 Assessment

297

(24)

11.1 Introduction

297

(1)

11.2 Inferential tasks, statements and trials

298

(1)

11.2.1 Inferential tasks

298

(1)

11.2.2 Previous experience and training sets

299

(1)

11.2.3 Inferential trials

299

(1)

11.3 Measures of normative comparison

299

(4)

11.3.1 Normative model and system

299

(1)

11.3.2 Nature of comparisons

300

(1)

11.3.3 Measures of performance

300

(2)

11.3.4 Measures associated with normal assessments

302

(1)

11.4 Sequential inferential tasks

303

(3)

11.4.1 Subject assessment profiles for a sequential inferential task: Doctor's trilemma

303

(3)

11.5 Some specific inferential tasks

306

(4)

11.5.1 Diagnostic inferential tasks

306

(1)

11.5.2 Predictive and prognostic inferential tasks

307

(1)

11.5.3 Calibrative inferential tasks

308

(2)

11.6 Distributions of inferential statements

310

(1)

11.7 Two studies involving inferential tasks

311

(5)

11.7.1 Doctor's trilemma

311

(2)

11.7.2 Statistician's syndrome

313

(3)

11.8 Bibliographic notes

316

(1)

11.9 Problems

317

(4)

Appendix A Data and Software

321

(6)

A.1 Aldosterone

321

(1)

A.2 Angiotensin II

321

(1)

A.3 Auditory dysfunction

321

(1)

A.4 Bacteria

322

(1)

A.5 Bilateral hyperplasia

322

(1)

A.6 Calcium contents

322

(1)

A.7 Cells

322

(1)

A.8 Cervical cancer

322

(1)

A.9 Conn's syndrome

323

(1)

A.10 Crohn's disease

323

(1)

A.11 Crown rump length

323

(1)

A.12 Cushing's syndrome

323

(1)

A.13 Cutaneous malignant melanoma

324

(1)

A.14 Diagnostic ratio

324

(1)

A.15 Glucose

324

(1)

A.16 Goitre

324

(1)

A.17 Haemophilia

325

(1)

A.18 Hormone

325

(1)

A.19 Keratoconjunctivitis sicca

325

(1)

A.20 Nephrology

325

(1)

A.21 Potassium

325

(1)

A.22 Pregnenetriol

326

(1)

A.23 Statistician's syndrome

326

(1)

A.24 Tobramycin

326

(1)

A.25 X-rays

326

(1)

References

327

(6)

Author index

333

(2)

Subject index

335

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Statistical Concepts and Applications in Clinical Medicine

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