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9781584882084

Statistical Concepts and Applications in Clinical Medicine

by ;
  • ISBN13:

    9781584882084

  • ISBN10:

    1584882085

  • Format: Hardcover
  • Copyright: 2004-10-28
  • Publisher: Chapman & Hall/

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Summary

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.

Author Biography

Ian J. Lauder is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Hong Kong.

Table of Contents

1 The Field of Application
1(30)
1.1 The role of the consulting statistician
1(1)
1.2 A challenging problem in differential diagnosis
2(4)
1.3 Identifying the problem
6(2)
1.4 Communication with practitioners
8(1)
1.5 Components of the medical process
9(4)
1.6 Experience
13(3)
1.7 Observation
16(1)
1.8 Direct measurement
17(1)
1.9 Indirect measurement
18(2)
1.10 Diagnosis
20(3)
1.11 Prognosis
23(1)
1.12 Bibliographic notes
24(1)
1.13 Problems
25(6)
2 Relating the Present Patient to Past Experience
31(14)
2.1 Introduction
31(1)
2.2 The referred patient
32(1)
2.3 Data set of past experience
32(1)
2.4 Incomplete data sets
33(1)
2.5 Measurement problems
33(1)
2.6 Referral and selection
34(1)
2.7 Referral of the present patient R
34(1)
2.8 Selection on the basis of v
35(2)
2.9 Selection independently with respect to v and u
37(1)
2.10 Referral and selection for assay
38(1)
2.11 Referral and selection for genetic counselling
39(1)
2.12 Bibliographic notes
40(1)
2.13 Problems
41(4)
3 A Review of Statistical Methodology
45(32)
3.1 Introduction
45(1)
3.2 Maximal parametric modelling
45(1)
3.3 Standard distributions
46(2)
3.4 Multivariate normal regression model
48(2)
3.5 Recursive formulae
50(2)
3.6 Categorical regression modelling
52(5)
3.6.1 Alternative models
54(1)
3.6.2 The d-category model
55(2)
3.7 Lattice testing towards a working model
57(1)
3.8 Testing a single hypothesis
57(2)
3.9 The lattice of hypotheses
59(1)
3.10 Testing within a lattice
59(3)
3.11 Measures of atypicality
62(6)
3.11.1 The multivariate normal model
63(1)
3.11.2 Extrapolation index
63(1)
3.11.3 The logistic regression model
64(4)
3.12 Concordance of data and model
68(4)
3.12.1 Tests of normality
68(1)
3.12.2 Transformations to normality
69(2)
3.12.3 Atypicality
71(1)
3.12.4 Regression diagnostics
71(1)
3.12.5 Influence in terms of Kullback-Liebler divergences
72(1)
3.13 Bibliographic notes
72(2)
3.14 Problems
74(3)
4 Further Statistical Methodology
77(36)
4.1 Introduction
77(1)
4.2 Compositional regression analysis
77(4)
4.2.1 The nature of compositional data
77(1)
4.2.2 Covariance structures for compositions
78(2)
4.2.3 Parametric classes of distributions on the simplex
80(1)
4.2.4 A methodology for compositional data analysis
81(1)
4.2.5 Assessment of conditional distributions for the compositional regression model
81(1)
4.3 The complete separation problem
81(4)
4.3.1 Construction of a fair prior
82(3)
4.4 Diagnosis with tree-structured types
85(3)
4.5 Mixed-effects models
88(1)
4.6 Gibbs sampling
89(5)
4.7 Biplots
94(11)
4.7.1 Unconstrained multivariate data
94(4)
4.7.2 Compositional data
98(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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