An Introduction to Medical Statistics, Third Edition
Author: 
Martin Bland 
Publisher: 
Oxford University Press 
Copyright: 
2000 
ISBN13: 
9780192632692 
Pages: 
405; paperback 
Price: 
$52.00 



Comment from the Stata technical group
An Introduction to Medical Statistics, Third Edition, by Martin
Bland, is a great introductory statistics text for students in the medical
sciences and is an ideal selfstudy text for medical practitioners. Bland
covers both elementary and advanced (those that would be taught in a
postgraduate course on medical statistics) concepts, clearly delineating the
two. With the advent of the personal computer as a statistical calculator, a
text such as this one becomes all the more important because it emphasizes
concepts over formulas.
After introducing the text, Bland discusses the basic principles of
experimental design, sampling, data summarization, and graphs. The text then
focuses on probability theory and the normal distribution, yet this
discussion is brief and to the point. The text then explains the standard
inference for means and proportions, tests of significance, the t
statistic, regression, and correlation, with an emphasis on how these topics
relate to medical data. The remainder of An Introduction to Medical
Statistics, Third Edition is devoted to advanced topics, such as rank
statistics, crosstabulations, survival data, standardized rates,
samplesize calculations, logistic regression, and metaanalysis.
Table of contents
Sections marked * contain material usually found only in postgraduate
courses
1 Introduction
1.1 Statistics and medicine
1.2 Statistics and mathematics
1.3 Statistics and computing
1.4 The scope of this book
2 The design of experiments
2.1 Comparing treatments
2.2 Random allocation
2.3 * Methods of allocation without random numbers
2.4 Volunteer bias
2.5 Intention to treat
2.6 Crossover designs
2.7 Selection of subjects for clinical trials
2.8 Response bias and placebos
2.9 Assessment bias and double blink studies
2.10 * Laboratory experiments
2.11 * Experimental units
2.12 * Consent in clinical trials
2M Multiple choice questions 1 to 6
2E Exercise: The ‘Know Your Midwife’ trial
3 Sampling and observational studies
3.1 Observational studies
3.2 Censuses
3.3 Sampling
3.4 Random sampling
3.5 Sampling in clinical and epidemiological studies
3.6 Crosssectional studies
3.7 Cohort studies
3.8 Case–control studies
3.9 * Questionnaire bias in observational studies
3.10 * Ecological studies
3M Multiple choice questions 7 to 13
3E Exercises: Campylobacter jejuni infection
4 Summarizing data
4.1 Types of data
4.2 Frequency distributions
4.3 Histograms and other frequency graphs
4.4 Shapes of frequency distribution
4.5 Medians and quantiles
4.6 The mean
4.7 Variance, range and interquartile range
4.8 Standard deviation
4A Appendix: The divisor for the variance
4B Appendix: Formulae for the sum of squares
4M Multiple choice questions 14 to 19
4E Exercise: Mean and standard deviation
5 Presenting data
5.1 Rates and proportions
5.2 Significant figures
5.3 Presenting tables
5.4 Pie charts
5.5 Bar charts
5.6 Scatter diagrams
5.7 Line graphs and time series
5.8 Misleading graphs
5.9 Logarithmic scales
5A Appendix: Logarithms
5M Multiple choice questions 20 to 24
5E Exercise: Creating graphs
6 Probability
6.1 Probability
6.2 Properties of probability
6.3 Probability distributions and random variables
6.4 The Binomial distribution
6.5 Mean and variance
6.6 Properties of means and variances
6.7 * The Poisson distribution
6.8 * Conditional probability
6A Appendix: Permutations and combinations
6B Appendix: Expected value of a sum of squares
6M Multiple choice questions 25 to 31
6E Exercise: Probability and the life table
7 The Normal distribution
7.1 Probability
7.2 The Normal distribution
7.3 Properties of the Normal distribution
7.4 Variables which follow a Normal distribution
7.5 The Normal plot
7A Appendix: Chisquares, t, and F
7M Multiple choice questions 32 to 37
7E Exercise: A Normal plot
8 Estimation
8.1 Sampling distributions
8.2 Standard error of a sample mean
8.3 Confidence intervals
8.4 Standard error and confidence interval for a proportion
8.5 The difference between two means
8.6 Comparison of two proportions
8.7 * Standard error of a sample standard deviation
8.8 * Confidence interval for a proportion when numbers are small
8.9 * Confidence interval for a median and other quantiles
8.10 What is the correct confidence interval?
8M Multiple choice questions 38 to 43
8E Exercise: Means of large samples
9 Significance tests
9.1 Testing a hypothesis
9.2 An example: The sign test
9.3 Principles of significance tests
9.4 Significance levels and types of error
9.5 One and twosided tests of significance
9.6 Significant, real and important
9.7 Comparing the means of large samples
9.8 Comparison of two proportions
9.9 * The power of a test
9.10 * Multiple significance tests
9.11 * Repeated significance tests and sequential analysis
9M Multiple choice questions 44 to 49
Exercise: Crohn's disease and cornflakes
10 Comparing the means of small samples
10.1 The t distribution
10.2 The onesample t method
10.3 The means of two independent samples
10.4 The use of transformations
10.5 Deviations from the assumptions of t methods
10.6 What is a large sample?
10.7 * Serial data
10.8 * Comparing two variances by the F test
10.9 * Comparing several means using analysis of variance
10.10 * Assumptions of the analysis of variance
10.11 * Comparison of means after analysis of variance
10.12 * Random effects in analysis of variance
10.13 * Units of analysis and clusterrandomized trials
10A Appendix: The ratio mean/standard error
10M Multiple choice questions 50 to 56
10E Exercise: The paired t method
11 Regression and correlation
11.1 Scatter diagrams
11.2 Regression
11.3 The method of least squares
11.4 * The regression of X and Y
11.5 The standard error of the regression coefficient
11.6 * Using the regression line for prediction
11.7 * Analysis of residuals
11.8 * Deviations from assumptions in regression
11.9 Correlation
11.10 Significance test and confidence interval for r
11.11 Uses of the correlation coefficient
11.12 * Using repeated observations
11.13 * Intraclass correlation
11A Appendix: The least squares estimates
11B Appendix: Variance about the regression line
11C Appendix: The standard error of b
11M Multiple choice questions 57 to 61
11E Exercise: Comparing two regression lines
12 Methods based on rank order
12.1 * Nonparametric methods
12.2 * The MannWhitney U test
12.3 * The Wilcoxon matched pairs test
12.4 * Spearman's rank correlation coefficient, rho
12.5 * Kendall's rank correlation coefficient, tau
12.6 * Continuity corrections
12.7 * Parametric or nonparametric methods?
12M * Multiple choice questions 62 to 66
12E * Exercise: Application of rank methods
13 The analysis of crosstabulations
13.1 The chisquared test for association
13.2 Tests for 2 by 2 tables
13.3 The chisquared test for small samples
13.4 Fisher's exact test
13.5 Yates' continuity correction for the 2 by 2 table
13.6 * The validity of Fisher's and Yates' methods
13.7 Odds and odds ratios
13.8 * The chisquared test for trend
13.9 * Methods for matched samples
13.10 * The chisquared goodness of fit test
13A Appendix: Why the chisquared test works
13B Appendix: The formula for Fisher's exact test
13C Appendix: Standard error for the log odds ratio
13M Multiple choice questions 67 to 73
13E Exercise: Admissions to hospital in a heatwave
14 Choosing the statistical method
14.1 * Method oriented and problem oriented teaching
14.2 * Types of data
14.3 * Comparing two groups
14.4 * One sample and paired samples
14.5 * Relationship between two variables
14M Multiple choice questions 74 to 80
14E * Exercises: Choosing a statistical method
15 Clinical measurement
15.1 Making measurements
15.2 * Repeatability and measurement error
15.3 * Comparing two methods of measurement
15.4 Sensitivity and specificity
15.5 Normal range or reference interval
15.6 * Survival data
15.7 * Computer aided diagnosis
15.8 * Number needed to treat
15M Multiple choice questions 81 to 86
15E Exercise: A reference interval
16 Mortality statistics and population structure
16.1 Mortality rates
16.2 Age standardization using the direct method
16.3 Age standardization by the indirect method
16.4 Demographic life tables
16.5 Vital statistics
16.6 The population pyramid
16M Multiple choice questions 87 to 92
16E Exercise: Deaths from volatile substance abuse
17 Multifactorial methods
17.1 * Multiple regression
17.2 * Significance tests and estimation in multiple regression
17.3 * Interaction in multiple regression
17.4 * Polynomial regression
17.5 * Assumptions of multiple regression
17.6 * Qualitative predictor variables
17.7 * Multiway analysis of variance
17.8 * Logistic regression
17.9 * Survival data using Cox regression
17.10 * Stepwise regression
17.11 * Metaanalysis: Data from several studies
17.12 * Other multifactorial methods
17M * Multiple choice questions 93 to 97
17E * Exercise: A multiple regression analysis
18 Determination of sample size
18.1 * Estimation of a population mean
18.2 * Estimation of a population proportion
18.3 * Sample size for significance tests
18.4 * Comparison of two means
18.5 * Comparison of two proportions
18.6 * Detecting a correlation
18.7 * Accuracy of the estimated sample size
18.8 * Trials randomized in clusters
18M * Multiple choice questions 98 to 100
18E * Exercise: Estimation of sample sizes
19 Solutions to exercises
References
Index