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Click to enlarge See the back cover 
An Introduction to Medical Statistics, Third Edition 

$52.00 each 




Comment from the Stata technical groupAn 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 contentsView 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

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