An Introduction to Medical Statistics.
- 4th ed.
- 1 online resource (447 pages)
Cover -- Preface to the Fourth Edition -- Contents -- Detailed Contents -- Chapter 1 Introduction -- 1.1 Statistics and medicine -- 1.2 Statistics and mathematics -- 1.3 Statistics and computing -- 1.4 Assumptions and approximations -- 1.5 The scope of this book -- Chapter 2 The design of experiments -- 2.1 Comparing treatments -- 2.2 Random allocation -- 2.3 Stratification -- 2.4 Methods of allocation without random numbers -- 2.5 Volunteer bias -- 2.6 Intention to treat -- 2.7 Cross-over designs -- 2.8 Selection of subjects for clinical trials -- 2.9 Response bias and placebos -- 2.10 Assessment bias and double blind studies -- 2.11 Laboratory experiments -- 2.12 Experimental units and cluster randomized trials -- 2.13 Consent in clinical trials -- 2.14 Minimization -- 2.15 Multiple choice questions: Clinical trials -- 2.16 Exercise: The 'Know Your Midwife' trial -- Chapter 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 Cross-sectional studies -- 3.7 Cohort studies -- 3.8 Case-control studies -- 3.9 Questionnaire bias in observational studies -- 3.10 Ecological studies -- 3.11 Multiple choice questions: Observational studies -- 3.12 Exercise: Campylobacter jejuni infection -- Chapter 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 -- 4.9 Multiple choice questions: Summarizing data -- 4.10 Exercise: Student measurements and a graph of study numbers -- Appendix 4A: The divisor for the variance -- Appendix 4B: Formulae for the sum of squares -- Chapter 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 Using different colours -- 5.10 Logarithmic scales -- 5.11 Multiple choice questions: Data presentation -- 5.12 Exercise: Creating presentation graphs -- Appendix 5A: Logarithms -- Chapter 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 -- 6.9 Multiple choice questions: Probability -- 6.10 Exercise: Probability in court -- Appendix 6A: Permutations and combinations -- Appendix 6B: Expected value of a sum of squares -- Chapter 7 The Normal distribution -- 7.1 Probability for continuous variables -- 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 -- 7.6 Multiple choice questions: The Normal distribution -- 7.7 Exercise: Distribution of some measurements obtained by students -- Appendix 7A: Chi-squared, t, and F -- Chapter 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 Number needed to treat -- 8.8 Standard error of a sample standard deviation -- 8.9 Confidence interval for a proportion when numbers are small -- 8.10 Confidence interval for a median and other quantiles -- 8.11 Bootstrap or resampling methods -- 8.12 What is the correct confidence interval? -- 8.13 Multiple choice questions: Confidence intervals. 8.14 Exercise: Confidence intervals in two acupuncture studies -- Appendix 8A: Standard error of a mean -- Chapter 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 two sided 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 -- 9.12 Significance tests and confidence intervals -- 9.13 Multiple choice questions: Significance tests -- 9.14 Exercise: Crohn's disease and cornflakes -- Chapter 10 Comparing the means of small samples -- 10.1 The t distribution -- 10.2 The one sample 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 cluster randomized trials -- 10.14 Multiple choice questions: Comparisons of means -- 10.15 Exercise: Some analyses comparing means -- Appendix 10A: The ratio mean/standard error -- Chapter 11 Regression and correlation -- 11.1 Scatter diagrams -- 11.2 Regression -- 11.3 The method of least squares -- 11.4 The regression of X on 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 -- 11.14 Multiple choice questions: Regression and correlation -- 11.15 Exercise: Serum potassium and ambient temperature -- Appendix 11A: The least squares estimates -- Appendix 11B: Variance about the regression line -- Appendix 11C: The standard error of b -- Chapter 12 Methods based on rank order -- 12.1 Non-parametric methods -- 12.2 The Mann-Whitney U test -- 12.3 The Wilcoxon matched pairs test -- 12.4 Spearman's rank correlation coefficient, ρ -- 12.5 Kendall's rank correlation coefficient, τ -- 12.6 Continuity corrections -- 12.7 Parametric or non-parametric methods? -- 12.8 Multiple choice questions: Rank-based methods -- 12.9 Exercise: Some applications of rank-based methods -- Chapter 13 The analysis of cross-tabulations -- 13.1 The chi-squared test for association -- 13.2 Tests for 2 by 2 tables -- 13.3 The chi-squared 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 chi-squared test for trend -- 13.9 Methods for matched samples -- 13.10 The chi-squared goodness of fit test -- 13.11 Multiple choice questions: Categorical data -- 13.12 Exercise: Some analyses of categorical data -- Appendix 13A: Why the chi-squared test works -- Appendix 13B: The formula for Fisher's exact test -- Appendix 13C: Standard error for the log odds ratio -- Chapter 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 -- 14.6 Multiple choice questions: Choice of statistical method. 14.7 Exercise: Choosing a statistical method -- Chapter 15 Multifactorial methods -- 15.1 Multiple regression -- 15.2 Significance tests and estimation in multiple regression -- 15.3 Using multiple regression for adjustment -- 15.4 Transformations in multiple regression -- 15.5 Interaction in multiple regression -- 15.6 Polynomial regression -- 15.7 Assumptions of multiple regression -- 15.8 Qualitative predictor variables -- 15.9 Multi-way analysis of variance -- 15.10 Logistic regression -- 15.11 Stepwise regression -- 15.12 Seasonal effects -- 15.13 Dealing with counts: Poisson regression and negative binomial regression -- 15.14 Other regression methods -- 15.15 Data where observations are not independent -- 15.16 Multiple choice questions: Multifactorial methods -- 15.17 Exercise: A multiple regression analysis -- Chapter 16 Time to event data -- 16.1 Time to event data -- 16.2 Kaplan-Meier survival curves -- 16.3 The logrank test -- 16.4 The hazard ratio -- 16.5 Cox regression -- 16.6 Multiple choice questions: Time to event data -- 16.7 Exercise: Survival after retirement -- Chapter 17 Meta-analysis -- 17.1 What is a meta-analysis? -- 17.2 The forest plot -- 17.3 Getting a pooled estimate -- 17.4 Heterogeneity -- 17.5 Measuring heterogeneity -- 17.6 Investigating sources of heterogeneity -- 17.7 Random effects models -- 17.8 Continuous outcome variables -- 17.9 Dichotomous outcome variables -- 17.10 Time to event outcome variables -- 17.11 Individual participant data meta-analysis -- 17.12 Publication bias -- 17.13 Network meta-analysis -- 17.14 Multiple choice questions: Meta-analysis -- 17.15 Exercise: Dietary sugars and body weight -- Chapter 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.
An Introduction to Medical Statistics, fourth edition, is a 'must-have' textbook. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the common statistical methods seen in published research and guidelines, as well as how to interpret and analyse statistics for clinical practice.