these texts are now available as e‐books, usually at a substantially reduced price compared with the hard copy.
TABLE 1.4 Impact of Screening for Breast Cancer on 5‐year Mortality in 62 000 Women
| Cause of Death | |||||
| Breast Cancer | All Other Causes | ||||
| n | n | Rate/1 000 | n | Rate/1 000 | |
| Screening group | |||||
| Examined | 20 200 | 23 | 1.1 | 428 | 21 |
| Refused | 10 800 | 16 | 1.5 | 409 | 38 |
| Total | 31 000 | 39 | 1.3 | 837 | 27 |
| Control group | 31 000 | 63 | 2.0 | 879 | 28 |
* Armitage P, Berry G, Mathews JNS. Statistical Methods in Medical Research. 4th edition. Blackwell Science. Oxford. 2001. Very thorough and wide‐ranging, with excellent explanations of the mathematics behind the statistics. Highly recommended.
* Bland M. An Introduction to Medical Statistics. 4th edition. Oxford University Press. 2015. Good, basic introduction, wide ranging, with lots of useful examples including SPSS. Might be a bit difficult for beginners, as he tends to jump straight in without too much underlying explanation.
* Bowling Ann. Research Methods in Health. 4th edition. Open University Press. Buckingham. 2014. This text provides an excellent overview of issues in both quantitative and qualitative research. Together with Ann Bowling's other text (‘Measuring Health’, 4th edition, McGraw Hill Education, 2017), it provides a practical and straightforward guide to research design for the health sciences.
Campbell MJ, Machin D, Walters SJ. Medical Statistics: A Textbook for the Health Sciences (Medical Statistics). 4th edition. Wiley‐Blackwell. Chichester. 2007. A comprehensive text, the book has lots of ‘common sense’ tips and useful comments sprinkled liberally throughout.
* Campbell MJ. Statistics at Square One. 11th edition. BMJ Books. 2009. Useful little ‘cookbook’, good for quick reference to remind you of the underlying statistical formulae, but not very good about explaining the principles underlying the tests or why they work as they do.
Campbell MJ. Statistics at Square Two. 2nd edition. BMJ Books. 2006. This is a useful follow‐on to Statistics at Square One. It explores more complex statistical analyses involving multiple variables and complex study designs.
Freedman D, Pisani R, Purves R. Statistics. 4th edition. Norton. London. 2014. Basic and very readable text. May at times seem long‐winded, but lots of detailed examples and useful exercises (with answers).
Glantz SA. Primer of Biostatistics. 7th edition. McGraw‐Hill. London. 2012. First rate text, very clear descriptions of tests with medical examples and problems for solving.
Corder GW, Forman DI. Nonparametric Statistics: A Step‐by‐Step Approach. 2nd edition. Wiley. 2014. Very good at explaining the fundamentals of nonparametric statistics.
* Juster, Norton. The Phantom Tollbooth. Harper Collins. New York. 2008. Illustrations by Jules Feiffer. A wonderful allegory of scientific thinking concerning two kidnapped Princesses: Rhyme and Reason. The illustrations by Jules Feiffer perfectly complement Milo’s struggle to make sense of the world. The ideal fantasy for when you're fed up with statistics.
Mead R, Curnow RN and Hasted A (editor). Statistical Methods in Agriculture and Experimental Biology. 3rd edition. Chapman and Hall CRC Press. London. 2002. The authors worked in the Applied Statistics Department of the Food Research Institute at Reading, so the examples are geared towards food science.
Moser CA and Kalton G. Survey Methods in Social Investigation. 2nd edition. Heinemann Educational. London. 1985. Detailed and practical advice on survey techniques and design. Nonmathematical. A classic.
* Norman GR and Streiner DL. Biostatistics: the Bare Essentials. 4th edition. People’s Medical Publishing House. USA. 2014. Clear, funny, and irreverent. Goes into the lower reaches of the upper echelons of statistics (i.e. covers the basics plus some of the more advanced stuff).
* Riegelman R. Studying a Study and Testing a Test: How to Read the Medical Evidence. 5th edition. Lippincott Williams and Wilkins. 2004. Good for interpreting the medical literature.
1.9 EXERCISES
Answers to these exercises can be found in Part 4, at the end of the chapters.
1 1.9.1 Rounding and significant digitsRound the following numbers to two decimal places. Use the rules plus common sense.12.2345144.567373.66513.665299.4545Round the same numbers to three significant digits.
2 1.9.2 Interpreting data: does screening save lives?62 000 women in a health insurance scheme were randomly allocated to either a screening programme for breast cancer, or no screening. After 5 years, the following results were observed (Table 1.4):Does screening save lives? Which numbers tell you so?Among the women in the screening group, the death rate from all other causes in the ‘Refused’ group was almost twice that in the ‘Examined’ group. Did screening cut the death rate in half? Explain briefly.Was the study blind?
3 1.9.3 Hypothesis and null hypothesisIn a study designed to assess whether undernutrition is a cause of short stature in poor inner‐city children:State the hypothesis (H1)State the null hypothesis (H0)Consider:confounding factorssources of systematic biasConsider ways to minimize the effects of confounding and systematic bias
REFERENCES
1 1. Popper Karl R. Conjectures and Refutations. The Growth of Scientific Knowledge. 5th edition. Routledge. London. 2002.
2 2. Fisher RA. Design of Experiments. 7th edition. Oliver and Boyd. London. 1960.
3 3. Juster Norton. The Phantom Tollbooth. Random House. New York. 2000.
4 4. Bradford Hill A. The environment and disease: association or causation? Proc R Soc Med. 1965 May; 58(5): 295–300.
5 5.
