David J. Torgerson;Carole J. Torgerson's Designing Randomised Trials in Health, Education and the PDF

By David J. Torgerson;Carole J. Torgerson

Coverage makers are more and more tough proof from randomized trials. The booklet makes a speciality of the layout of rigorous trials instead of their statistical underpinnings or analyses. as a result, statistical conception is absent and statistical equipment are minimum. Few different texts cross into such distinctive description approximately randomization strategies and diversified trial designs in the similar quantity. The e-book has chapters on: pragmatic designs; placebo designs; choice techniques; unequal allocation; economics; analytical ways; randomization tools.

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Extra resources for Designing Randomised Trials in Health, Education and the Social Sciences: An Introduction

Sample text

2 Non-randomised controlled trials and selection bias Control groups must be formed through a process of random allocation, or a similar method, in order to eliminate selection bias. Selection bias occurs when the intervention/treatment group has an imbalance in a variable that is associated with outcome compared with the control group. For example, early non-randomised evaluations of computer technology in schools compared technology resource-rich schools with technology resource-poor schools (Torgerson and Elbourne, 2002).

One quite widely used method involves the use of an identification number. We might for instance allocate people on the basis of their hospital number or their social security/national insurance number: odd numbers might form one group and even numbers the other. The major problem with this approach is that it invites subversion, or sabotage, of the allocation process. Because we know that odd numbers will receive a given intervention we can, if so minded, withhold the intervention to selected participants.

The corresponding plot of these marks shows a classic symptom of regression towards the mean, where there is a correlation between the difference in pre- and post-test scores (in this instance first and second markers) and pre-test scores. Regression to the mean will confound any education, health or public policy strategy based on selecting groups of people or hospitals, prisons or schools that have performed particularly badly or well on a measure. Regression to the mean will explain why so many ‘action research’ or ‘clinical audit’ projects appear to be successful.

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