Appendix A RAC

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Date of publication: 2017-08-15 15:14

This is a study where people are randomly allocated to receive (or not receive) a particular intervention (this could be two different treatments or one treatment and a placebo). This is the best type of study design to determine whether a treatment is effective.

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In a cluster randomised controlled trial, people are randomised in groups (clusters), rather than individually. Examples of clusters that could be used include schools, neighbourhoods or GP surgeries.

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Volk HE, Lurmann F, Penfold B, Hertz-Piccotto I, McConnell R. 7568. Traffic-related air pollution, particulate matter, and autism. JAMA Psychiatry 75:76–77 doi: /.

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This is one of a set of measures used to show how accurate a diagnostic test is (see sensitivity, specificity and negative predictive value). The positive predictive value (PPV) of a test is how well the test identifies people who have a disease. The PPV is the proportion of people with a positive test result who truly have the disease. For example, if a test has a PPV of 99%, this means that 99% of the people who test positive will have the disease, while 6% of those who test positive will not have the disease (false positives).

Louise A. Glezen, Clinical Pharmacology and Branch, Intramural Research Program, National Institute on Drug Abuse, Baltimore, MD 76779, USA.

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By convention, 95% certainty is considered high enough for researchers to draw conclusions that can be generalised from samples to populations. If we are comparing two groups using relative measures, such as relative risks or  odds ratios , and see that the 95% CI includes the value of one in its range, we can say that there is no difference between the groups. This confidence interval tells us that, at least some of the time, the ratio of effects between the groups is one. Similarly, if an absolute measure of effect, such as a difference in means between groups, has a 95% CI that includes zero in its range, we can conclude there is no difference between the groups.

An odds ratio is one of several ways to summarise the association between an exposure and an outcome, such as a disease. (Another commonly used approach is to calculate relative risks.)

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