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    I have a couple of data interpretation questions for my degree and I have no idea how to approach them. I have tried having a go at them but I really don't understand what to do.

    Any help would be much appreciated! x
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  1. File Type: pdf Data Interpretation practice 1.03 1.05.pdf (238.4 KB, 139 views)

    I'll attempt to answer this question step-wise:

    1. Effect size is essentially a quantitative measure of the strength of an effect. This idea can be understood by considering effect size in terms of a standardised difference - this is the mean difference between groups in standard score form (Glass, 1976). In order to understand the role of effect size in meta-analyses, we must first understand what is meant by a "meta-analysis". Meta-analyses are essentially the study of a large volume of already published studies on a given subject. With this in mind, the standard error of effect size can be used to weight effect sizes when combining studies; in essence, large studies are considered more important than smaller studies.

    2. Defining the acceptance criteria (incorporation, inclusion or exclusion) in meta-analyses is important when enabling the interpreter of the meta-analysis to understand components of the study itself, these may include subject number (n), male:female ratio, methods used, characteristics sought after, and characteristics excluded. This information can then be utilised when considering the results of the meta-analyses. For instance, the results of a meta-analysis may find the administration of drug X to be effective in reducing cardiovascular disease in a subset of 50,000 subjects. However, this meta-analysis may state exclusion criteria that excluded female subjects, and so this result cannot be extrapolated to the female population.

    3. DE

    4. BMI decrease stated in Table 3 is based on a very small cohort.
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