[R-meta] Meta-analysis of single group attitude scores
lists at dewey.myzen.co.uk
Fri Nov 24 15:02:03 CET 2017
If you subtract the neutral point fr each study then this will only make
a difference if the studies have different neutral points but it would
not harm things anyway.
Dividing by the standard deviation seems unnecessary to me, and
potentially harmful. Why not use the standard error of each mean? Then
you would get the proper weights and an estimate of heterogeneity.
On 24/11/2017 12:26, Tommy van Steen wrote:
> Dear all,
> I have a question about my meta-analytic approach in a project that I’m working on.
> In this project, we are conducting a meta-analysis of attitudes. The study outcome variable is the mean attitude score on a scale (often a Likert-scale type survey or single item).
> I am trying to figure out what the best way is to conduct a meta-analysis based on this type of data as the data comes from single groups and studies vary in the number of answering possibilities on the Likert-scales.
> My thought would be to transform the study mean into a z-score by subtracting the neutral score (e.g. ‘3' in a 5-point scale study) from the study mean and divide the outcome by the standard deviation of the study mean. This way, the z-score reflects whether the attitude was positive (f the z-score is positive) or negative (if the z-score is negative), with 0 being neutral. I would then use this z-score as the effect size for my meta-analysis.
> Based on this, I have three questions:
> 1. Is this a sensible option?
> 2. If so, how should I calculate the study weights? (As z-scores typically have an SD of 1 if I understand correctly.)
> 3. How would I run the meta-analysis based on these z-scores? (Simply loading the scores as effect sizes in an SMD meta-analysis using the metafor-package seems odd perhaps?)
> Thank you very much for your time and thoughts.
> With kind regards,
> Tommy van Steen
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> R-sig-meta-analysis at r-project.org
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