Meta analysis as a qualitative research design

1. dinesh.s

3.  Meta-analysis is a statistical technique for
amalgamating, summarizing, and reviewing previous
quantitative research.
 Selected parts of the reported results of primary
studies are entered into a database, and this "meta-
data" is "meta-analyzed", in similar ways to working
with other data - descriptively and then inferentially
to test certain hypotheses.

4.  Meta analysis can be used as a guide to answer
the question 'does what we are doing make a
difference to X?', even if 'X' has been measured
using different instruments across a range of
different people.
 Meta-analysis provides a systematic overview of
quantitative research which has examined a
particular question.

5.  Meta-analysis has been used to give helpful
insight into:
o the overall effectiveness of interventions (e.g.,
psychotherapy, outdoor education),
othe relative impact of independent variables
(e.g., the effect of different types of
therapy), and
othe strength of relationship between variables.

6.  Instatistics, a meta-analysis combines the results
of several studies that address a set of related
research hypotheses. This is normally done by
identification of a common measure of effect size,
which is modeled using a form of meta-
regression.

7. Why do a meta-analysis?

8.  we often have a lot of information, from many
studies, sometimes contradictory, and meta-analysis
offers us a tool to help us integrate this.
 A meta-analysis may increase statistical power,
resolve uncertainty, improve estimates of effect size,
and may in fact be able to address questions not
posed when the studies were designed.
 to understand both the statistical, substantive, and
methodological issues both in the original studies and
in the meta-analysis.

9. How is a
meta-analysis
done?

10. 1. Decide on the topic.
2. Decide on the hypothesis being tested.
3. Review the literature for all studies which test
that hypothesis. (computerized search of the
literature, careful study of the references in
articles, examination of papers, abstracts, and
presentations not published, and other sources
of unpublished). This needs to be done carefully
to minimize bias.

11. 4. Evaluate each study carefully.
5. Create a database containing the information
necessary for the analyses.
6. Perform the meta-analysis
7. Interpret the results.

12. When is a meta-analysis
appropriate?

13. A meta-analysis is appropriate :
 When researcher have multiple studies which test the
same or similar hypotheses
 When researcher have numerous contradictory
studies
 when trying to review a complex literature
 However, the studies involved need to contain
sufficient information for the meta-analysis to be
meaningful, and for the meta-analyst to evaluate the
assumptions properly.

14.  Imposes a discipline on the process of summing
up research findings.
 Represents findings in a more differentiated and
sophisticated manner than conventional reviews.
 Capable of finding relationships across studies
that are obscured in other approaches.
 Protects against over-interpreting differences
across studies.
 Can handle a large numbers of studies. (this
would overwhelm traditional approaches to
review)

15.  Requires a good deal of effort
 Mechanical aspects don’t lend
themselves to capturing more
qualitative distinctions between
studies
 “Apples and oranges”; comparability
of studies is often in the “eye of the
beholder”
 Most meta-analyses include
“blemished” studies

16.  Sources of bias are not controlled by the
method. Selection bias posses continual threat.
 Analysis of between study differences is
fundamentally correlational.
 Heavy reliance on published studies, which
may increase the effect as it is very hard to
publish studies that show no significant results.
This publication bias or "file-drawer effect"
(where non-significant studies end up in the
desk drawer instead of in the public domain)
should be seriously considered when
interpreting the outcomes of a meta-analysis.

17.  Meta-analysis adds together apples and
oranges. Overgeneralization can occur just as
easily
 Meta-analysis ignores qualitative differences
between studies
 Meta-analysis ignores study quality.
 Meta-analysis cannot draw valid conclusions
because only significant findings are
published.
 Meta-analysis is regarded as objective by its
proponents but really is subjective. Meta-
analysis relies on shared subjectivity rather
than objectivity.

18.  Meta analysis is a useful
methodology for making sense
out of conflicting research
studies.
 Make findings from individual
studies more applicable to
clinical practice.
 Evidence-based practice to
involve and integrate the best
available evidence from research
with clinical expertise and
patient values to achieve optimal
patient outcomes.