Meta-analysis: Meaning and Key Concepts
Gene Glass coined the term meta-analysis to describe an empirically-based research
method, which synthesizes research findings from numerous empirical studies. In short,
a meta-analysis is a synthesis of results of many researchers about the field or topic of
interest.
Meta-analysis had its beginning in the social science literature, but its applicability
extends to behavioral and physical sciences research and to any discipline where
individual study findings are too meager to test a theory. Meta-analysis can address
policy issues. It has also been a popular research methodology.
Meta-analysis is related to the review of related literature presented in research
reports. What makes it different from an ordinary literature review is that it is more
rigorous and exhaustive and requires the original empirical data or summaries, such as
means, standard deviations, and correlation co-efficient.
While a literature review simply reports the results of a study as significant or not, meta-
analysis requires statistical analysis of original data from the studies being integrated.
The real strength of meta-analysis lies in its ability to relate conditions that vary across
studies to outcomes. For example, Gene Glass and Mary Smith made a meta-analysis of
375 psychotherapy outcome studies and calculated 833 effects. They found a mean
effect size of 68 which indicates that the average treated group was two-thirds of a
standard deviation better than its control group. Furthermore, 88% of the effects were
positive, showing that most treatment groups exceeded their respective control groups
on all kinds of outcomes.
Quantitative Methods and Meta-analysis
Quantitative meta-analysis employs quantitative methodology similar to that used in
the primary researches that are being integrated. Statistical significance and estimation
of effect size provide summaries of study in quantitative integrated reviews. As pointed
by R. Rosenthal, the general relationship between tests of significance and effect size is
given by the relation: Test statistics is a product of size of effect and sample size.
Effect is determined by dividing the control and experimental group difference by the
standard deviation of the control group (the standard deviation being presumed to have
been unaffected by treatment). The result is similar to a Z score. This results in
standardized measures of effect for comparability of results across studies. The
Gene Glass coined the term meta-analysis to describe an empirically-based research
method, which synthesizes research findings from numerous empirical studies. In short,
a meta-analysis is a synthesis of results of many researchers about the field or topic of
interest.
Meta-analysis had its beginning in the social science literature, but its applicability
extends to behavioral and physical sciences research and to any discipline where
individual study findings are too meager to test a theory. Meta-analysis can address
policy issues. It has also been a popular research methodology.
Meta-analysis is related to the review of related literature presented in research
reports. What makes it different from an ordinary literature review is that it is more
rigorous and exhaustive and requires the original empirical data or summaries, such as
means, standard deviations, and correlation co-efficient.
While a literature review simply reports the results of a study as significant or not, meta-
analysis requires statistical analysis of original data from the studies being integrated.
The real strength of meta-analysis lies in its ability to relate conditions that vary across
studies to outcomes. For example, Gene Glass and Mary Smith made a meta-analysis of
375 psychotherapy outcome studies and calculated 833 effects. They found a mean
effect size of 68 which indicates that the average treated group was two-thirds of a
standard deviation better than its control group. Furthermore, 88% of the effects were
positive, showing that most treatment groups exceeded their respective control groups
on all kinds of outcomes.
Quantitative Methods and Meta-analysis
Quantitative meta-analysis employs quantitative methodology similar to that used in
the primary researches that are being integrated. Statistical significance and estimation
of effect size provide summaries of study in quantitative integrated reviews. As pointed
by R. Rosenthal, the general relationship between tests of significance and effect size is
given by the relation: Test statistics is a product of size of effect and sample size.
Effect is determined by dividing the control and experimental group difference by the
standard deviation of the control group (the standard deviation being presumed to have
been unaffected by treatment). The result is similar to a Z score. This results in
standardized measures of effect for comparability of results across studies. The
