Meta-analysis is a set of statistical procedures designed to accumulate
experimental and correlational results across independent studies that
address a related set of research questions. Unlike traditional research
methods, meta-analysis uses the summary statistics from individual
studies as the data points. A key assumption of this analysis is that
each study provides a differing estimate of the underlying relationship
within the population (rho). By accumulating results across studies, one
can gain a more accurate representation of the population relationship
than is provided by the individual study estimators.

There are a variety of different procedures for conducting a
meta-analysis involving the accumulation of individual study statistics
and converting them to correlations (r), standardized differences between
mean scores (d), p values, or Z-scores (Glass, 1976, 1977; Hunter et
al.,1982; Hunter and Schmidt, 1990; Rosenthal, 1991; Smith and Glass,
1977; Smith, Glass and Miller, 1980; Wolf, 1986).

Schmidt, Hunter, and their colleagues (Schmidt and Hunter, 1977; Hunter,
et. al., 1982; Hunter and Schmidt, 1990) developed one method of
meta-analysis that does not rely on the combination of Z-scores or
probability values as the common metric. This procedure uses either r or
d as the combinatorial statistic. It progressively corrects the mean r or
d and their obtained variances for sampling error and then measurement
error and range restriction.

The following references may be helpful:

Cohen, J. (1988). Statistical power analysis for the behavioral sciences.
(2nd Ed). Hillsdale, NJ: Lawrence Erlbaum Associates.
Glass, G. (1976). Primary, secondary and meta-analysis of research.
Educational Researcher, 5, 3-8.
Glass, G. (1977). Integrating findings: The meta-analysis of research.
Review of Research in Education, 5, 351-379.
Huffcutt A., Arthur, W., and Bennett W. (1993). Conducting meta-analysis
using the PROC MEANS procedure in SAS. Educational and Psychological
Measurement, 53, 119-131.
Hunter, J. and Schmidt, F. (1990). Methods of meta-analysis: Correcting
error and bias in research findings. Beverly Hills CA: Sage.
Hunter, J., Schmidt, F., and Jackson, G. (1982). Meta-Analysis:
Cumulating research findings across studies. Beverly Hills CA: Sage.
McDaniel, M. (1986). Computer programs for calculating meta-analysis
statistics. Educational and Psychological Measurement, 46, 175-177.
Mullen, B. and Rosenthal R. (1986). BASIC meta-analysis: Procedures and
programs. Hillsdale, NJ: Lawrence Erlbaum Associates.
Mullen, B. (1990). Advanced BASIC meta-analysis. Hillsdale, NJ: Lawrence
Erlbaum
Associates.
Rosenthal, R. (1991a). Meta-analytic procedures for social research (rev
ed). Beverly Hills CA: Sage.
Rosenthal R. (1991b) Meta-analysis: A review. Psychosomatic Medicine, 53,
247-271.
Schmidt, F. L. and Hunter, J. E. (1977). Development of a general
solution to the problem of validity generalization. Journal of Applied
Psychology, 62, 529-540.
Smith, M., and Glass, G. (1977). Meta-analysis of psychotherapy outcome
studies. American Psychologist, 32,752-760.
Smith, M. Glass, G. and Miller, T. (1980). The benefits of psychotherapy.
Baltimore: The Johns Hopkins University Press.
Wolf, F. (1986). Meta-Analysis: Quantitative methods for research
synthesis. Beverly Hills, CA: Sage.

I did not include material by Olkin and Hedges etc (mainly because I have
not got around to reading them), but otherwise this covers a fair amount
of the field. Also if you have access to a Mac, I've developed a
hypercard based meta-analysis program that may be useful. If you are
interested, it is available at ftp.stolaf.edu in directory /pub/macpsych.
the file is called MetaAnalysis_Stack.sea.hqx.

Regards,

Larry C. Lyons                       | Dept of Psychology
email: Solo...@vt.edu                | Virginia Tech,
                                     | Blacksburg, VA 24061 - 0436
Tel: (703) 231 - 6581                | Fax: (703) 231 - 3652