Methodological complexity in the use of meta-analysis for empirical environmental case studies

The primary aim of meta‐analysis is to carry out a synthesis of results obtained by different single studies on common problems. It is, therefore, characterized by a high level of transversality, both horizontally (identification, selection and analysis of the case studies under consideration) and vertically (identification and description of the problem to be studied, definition of the objectives of the study, and operative use of the results obtained). This instrument of analysis, while undoubtedly of great interest and potential, is, however characterized by a considerable methodological complexity, especially when the studies carried out are in the field of the non‐experimental social sciences, and in particular of environmental sciences. Defines six different levels of analysis with reference to a meta‐analytical approach in general, and identifies the most important and characteristic methodological problems for each of these. Also offers a more plausible and appealing way of tackling these problems with particular reference to the field of environmental economics.

[1]  J. R. Ravetz,et al.  Qualified Quantities: Towards an Arithmetic of Real Experience , 1987 .

[2]  K. Wachter,et al.  Disturbed by meta-analysis? , 1988, Science.

[3]  Z. Pawlak,et al.  Decision analysis using rough sets , 1994 .

[4]  Wilfried R. Vanhonacker,et al.  Using Meta-Analysis Results in Bayesian Updating: The Empty-Cell Problem , 1992 .

[5]  A. Woodside,et al.  A meta-analysis of effect sizes based on direct marketing campaigns , 1993 .

[6]  Deniz S. Ones,et al.  PERSONALITY AND JOB PERFORMANCE: A CRITIQUE OF THE TETT, JACKSON, AND ROTHSTEIN (1991) META-ANALYSIS , 1994 .

[7]  Hugh J. Miser,et al.  A foundational concept of science appropriate for validation in operational research , 1993 .

[8]  Meni Koslowsky,et al.  On the efficacy of credibility intervals as indicators of moderator effects in meta-analytic research , 1993 .

[9]  Po L. Yu,et al.  Forming Winning Strategies , 1990 .

[10]  L. Witt,et al.  Gender and the relationship between perceived fairness of pay or promotion and job satisfaction. , 1992, The Journal of applied psychology.

[11]  J. Ravetz Scientific Knowledge and Its Social Problems , 2020 .

[12]  L. Hedges,et al.  Statistical Methods for Meta-Analysis , 1987 .

[13]  J. Kemeny A Philosopher Looks At Science , 1960 .

[14]  Jerzy W. Grzymala-Busse,et al.  Rough Sets , 1995, Commun. ACM.

[15]  Z. Pawlak Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[16]  Jerome R. Ravetz,et al.  Uncertainty and Quality in Science for Policy , 1990 .