作者: Marc J. Lajeunesse , Mark R. Forbes
DOI: 10.1046/J.1461-0248.2003.00448.X
关键词: High ability 、 Item response theory 、 Publication bias 、 Ecology 、 Type I and type II errors 、 Representation (mathematics) 、 Statistics 、 Mathematics 、 Monte Carlo method 、 Null (SQL) 、 Variable (computer science)
摘要: Variable reporting of results can influence quantitative reviews by limiting the number studies for analysis, and thereby influencing both type analysis scope review. We performed a Monte Carlo simulation to determine statistical errors three meta-analytical approaches related how such were affected numbers constituent studies. Hedges d effect sizes based on item response theory (IRT) had similarly improved error rates with increasing when there was no true effect, but IRT conservative effect. Log ratio low precision detecting null effects as result overestimation sizes, high ability detect effects, largely irrespective Traditional meta-analysis are preferred; however, should use various methods in concert improve representation inferences from summaries published data.