Abstract
BACKGROUND: For outcomes that studies report as the means in the treatment and control groups, some medical applications and nearly half of metaanalyses in ecology express the effect as the ratio of means (RoM), also called the response ratio (RR), analyzed in the logarithmic scale as the logresponseratio, LRR.
METHODS: In randomeffects metaanalysis of LRR, with normal and lognormal data, we studied the performance of estimators of the betweenstudy variance, τ2, (measured by bias and coverage) in assessing heterogeneity of studylevel effects, and also the performance of related estimators of the overall effect in the log scale, λ. We obtained additional empirical evidence from two examples.
RESULTS: The results of our extensive simulations showed several challenges in using LRR as an effect measure. Point estimators of τ2 had considerable bias or were unreliable, and interval estimators of τ2 seldom had the intended 95% coverage for small to moderatesized samples (n<40). Results for estimating λ differed between lognormal and normal data.
CONCLUSIONS: For lognormal data, we can recommend only SSW, a weighted average in which a study's weight is proportional to its effective sample size, (when n≥40) and its companion interval (when n≥10). Normal data posed greater challenges. When the means were far enough from 0 (more than one standard deviation, 4 in our simulations), SSW was practically unbiased, and its companion interval was the only option.
Original language  English 

Article number  263 
Journal  BMC Medical Research Methodology 
Volume  20 
Issue number  1 
DOIs  
Publication status  Published  22 Oct 2020 
Keywords
 Betweenstudy variance
 Heterogeneity
 Logresponseratio
 Metaanalysis
 Randomeffects model
 Ratio of means
Profiles

Elena Kulinskaya
 School of Computing Sciences  Emeritus Professor
 Norwich Epidemiology Centre  Member
 Data Science and AI  Member
Person: Honorary, Research Group Member