As a result, γ j, i − 1 ( K ) is an inverse Gamma random variable.
For continuous outcomes, weighted mean differences were calculated and an inverse variance random effects model was used.
We used standard inverse variance random effects meta-analyses to combine effect sizes across trials and calculated the variance estimate τ as a measure of heterogeneity.
We calculated pooled risk ratios by synthesising across the shift schedules used in individual studies; we used generic inverse variance random effects models with 95% confidence intervals.
28 We used a generic inverse variance random effects model to pool the standardised mean difference (SMD) between change in mental health in quitters and continuing smokers, from baseline to follow-up.
The forest plot of comparison for length of stay (fig 5) also showed no significant difference between the antibiotic treatment group and the appendicectomy group (mean difference (inverse variance, random) 0.34 (−0.19 to 0.87); I=48%, P=0.20).
Pooled effects were calculated using an inverse-variance random effect meta-analysis.
Each domain effect is assumed to be normally distributed, with mean zero and variance an inverse-gamma random variable.
For each binary effect measure, the meta-analysis was conducted including and excluding zero total event trials using the inverse variance random-effects model.
