A table with the hyperparameters of the predictive distributions for the between-study variance developed by Turner et al. (2015) and Rhodes et al. (2015): log-normal distribution and t-distribution (with 5 degrees of freedom) when the outcome data are analysed in the odds ratio or standardised mean difference scale, respectively.
table_tau2_prior(measure, area)A cross-sectional table as a heatmap showing the hyperparameters (mean and standard deviation) of the corresponding predictive distribution for all combinations between the outcome types and treatment-comparison types and according to the selected medical area (only relevant with standardised mean difference) as defined by Turner et al. (2015) and Rhodes et al. (2015). The tiles are coloured with different shades according to the corresponding median value: the larger the median, the darker the colour.
Character string indicating the effect measure with possible
values "OR" for odds ratio and "SMD" for standardised mean
difference.
Character string indicating the medical area relating to the
predictive distributions for standardised mean difference with possible
values "cancer" for medical areas of cancer, "respiratory"
for medical areas of respiratory diseases, and "other" for medical
areas other than cancer or respiratory diseases. The argument is not
relevant for odds ratio.
Loukia M. Spineli
This table aids in selecting the hyperparameters for the function
heterogeneity_param_prior when considering an informative prior
distribution for the between-study variance parameter based on the two
publications mentioned above (relevant for the function
run_model to conduct random-effects network meta-analysis).
Rhodes KM, Turner RM, Higgins JP. Predictive distributions were developed for the extent of heterogeneity in meta-analyses of continuous outcome data. J Clin Epidemiol 2015;68(1):52--60. doi: 10.1016/j.jclinepi.2014.08.012
Turner RM, Jackson D, Wei Y, Thompson SG, Higgins JP. Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis. Stat Med 2015;34(6):984--98. doi: 10.1002/sim.6381
heterogeneity_param_prior, run_model