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I am trying to generate subgroup forest plots for proportion and mean meta-analysis using the 'subgroup' argument in metaprop and metamean functions. The forest plot for the metaprop works very well but I keep getting the error below when I use the 'forest' argument with metamean:
Error in x$labels[[i]] : subscript out of bounds
The argument passed to 'forest' is below:
Number of studies combined: k = 10
Number of observations: o = 4910
Results for subgroups (random effects model):
k mean 95%-CI
Population = European 2 1.0373 [ 0.7738; 1.3008]
Population = Chinese 3 2.3380 [ 1.1179; 3.5581]
Population = Middle East 1 2.7700 [ 2.6262; 2.9138]
Population = Indian 2 2.3655 [-0.1727; 4.9036]
Population = South and North American 2 2.0990 [ 0.0606; 4.1374]
tau^2 tau Q I^2
Population = European 0.0324 0.1800 9.00 88.9%
Population = Chinese 1.1524 1.0735 245.20 99.2%
Population = Middle East -- -- 0.00 --
Population = Indian 3.3426 1.8283 293.42 99.7%
Population = South and North American 2.1598 1.4696 641.59 99.8%
Test for subgroup differences (random effects model):
Q d.f. p-value
Between groups 128.06 4 < 0.0001
Details on meta-analytical method:
Inverse variance method
Restricted maximum-likelihood estimator for tau^2
Q-profile method for confidence interval of tau^2 and tau
Untransformed (raw) means
#subgroup_population_ALL
k=metamean(subgroup = Population, n=N, mean=mean, sd = sd, data = met_all, studlab = SN, fixed=FALSE)
forest(k)
Error in x$labels[[i]] : subscript out of bounds
Any help will be appreciated.
John
The text was updated successfully, but these errors were encountered:
Hi,
I am trying to generate subgroup forest plots for proportion and mean meta-analysis using the 'subgroup' argument in metaprop and metamean functions. The forest plot for the metaprop works very well but I keep getting the error below when I use the 'forest' argument with metamean:
Error in x$labels[[i]] : subscript out of bounds
The argument passed to 'forest' is below:
Number of studies combined: k = 10
Number of observations: o = 4910
Random effects model 2.0754 [1.3918; 2.7590]
Quantifying heterogeneity:
tau^2 = 1.2092 [0.5682; 4.0494]; tau = 1.0996 [0.7538; 2.0123]
I^2 = 99.7% [99.7%; 99.8%]; H = 18.92 [17.54; 20.41]
Test of heterogeneity:
Q d.f. p-value
3222.66 9 0
Results for subgroups (random effects model):
k mean 95%-CI
Population = European 2 1.0373 [ 0.7738; 1.3008]
Population = Chinese 3 2.3380 [ 1.1179; 3.5581]
Population = Middle East 1 2.7700 [ 2.6262; 2.9138]
Population = Indian 2 2.3655 [-0.1727; 4.9036]
Population = South and North American 2 2.0990 [ 0.0606; 4.1374]
tau^2 tau Q I^2
Population = European 0.0324 0.1800 9.00 88.9%
Population = Chinese 1.1524 1.0735 245.20 99.2%
Population = Middle East -- -- 0.00 --
Population = Indian 3.3426 1.8283 293.42 99.7%
Population = South and North American 2.1598 1.4696 641.59 99.8%
Test for subgroup differences (random effects model):
Q d.f. p-value
Between groups 128.06 4 < 0.0001
Details on meta-analytical method:
Any help will be appreciated.
John
The text was updated successfully, but these errors were encountered: