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trialrun2.csv [6] | 6.93 KB |

Dear Sir,

I am in the midst of running the multivariate meta-analysis with moderators included. The attached dataset consists of 63 observations, 6 effect sizes and their respective variances and covariances. There are many missing data as most studies do not report all the 6 effect sizes, in fact there is not one study that reported all the 6 effect sizes. I am able to run the random effects multivariate meta-analysis by imposing a diagonal structure on T2 but when I tried running an analysis with P.f as one of the moderators (there are no missing data on this variable-all studies have reported the P.f), the following error occurred:

Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) :

0 (non-NA) cases

However, when I ran the multivariate meta-analysis with just the first 3 effect sizes, and the moderator included, the error does not appear. What is exactly causing the error to appear? Is the main problem problem due to the vast number of missing data in the dataset? Is there any other way to solve this issue aside from dropping the number of effect sizes included (which then reduces the number of missing data)?

The following is my syntax,

> m1 <- read.csv(“trialrun2.csv”)

> RE <- Diag(c("0.01*Tau2_1", "0.01*Tau2_2", "0.01*Tau2_3", "0.01*Tau2_4", "0.01*Tau2_5", "0.01*Tau2_6"))

m2 <- meta(y=cbind(z_d, z_a, z_s, z_o, z_f, z_w), v=cbind(Var_d, cov.d.a, cov.d.s, cov.d.o, cov.d.f, cov.d.w, Var_a, cov.a.s, cov.a.o, cov.a.f, cov.a.w, Var_s, cov.s.o, cov.s.f, cov.s.w, Var_o, cov.o.f, cov.o.w, Var_f, cov.f.w, Var_w), x = P.f, data=m1, RE.constraints=RE)

Any help will be appreciated! Thank so much.

Yours sincerely,

GerardCY