Dear researchers, I am trying to conduct a meta-analysis with two-stage structural equation modeling (TSSEM) using R, the model I want to estimate has four independent variables (X1, X2 and two control variables C1, C2), one mediation variable (M), and two dependent variables (Y1, Y2). However, in the output result of the second stage of random-effect model, two estimates of the upbound of 95%CI are missing (please see the picture attached to this question), I wonder what caused it and how to fix it. I would be very grateful if you could offer help!

Here are some problems I encountered during the research process that I thought might be related to this issue:

1. Some of the relationships (e.g. correlation X1-X2, C1-X1) are only reported in 3 or 4 primary studies, and heterogeneity is high. Only one primary study reported correlation C1-M.

2. The first stage of random-effect model did not converge, and rerun didn't find a solution. Here's the warning message:

Warning message: In print.summary.meta(x) : OpenMx status1 is neither 0 or 1. You are advised to 'rerun' it again. > stage1random vcov(stage1random)

Warning message: In .solve(x = object$mx.fit@output$calculatedHessian, parameters = my.name) : Error in solving the Hessian matrix. Generalized inverse is used. The standard errors may not be trustworthy.

> stage2_direct