# Complex data anaysis in REM doesn't result

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Joined: 12/04/2019 - 08:04
Complex data anaysis in REM doesn't result
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Dear Mike & colleagues,
First of all, I am grateful for asking my question to this forum where gurus of meta-SEM are helping people like me.
I'm trying to make analysis in your metasem package. I have 41 studies and so 41 correlation matrices. and the correlation matrices consist of 20x20.
While i was anaysing the data under the fixed effects model, the results came after a long time. But while i'm trying to analyse under the random effect model, the analysis is running but no results even though I wait a long time. Why i can not take the result, becouse of amount of matrices or items/complex data?

May I ask how can handle this problem?

Thanks for your time and patience.

(i added my syntax for you to review )

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Joined: 10/08/2009 - 22:37
Hi vildan,

Hi vildan,

For the fixed-effects model, you are fitting a multiple-group analysis with 41 groups. For the random-effects model, there are 20x19/2 random effects. Both of them are computationally intensive. It may take a long time to run them. It may be better to run these analyses in High-performance computing (HPC) computers.

BTW, I have modified the code a bit for your reference. I hope it works.

## Add the variable labels to the data
var.names <- paste0("x", 1:20)
ucla <- lapply(ucla, function(x) {dimnames(x) <- list(var.names, var.names); x})

## First stage of the analysis
random1 <- tssem1(ucla, n, method="REM")
summary(random1)

## Create the model in lavaan syntax
model <- paste0("f =~ ", paste0("x", 1:20, collapse = "+"))

## Plot it for checking
plot(model)

## Convert it into RAM specification
RAM1 <- lavaan2RAM(model, obs.variables = var.names)
RAM1

## Second stage of the analysis
random2 <- tssem2(random1, RAM=RAM1)
summary(random2)

## Plot the results
plot(random2)

Best,
Mike