FIML Estimation
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I want to ask you.
actually, I have a problem with my data. My new data is incomplete (missing data). I read on the web if no data is lost then using FIML function, but I am confused what to put where and what. I have tried but I always fail. please help me.
other than that, is there any basis we determine the value? I tried to try to change the value of 0.25-1 and outcome affect the output Standard error of estimate.
thank you.
actually, I have a problem with my data. My new data is incomplete (missing data). I read on the web if no data is lost then using FIML function, but I am confused what to put where and what. I have tried but I always fail. please help me.
other than that, is there any basis we determine the value? I tried to try to change the value of 0.25-1 and outcome affect the output Standard error of estimate.
thank you.
Hi, To use FIML, simply
To use FIML, simply create a model with raw data.
aModel <- mxModel(name="Example with FIML",
mxData(aRawDataSet, type="raw"),
# other paths, matrices, and algebras
)
Cheers,
Mike Hunter
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In reply to Hi, To use FIML, simply by mhunter
Great. Thank You for your
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example FIML model
All you need to do is include your raw data in the mxData() line, and use the FIML objective.
Here's an example:
data(myFADataRaw, package="OpenMx")
manifests = names(myFADataRaw)
myFADataRaw = myFADataRaw[, manifests]
latents = c("G")
m1 <- mxModel("m1", type="RAM",
manifestVars = manifests,
latentVars = latents,
# Factor loadings
mxPath(from = latents, to = manifests),
# residuals and variances
mxPath(from = manifests, arrows = 2), # manifest residuals
mxPath(from = latents, arrows = 2, free = F, values = 1), # latents fixed@1
mxPath(from = c("x1", "x2"), to = "x3", arrows = 1), # manifest causes
mxPath(from = "one", to = manifests, arrows = 1), # manifest means
mxData(myFADataRaw, type = "raw")
)
m1 = umxRun(m1, setLabels = T, setStart = T)
umxSummary(m1)
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