lavPredict

[Nour Fayed]

So I'm trying to get Factor Scores after an SEM, and I want to test different scenarios for policy analysis. 

Each scenario consists of setting all collected values of one of the latent variables (so all corresponding indicators) to the maximum level (5 on a likert scale) . When I do this, using lavPredict, I get the following:

model1 = '

OVERALL=~Q1+Q2+Q4

IAQ=~Q19+Q20+Q21+Q22

ACOUSTIC=~Q24+Q25+Q27+Q28

THERMAL=~Q13+Q14+Q15+Q17

OVERALL~IAQ+ACOUSTIC+THERMAL

'

model1.fit <- sem(model1, data = mydata, std.lv=TRUE, fixed.x=TRUE, ordered = names(mydata))

#Factor Score

lavPredict(model1.fit, newdata = dataIAQ, label = TRUE)

Error in lav_data_full(data = data, group = group, cluster = cluster,  : 

  lavaan ERROR: ordered variable(s) has/have only 1 level

Note that mydata is the original data collected, and dataIAQ is the one where I manually set the answers to 5.

Is there a way to fix this?

Thanks!

[Christopher David Desjardins]

I am guessing by "dataIAQ", you mean you set that latent variable's indicators: Q19, Q20, Q21, and Q22 to 5? Then they have no variance and no covariance. Does this model run? If you have a variable with only one value, then it's a constant. You should remove it.

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[Nour Fayed]

Yes that's exactly what I did.. I guess I'll have to figure another way.

Thanks!