Why are variance estimates different between "Estimate" and "Std.lv" when "std.lv = TRUE" was used?

[Tetsuhiro Yamada]

I apologize if this has been answered before; please point me to the relevant thread if this is the case.

I am running an SEM model with three latent factors as follows:

'sql =~ sql1r+sql2r+sql3r+sql4r+sql5+sql6

scpos =~ slpc_prc1+slpc_prc2+slpc_prc3+slpc_prc4

slpmot =~ slpmot1+slpmot2+slpmot3+slpmot4+slpmot5

sql ~ slpmot

slpmot ~ scpos'

The estimates look like what I would expect, except in the estimated variances of the latent factors sql and slpmot, the "Estimate" is 1 for both while "Std.lv" are .844 and .939, respectively. 

My understanding is that std.lv = TRUE fixes the latent factor variance to 1, so shouldn't "Estimate" and "Std.lv" both be 1? 

If not, please help me understand why this might happen.

[Jeremy Miles]

sql and slpmot are endorgenous, so the variance is the residual variance. 

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[Tetsuhiro Yamada]

Hello Jeremy,

Thank you for the clarification.

That makes total sense; I forgot to take into account that some latent factors are being predicted by other factors in my model.

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Tetsuhiro Yamada

Doctoral Candidate

Industrial/Organizational Psychology

University of Minnesota