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Say the model I am working with is simply:

M <- IV
DV <- IV + M

All three constructs are obtained using the same survey, hence the common method bias issue. I thought about allowing the error terms of all three correlate, but then SEM can't compute standard errors.

Is there another way to counter this common method bias using lavaan?

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  • $\begingroup$ Questions about lavaan syntax are off topic here and will be closed. I have edited the question, because it is more broad than just lavaan. $\endgroup$ – Jeremy Miles Jan 11 at 18:17
  • $\begingroup$ And I think the answer is no. $\endgroup$ – Jeremy Miles Jan 11 at 18:17
  • $\begingroup$ Well, I know one way conceptually for SEM to counter this is to add a common latent factor (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003; Williams, Edwards, & Vandenberg 2003). But I am not sure if lavaan can do this... as it is unobserved variable/I have no data for it. $\endgroup$ – Carrie Jan 14 at 6:47
  • $\begingroup$ You can add it, but the model won't be identified. $\endgroup$ – Jeremy Miles Jan 14 at 16:59
  • $\begingroup$ ... Unless M, IV and DV are latent and have at least three (?) indicators each. This is true of every SEM program. $\endgroup$ – Jeremy Miles Jan 14 at 17:00

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