I'd like to know how can I test for inequality of estimates in a
lavaan::sem() fitted model (using
Also, is there a known way to control for the fact that some estimates come from reverse scored scales?
The example model I work with is specified as:
model <- ' # measurement model opp =~ FTP1 + FTP2 + FTP3 + FTP9 ext =~ FTP4 + FTP5 + FTP6 + FTP7 const =~ FTP8 + FTP9 + FTP10 ses =~ SES1 + SES2 + SES3 + SES4 + SES5 + SES6 # regressions ses ~ opp + ext + const '
summary() of my
fit <- sem(model, data=w1) object I can tell that one of the predictors is unsignificant
Regressions: Estimate Std.Err z-value P(>|z|) ses ~ opp 0.148 0.035 4.266 0.000 ext 0.103 0.072 1.440 0.150 const -0.090 0.025 -3.668 0.000
Given these numbers i'd like to test the difference between
ses~const estimates but considering the fact, that
const was computed out of reverse scored questions.
I know how to call a Wald Test of Parameter Constraints in Mplus to test the difference between the two estimates. But I sense, that the fact it is significant is due to reversed scores:
Wald Test of Parameter Constraints Value 13.131 Degrees of Freedom 1 P-Value 0.0003
I wonder how can I do it in R, and control for the fact that same of my scales have negative estimates due to the way they are measured?
Please note, that I'm very new to SEM and odds are I'm after something not making any sense. If that's the case, please let me know. I'm happy to learn. All the best. Thank you.