Does anyone know how to manually predict fitted values for a growth model in R?
I know I can use lavPredict(fit, type="yhat") but I want to report/explain how these values are computed in my dissertation.
Thank you for the help!
#growth model
socsupp_mean_var_resid <- 'i =~ 1*socsuppavg1 + 1*socsuppavg2 + 1*socsuppavg3 +
1*socsuppavg4 + 1*socsuppavg5 + 1*socsuppavg6
s =~ 0*socsuppavg1 + 1*socsuppavg2 + 2*socsuppavg3 +
3*socsuppavg4 + 4*socsuppavg5 + 5*socsuppavg6
# freely estimate separate residual variances between group but constrain across time
socsuppavg1 ~~ c("p1", "p2")*socsuppavg1
socsuppavg2 ~~ c("p1", "p2")*socsuppavg2
socsuppavg3 ~~ c("p1", "p2")*socsuppavg3
socsuppavg4 ~~ c("p1", "p2")*socsuppavg4
socsuppavg5 ~~ c("p1", "p2")*socsuppavg5
socsuppavg6 ~~ c("p1", "p2")*socsuppavg6'
#fitted
socsupp.full.fit <- growth(socsupp_mean_var_resid,
data = socsupp.wide.full.mis,
missing = "fiml",
group = "women")
#predict estimated values
pred_lgm_socsupp <- lavPredict(socsupp.full.fit, type="yhat")
#replicate estimated values prediction manually
# ?????