negative variance in factor representing change in anxiety (latent factor)

I'm having trouble with a model investigating change in anxiety over time. In the future, I will be building out a more complex model with other factors predicting change in anxiety over time, but I'm now just at a step before that looking into a model with only change in anxiety over time--only for two time points.

Even before I did this step, I looked into invariance over time for the items that make up the latent factor of anxiety at both time points. This was a brief four item measure of anxiety. That initial test looked good with positive variances and a good fit.

I used the method to form a latent change factor using the McArdle method from his 2009 paper "Latent Variable Modeling of Differences and Changes with Longitudinal Data." However, I was getting negative variance when I did this. This is the code for this model (I have attached the visual for this original model):

Finalmodelanxietystep2<-mxModel(model="finalmodelanxietystep2", type="RAM", manifestVars=manifests, latentVars=latents,
mxPath(from="Time2anxiety", to="Time2anxiety_1a", arrows=1, free=TRUE, values=0.8476268, labels=c("anxanx1a")),
mxPath(from="Time2anxiety", to="Time2anxiety_1b", arrows=1, free=TRUE, values=0.8577030, labels=c("anxanx1b")),
mxPath(from="Time2anxiety", to="Time2anxiety_1f", arrows=1, free=TRUE, values=0.8541549, labels=c("anxanx1f")),
mxPath(from="Time2anxiety", to="Time2anxiety_1h", arrows=1, free=TRUE, values=0.8378001, labels=c("anxanx1h")),
mxPath(from="Time4anxiety", to="Time4anxiety_1a", arrows=1, free=TRUE, values=0.8476268, labels=c("anxanx1a")),
mxPath(from="Time4anxiety", to="Time4anxiety_1b", arrows=1, free=TRUE, values=0.8577030, labels=c("anxanx1b")),
mxPath(from="Time4anxiety", to="Time4anxiety_1f", arrows=1, free=TRUE, values=0.8541549, labels=c("anxanx1f")),
mxPath(from="Time4anxiety", to="Time4anxiety_1h", arrows=1, free=TRUE, values=0.8378001, labels=c("anxanx1h")),
mxPath(from = "L1", to = "Time2anxiety", arrows=1, free=FALSE , values=1, labels=c("L1T2anx")),
mxPath(from = "L2", to = "Time4anxiety", arrows=1, free=FALSE , values=1, labels=c("L2T4anx")),
mxPath(from = "L1", to = "L2", arrows=1, free=FALSE , values=1, labels=c("L1L2")),
mxPath(from = "changeanxiety", to = "L2", arrows=1, free=FALSE , values=1, labels=c("changeanxT4L2")),
mxPath(from ="L1", to = "changeanxiety", arrows = 2, free=TRUE, values = -.9, labels=c("L1changeanx")),
mxPath(from = "L1", to = "L1", arrows = 2, free=FALSE, values = 1, labels=c("L1var")),
mxPath(from = "Time2anxiety", to = "Time2anxiety", arrows = 2, free=FALSE, values = 1, labels=c("T2anxvar")),
mxPath(from = "Time4anxiety", to = "Time4anxiety", arrows = 2, free=FALSE, values = 1, labels=c("T4anxvar")),
mxPath(from = "changeanxiety", to = "changeanxiety", arrows = 2, free=TRUE, values = 100, labels=c("changeanxvar")),
mxPath(from = "Time2anxiety_1a", to = "Time2anxiety_1a", arrows = 2, free=TRUE, values = 0.5647315, labels=c("anx1avar")),
mxPath(from = "Time2anxiety_1b", to = "Time2anxiety_1b", arrows = 2, free=TRUE, values = 0.3528205, labels=c("T2anx1bvar")),
mxPath(from = "Time2anxiety_1f", to = "Time2anxiety_1f", arrows = 2, free=TRUE, values = 0.5079372, labels=c("anx1fvar")),
mxPath(from = "Time2anxiety_1h", to = "Time2anxiety_1h", arrows = 2, free=TRUE, values = 0.5221816, labels=c("anx1hvar")),
mxPath(from = "Time4anxiety_1a", to = "Time4anxiety_1a", arrows = 2, free=TRUE, values = 0.5647315, labels=c("anx1avar")),
mxPath(from = "Time4anxiety_1b", to = "Time4anxiety_1b", arrows = 2, free=TRUE, values = 0.2175539, labels=c("T4anx1bvar")),
mxPath(from = "Time4anxiety_1f", to = "Time4anxiety_1f", arrows = 2, free=TRUE, values = 0.5079372, labels=c("anx1fvar")),
mxPath(from = "Time4anxiety_1h", to = "Time4anxiety_1h", arrows = 2, free=TRUE, values = 0.5221816, labels=c("anx1hvar")),
mxPath(from = "one", to = "changeanxiety", arrows=1, free=TRUE, values = -1.5, labels=c("mchangeanx")),
mxPath(from = "one", to = "Time4anxiety", arrows=1, free=FALSE, values = 0, labels=c("mT4anx")),
mxPath(from = "one", to = "Time2anxiety", arrows=1, free=FALSE, values = 0, labels=c("mT2anx")),
mxPath(from = "one", to = "L1", arrows=1, free=FALSE, values = 0, labels=c("mL1")),
mxPath(from = "one", to = "Time2anxiety_1a", arrows=1, free=TRUE, values = 2.29, labels=c("mT2anx1a")),
mxPath(from = "one", to = "Time2anxiety_1b", arrows=1, free=TRUE, values = 1.68, labels=c("mT2anx1b")),
mxPath(from = "one", to = "Time2anxiety_1f", arrows=1, free=TRUE, values = 1.85, labels=c("mT2anx1f")),
mxPath(from = "one", to = "Time2anxiety_1h", arrows=1, free=TRUE, values = 1.68, labels=c("mT2anx1h")),
mxPath(from = "one", to = "Time4anxiety_1a", arrows=1, free=TRUE, values = 2.22, labels=c("mT4anx1a")),
mxPath(from = "one", to = "Time4anxiety_1b", arrows=1, free=TRUE, values = 1.60, labels=c("mT4anx1b")),
mxPath(from = "one", to = "Time4anxiety_1f", arrows=1, free=TRUE, values = 1.81, labels=c("mT4anx1f")),
mxPath(from = "one", to = "Time4anxiety_1h", arrows=1, free=TRUE, values = 1.65, labels=c("mT4anx1h")),
mxData(observed=mydata8, type="raw"))

Finalmodelanxietystep2Run <-mxTryHard(Finalmodelanxietystep2)
refMods<-mxRefModels(Finalmodelanxietystep2Run, run = T)
summary(Finalmodelanxietystep2Run, refModels=refMods)

No matter what I used as starting points for the variance in change in anxiety and the covariance of L1 and change in anxiety, it always came up as the same negative number, -.69.

Then, I thought that maybe I should also add in the covariance between T2 anxiety and T4 anxiety, like this (only added piece is the T2anxT4anx parameter):

Finalmodelanxietystep2<-mxModel(model="finalmodelanxietystep2", type="RAM", manifestVars=manifests, latentVars=latents,
mxPath(from="Time2anxiety", to="Time2anxiety_1a", arrows=1, free=TRUE, values=0.8476268, labels=c("anxanx1a")),
mxPath(from="Time2anxiety", to="Time2anxiety_1b", arrows=1, free=TRUE, values=0.8577030, labels=c("anxanx1b")),
mxPath(from="Time2anxiety", to="Time2anxiety_1f", arrows=1, free=TRUE, values=0.8541549, labels=c("anxanx1f")),
mxPath(from="Time2anxiety", to="Time2anxiety_1h", arrows=1, free=TRUE, values=0.8378001, labels=c("anxanx1h")),
mxPath(from="Time4anxiety", to="Time4anxiety_1a", arrows=1, free=TRUE, values=0.8476268, labels=c("anxanx1a")),
mxPath(from="Time4anxiety", to="Time4anxiety_1b", arrows=1, free=TRUE, values=0.8577030, labels=c("anxanx1b")),
mxPath(from="Time4anxiety", to="Time4anxiety_1f", arrows=1, free=TRUE, values=0.8541549, labels=c("anxanx1f")),
mxPath(from="Time4anxiety", to="Time4anxiety_1h", arrows=1, free=TRUE, values=0.8378001, labels=c("anxanx1h")),
mxPath(from = "L1", to = "Time2anxiety", arrows=1, free=FALSE , values=1, labels=c("L1T2anx")),
mxPath(from = "L2", to = "Time4anxiety", arrows=1, free=FALSE , values=1, labels=c("L2T4anx")),
mxPath(from = "L1", to = "L2", arrows=1, free=FALSE , values=1, labels=c("L1L2")),
mxPath(from = "changeanxiety", to = "L2", arrows=1, free=FALSE , values=1, labels=c("changeanxT4L2")),
mxPath(from ="L1", to = "changeanxiety", arrows = 2, free=TRUE, values = -.9, labels=c("L1changeanx")),
mxPath(from ="Time2anxiety", to = "Time4anxiety", arrows = 2, free=TRUE, values = .67, labels=c("T2anxT4anx")),
mxPath(from = "L1", to = "L1", arrows = 2, free=FALSE, values = 1, labels=c("L1var")),
mxPath(from = "Time2anxiety", to = "Time2anxiety", arrows = 2, free=FALSE, values = 1, labels=c("T2anxvar")),
mxPath(from = "Time4anxiety", to = "Time4anxiety", arrows = 2, free=FALSE, values = 1, labels=c("T4anxvar")),
mxPath(from = "changeanxiety", to = "changeanxiety", arrows = 2, free=TRUE, values = 100, labels=c("changeanxvar")),
mxPath(from = "Time2anxiety_1a", to = "Time2anxiety_1a", arrows = 2, free=TRUE, values = 0.5647315, labels=c("anx1avar")),
mxPath(from = "Time2anxiety_1b", to = "Time2anxiety_1b", arrows = 2, free=TRUE, values = 0.3528205, labels=c("T2anx1bvar")),
mxPath(from = "Time2anxiety_1f", to = "Time2anxiety_1f", arrows = 2, free=TRUE, values = 0.5079372, labels=c("anx1fvar")),
mxPath(from = "Time2anxiety_1h", to = "Time2anxiety_1h", arrows = 2, free=TRUE, values = 0.5221816, labels=c("anx1hvar")),
mxPath(from = "Time4anxiety_1a", to = "Time4anxiety_1a", arrows = 2, free=TRUE, values = 0.5647315, labels=c("anx1avar")),
mxPath(from = "Time4anxiety_1b", to = "Time4anxiety_1b", arrows = 2, free=TRUE, values = 0.2175539, labels=c("T4anx1bvar")),
mxPath(from = "Time4anxiety_1f", to = "Time4anxiety_1f", arrows = 2, free=TRUE, values = 0.5079372, labels=c("anx1fvar")),
mxPath(from = "Time4anxiety_1h", to = "Time4anxiety_1h", arrows = 2, free=TRUE, values = 0.5221816, labels=c("anx1hvar")),
mxPath(from = "one", to = "changeanxiety", arrows=1, free=TRUE, values = -1.5, labels=c("mchangeanx")),
mxPath(from = "one", to = "Time4anxiety", arrows=1, free=FALSE, values = 0, labels=c("mT4anx")),
mxPath(from = "one", to = "Time2anxiety", arrows=1, free=FALSE, values = 0, labels=c("mT2anx")),
mxPath(from = "one", to = "L1", arrows=1, free=FALSE, values = 0, labels=c("mL1")),
mxPath(from = "one", to = "Time2anxiety_1a", arrows=1, free=TRUE, values = 2.29, labels=c("mT2anx1a")),
mxPath(from = "one", to = "Time2anxiety_1b", arrows=1, free=TRUE, values = 1.68, labels=c("mT2anx1b")),
mxPath(from = "one", to = "Time2anxiety_1f", arrows=1, free=TRUE, values = 1.85, labels=c("mT2anx1f")),
mxPath(from = "one", to = "Time2anxiety_1h", arrows=1, free=TRUE, values = 1.68, labels=c("mT2anx1h")),
mxPath(from = "one", to = "Time4anxiety_1a", arrows=1, free=TRUE, values = 2.22, labels=c("mT4anx1a")),
mxPath(from = "one", to = "Time4anxiety_1b", arrows=1, free=TRUE, values = 1.60, labels=c("mT4anx1b")),
mxPath(from = "one", to = "Time4anxiety_1f", arrows=1, free=TRUE, values = 1.81, labels=c("mT4anx1f")),
mxPath(from = "one", to = "Time4anxiety_1h", arrows=1, free=TRUE, values = 1.65, labels=c("mT4anx1h")),
mxData(observed=mydata8, type="raw"))

Finalmodelanxietystep2Run <-mxTryHard(Finalmodelanxietystep2)
refMods<-mxRefModels(Finalmodelanxietystep2Run, run = T)
summary(Finalmodelanxietystep2Run, refModels=refMods)


This ran without negative variances, but the variance of change in anxiety is huge, like 66, and the covariance of L1 and change in anxiety is super negative, -33. This seems maybe a bit off?

Any help would be greatly appreciated! Thank you!