Longitudinal SEM and Latent Growth Curves
kme
Joined: 04/27/2022
Individual slope and intercept estimates?
I'm fitting a growth curve model (not latent growth curve model yet) using intercept and slope factors, and need individuals' slope and intercept estimates.
My inclination is to get factor score estimates for the intercept and slope factors, but when I do this using mxFactorScores(), I get an error message:
"Error: In model 'FactorScoresLGCM_N' the name 'fscore' is used as a free parameter in 'FactorScoresLGCM_N.Score' but as a fixed parameter in 'FactorScoresLGCM_N.Score'.
- Read more about Individual slope and intercept estimates?
- 6 comments
- Log in or register to post comments
ssciarra
Joined: 01/08/2021
Structured latent growth curve with definition variables
I am trying to fit a structured latent growth curve model where the actual days of observation are inserted into the latent variable loadings using definition variables. Unfortunately, I run into the following error:
Error in value[rows[[i]], cols[[i]]] <- startValue :
incorrect number of subscripts on matrix
Pablo F Cáncer
Joined: 08/15/2021
LCS: Effect of a time-independent predictor on a covariance
I'm trying to model the effect of a time-independent predictor on the parameters of a dual latent change score model (in discrete time). My predictor is the cohort to which the subjects belong. The groups (cohorts) of individuals in my data have different values for the parameters (e.g., different self-feedbacks, mean and variance of the slope...). I managed to successfully account for cohort effects on means, variances, and regression parameters, just using mxPaths.
ssciarra
Joined: 01/08/2021
How to use the EM algorithm with a nonlinear latent growth curve model?
I am trying to fit a nonlinear latent growth curve model (as part of simulations I am conducting) using the three-parameter logistic (s-shaped change) function below
$$y_{obs} = \frac{diff}{1+e^{\frac{\beta - time_i}{\gamma}}}, $$
mxruby
Joined: 11/23/2020
RI-CLPM: covariates and scaling
I'm new to all things SEM, but I'm attempting to use OpenMx for a Cross-lagged Panel Model (with random intercepts) on longitudinal data in youth. I have two measured variables at two timepoints, equally spaced apart. I have gone through John Flournoy's tutorials (http://johnflournoy.science/2018/09/26/riclpm-openmx-demo/) as well as several other resources on this topic, but I have a few questions I was hoping I could get some input on from the experts here!
- Read more about RI-CLPM: covariates and scaling
- 1 comment
- Log in or register to post comments
ZR
Joined: 07/26/2017
Cross-lagged model issues
Hello,
I have a cross-lagged model that I have run using the code below:
- Read more about Cross-lagged model issues
- 15 comments
- Log in or register to post comments
rranne2@uic.edu
Joined: 12/10/2018
negative variance in factor representing change in anxiety (latent factor)
Hello there!
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.
Aivil
Joined: 03/14/2019
How to implement FIML estimation in OpenMx?
Hello,
I am running this code to conduct LGCM prior to GMM.
I was wondering if there is a way of implementing FIML instead of ML in my code.
This is because my data has a lot of missingness by design (longitudinal data) and is not normally distributed.
Many thanks!!!
require(OpenMx)
?MxFitFunction
fitFunction <- mxFitFunctionML(rowDiagnostics=TRUE)
mxOption(NULL,"Default optimizer","SLSQP") ### to avoid msg error: https://openmx.ssri.psu.edu/node/4238
- Read more about How to implement FIML estimation in OpenMx?
- 1 comment
- Log in or register to post comments
Aivil
Joined: 03/14/2019
Help in understanding notation for NO-GROWTH MODEL (OpenMx) and ERROR message
Hello,
I´m having a hard time understanding the OpenMx notation from this handbook "Growth Modeling" (Grimm, Ram & Estabrook, 2017).
The authors compare the script from MPlus and OpenMx with regard to the specification of a no-growth model (attached as pics). While in Mplus is pretty straightforward, I don´t understand why the latent factor variance (psi_11) and the indicators residual variances are set at 80 and 60 respectively in the OpenMx script.
ethibodeau
Joined: 05/16/2018
More questions about the magic of LGM with use of age definition variables
Either SEMNET is not getting my emails or they don't care about my questions (probably the latter), so I'll ask them here specific to OpenMx.