Longitudinal SEM and Latent Growth Curves

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No user picture. 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'.

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No user picture. 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

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No user picture. 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.
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No user picture. 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

$$y_{obs} = \frac{diff}{1+e^{\frac{\beta - time_i}{\gamma}}}, $$

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No user picture. 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!

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No user picture. ZR Joined: 07/26/2017

Cross-lagged model issues

Hello,
I have a cross-lagged model that I have run using the code below:

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No user picture. 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.

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No user picture. 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

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No user picture. 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.

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No user picture. 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.