Mixed Effects and Nested Models
Longitudinal twin analysis with at most three time points
Hello, I'm working on a twin database (monozigotic and dyzigotic) with 537 twin pairs, of which 311 are present in only one wave, 139 have two time points and 77 three data points.
I fitted the saturated and ACE models on the 311 with one time point only, but I'm wondering how to use the longitudinal aspect in the 216 twin pairs, as I did with linear mixed models in which I added random components.
Can you suggest a way (and/or also a possibile script) for this analysis?
Many thanks in advance
Ugo Lancia
two-level growth mixture model
I am trying to fit a two-level growth mixture model (which is three-level LMM with two latent classes).
The subject's outcome (y0, y1, y2, y3) is nested within the subject and then nested within different centers.
##wide type
data <- reshape(indata[,c("Center","ID","Time","y")], idvar = c("Center","ID"), timevar = "Time", direction = "wide", sep = "")
centerdata= data.frame(Center= mydata3[!duplicated(mydata3$Center),1])
- Read more about two-level growth mixture model
- 4 comments
- Log in or register to post comments
Mulitlevel model with ordinal data
- Read more about Mulitlevel model with ordinal data
- 4 comments
- Log in or register to post comments
Variance components in two-level models
I want to estimate the variance components in a two-level model. The estimated variances seem correct when there is only one variable. However, the estimated variances appear incorrect when more than one variable. The observation is that the between-level variances are under-estimated, whereas the within-level variances are over-estimated.
Attached is an example with 1,000 level-2 units, each with 100 level-1 units. This ensures that sampling error does not play a critical role.
Did I do something wrong here? Thanks in advance.
- Read more about Variance components in two-level models
- 1 comment
- Log in or register to post comments
Nesting with movement between clusters over time
CHILDID, Y1, X1, SCHOOLID1, Y2, X2, SCHOOLID2, ...
I initially considered having a single random effect value per school, and having $y_{i,t,school} = \mu_{school} + \dots$, but I'm not sure how to index the same random effect by different variables over time (i.e. mu[SCHOOL1]
, mu[SCHOOL2]
) in this way.
Mixed-effects mediation example in openmx?
thank you so much for developing openmx, it's fantastic and flexible.
Do you probably have an example for openmx for a
(i) mediation model in openmx, or
(ii) mediation in a mixed-effects model [at the cluster-level or the within-cluster-level]
(Couldn't find any on the page here nor google).
Cheers, and thank you!
Jana
- Read more about Mixed-effects mediation example in openmx?
- Log in or register to post comments
Two-parts mixed effects model for longitudinal data with mixture distribution for random effects
My outcome variable is a semicontinuous variable measured over time with a bunch of zero values. Since it is continuous data I cannot use poison or other zero-inflated models. However, I am implementing a two-parts model. The first part is a logistic mixed effects model for modeling the zero currency. Then, the second part is a linear mixed effects model. Now, there are two main issues. First, the random effects of both models are correlated. Second, the distribution of the random effects is a mixture of normal distributions.
Postulating mixed effects model with random intercepts and slopes
Latent variables depict latent intercepts and latent slopes.
I am a beginner in OpenMx and need to check the model urgently.
I would be really grateful if you could help.
Multilevel, longitudinal model (3-level model)
I know similar questions have been posted here but I'm still unable to figure out the code for my model, as I am super new to OpenMx and structural equation modeling in general. I have intervention data collected at three time-points on children nested within schools. I would like to look at the effect of the intervention over time for the children, but taking the clustering from the schools into account. I'm trying to get my structural equation model to match this mixed model from the nlme package:
Combined multi-group and multi-level SEM
- Read more about Combined multi-group and multi-level SEM
- 3 comments
- Log in or register to post comments
Pagination
- Page 1
- Next page