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CecileProust-Lima / lcmm

R package lcmm
https://CecileProust-Lima.github.io/lcmm/
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Questions regarding predicted trajectories and weighted subject-specific predicitons #262

Open Esther-ye2024 opened 6 days ago

Esther-ye2024 commented 6 days ago

Hi @CecileProust-Lima, @VivianePhilipps,

Thank you very much for developing package.

I am using the lcmm package to identify latent classes. I encountered two problems.

  1. I run the hlme() function on longitudinal outcome for anxiety z score. The original z score outcome has a minimum of -1.76 and a maximum of 5.80. When I plot the predicted trajectories, one trajectory decreased to lower than -10. I was wondering if the predictY showed the exact predicted z score and how to interpret the predicted trajectory for the z score. Here are my code and plot.

    data_pred <- data.frame(Time=seq(4,16,length.out=50))
data_pred$Time10 <- (data_pred$Time - 4)/10
pred <- predictY(lcga2, data_pred, var.time = "Time")
plot(pred, col=c("red","navy"), lty=1,lwd=5,ylab="anxiety",xlab="age",legend=NULL,  main="Predicted trajectories for anxiety ",ylim=c(-10,5))

    l image 1

  2. I followed the code in the vignette to plot Graph of the predictions versus observations.

plot(lcga2, which="fit", var.time="Time", marg=FALSE, shades = TRUE)

The plot was different from my predicted trajectory in terms of the trajectory and x axis values. Could you please let me know how to solve this problem.

image 2

Thank you very much in advance for your help with this issue and kind regards, Esther