Hi all,
I am attempting to learn my way through the sem package by constructing
a simple structural model for some of my data on bird diversity,
abundance, and primary productivity.
I have constructed a covariance matrix between these variables as per
the following:
>S_matrix = matrix(c(
>+ 0.003083259, 0, 0,
>+ 0.143870284, 89.7648490, 0,
>+ 0.276950919, 81.3484101, 215.3570157
> ), ncol = 3, byrow = T)
>rownames(S_matrix) = colnames(S_matrix) = c("dec_mean_EVI", "density",
"ALL_Jack1")
I then construct a model using a symbolic ram specification as follows
>tmodel <- specify.model()
>dec_mean_EVI -> density, gam1, NA
>density -> ALL_Jack1, gam2, NA
>dec_mean_EVI -> ALL_Jack1, gam3, NA
>dec_mean_EVI <-> dec_mean_EVI, ps1, NA
>density <-> density, ps2, NA
>ALL_Jack1 <-> ALL_Jack1, theta1, NA
>dec_mean_EVI <-> density, theta2, NA
>dec_mean_EVI <-> ALL_Jack1, theta2, NA
>density <-> ALL_Jack1, theta3, NA
I then try to run the sem analysis using the matrix and model.
>sem_1 <- sem(ram = tmodel, S = S_matrix, N = 88, fixed.x =
c("dec_mean_EVI"))
>summary(sem_1)
However, I only get the following error message:
"Error in sem.default(ram = ram, S = S, N = N, param.names = pars,
var.names = vars, :
The model has negative degrees of freedom = -3
In addition: Warning message:
In sem.default(ram = ram, S = S, N = N, param.names = pars, var.names =
vars, :
The following variables have no variance or error-variance parameter
(double-headed arrow):
density, ALL_Jack1, dec_mean_EVI , density , density ,
ALL_Jack1
The model is almost surely misspecified; check also for missing
covariances."
It must be obvious to those experienced with sem, but I can't yet see
where I have gone wrong in constructing my matrix or model, any thoughts
would be much appreciated.
thanks in advance,
Alex
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
