To understand an error message like you reported, someone recently
suggested using "traceback()". That's worth trying. If that is
not
adequate, I've had good luck using "debug" to trace through code
line by
line. With "lme", however, it's not completely transparent how to
do
that, because the function consists of only one line,
'UseMethod("lme")'. The function
'methods("lme")' gives us the following:
[1] lme.formula lme.groupedData* lme.lmList
This tells us that 'UseMethod("lme")' calls
'lme.formula' if the first
argument is of class 'formula', which covers your example. You can then
walk through the code line by line until you find the line that produces
your error message. Then you can study that statement by itself, read
its documentation and try different things until you figure out what you
need to make it do what you want.
If you had provided a replicable example, as suggested in the posting
guide (www.R-project.org/posting-guide.html), I might have been able to
help more -- or someone else might have answered your question sooner.
hope this helps,
spencer graves
Pryseley Assam wrote:
> Dear R-users
>
> I have problems using lme
>
> The model i want to fit can be viewed as a two-level bivariate model
>
> Two-level bivariate: bivariate (S coded as -1,T coded as 1) endpoint within
trial
> OR
> It can equivalently be considered as a three-level model.Three-level:
endpoint within patient, patient within trial.
>
> My code tries to model the levels through a RANDOM statement and a within
group correlation structure.
>
>
----------------------------------------------------------------------------------------------------------
>
> Now then, i used the following R code:
> bm <- lme (outcome~ -1 + as.factor(endpoint)+ as.factor(endpoint):trt,
data=datt,
> random=~-1 + as.factor(endpoint) + as.factor(endpoint):trt
|as.factor(Trial),
> corr = corSymm(form~-1+as.factor(endpoint)|trial/subject))
>
> I beleive the fixed effects part of the code is okay. My intention for the
random effects part is to estimate an intercept and treatment effect for
each
endpoint at the trial level. The correlation structure should produce a
within
correlation matrix for the enpoints at the subject
level.>
> Thus the random effects matrix is 4 by 4 and the within correlation
matrix is 2 by 2
> When i run the code in R, i get the following error message
>
> "Error in Initialize.corSymm(X[[2]], ...) :
> Initial value for corSymm parameters of wrong dimension"
>
> I hope someone will correct my codes .
>
> Kind regards
> Pryseley
>
>
>
>
>
>
>
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