Using NLME in version 6.1 on a Sun Sparc.
I get getting a message about NA's even though I have no missing data in
my dataset.
I have 4 pairs of corneas, 1 case - 1 control per pair.
Corneas were stored in solution and concentration of a chemical
was measured everyday for 21 days in all 8 samples.
> noGD
Grouped Data: Conc ~ Day | Sam
Day Group Eye Conc Sam
1 1 0 A 0.00000000 A0
2 2 0 A 0.10595760 A0
3 3 0 A 0.53191440 A0
4 4 0 A 0.90191355 A0
5 5 0 A 1.13137230 A0
6 6 0 A 1.65407400 A0
7 7 0 A 2.03353260 A0
8 8 0 A 2.21974815 A0
9 9 0 A 2.45190960 A0
To prove I have no missing:
> apply(is.na(noGD),2,sum)
Day Group Eye Conc Sam
0 0 0 0 0
And I have numerics and factors where appropriate:
> unlist(lapply(noGD,class))
Day Group Eye Conc Sam
"numeric" "numeric" "factor" "numeric" "factor"
But when I try to fit the Michaelis-Menten model for each of the 8 corneas
I receive a strange error:
> fitList <- nlsList(Conc ~ SSmicmen(Day, Vm, K), data=noGD)
Problem in nls(y ~ x/(K + x), data = xy, start = lis..: 21 NAs found in
value, while calling subroutine setup_nonlin
Use traceback() to see the call stack
(this error repeats 8 times).
I get the same error when trying to fit 1 model to all 168 data point:
> fit <- nls(Conc ~ SSmicmen(Day, Vm, K), data=noGD)
Problem in nls(y ~ x/(K + x), data = xy, start = lis..: 21 NAs found in
value, while calling subroutine setup_nonlin
Use traceback() to see the call stack
Any suggestions for things to try?
Thank you.
Jason
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