Error: "Cannot get confidence intervals...", with lme, what does it means?
check whether the following solves the problem: Total$DietC <- relevel(Total$Diet, "C") lmefit1 <- lme(Weight ~ Diet * Time, Total, random = ~ 1 | Place) intervals(lmefit1) lmefit2 <- lme(Weight ~ DietC * Time, Total, random = ~ 1 | Place) intervals(lmefit2) I hope it helps. Best, Dimtris
R.S. Cotter wrote:
Hello, In some occasions I get this error message: "Cannot get confidence intervals on var-cov components: Non-positive definite approximate variance-covariance". I have tried to figure out this by using help function, but didn't find answer to the question. I address this question with describing the model and the primary task that I want to solve. Sorry if the question is clumsy formulated, I 'm not that experienced with R and statistics. My model is: Response= Weight(continous) Explanatory variables= Time (continous) and Diet (kategorical, two groups; B&C) The primary question of interest is wheter the growth rates (Weight/Time) differ among the two diets. lmefit1<-lme(Weight ~ Diet*Time,random=~1|Place,data=Total) Summary output is ok, so far so good. But I also wanted to get the slope and confidence intervals for the growth rates for both diets (B&C), so I ran intervals(). And I got the intercept, slope and confidence intervals for diet B, see below. But I also wanted the same for the diet C, to do this I renamed diet C to A in the data sheet to force C to be the dummy variable. Is this the right way to do it? When running the intervals () once again, I got this message: "Cannot get confidence intervals on var-cov components: Non-positive definite approximate variance-covariance". What could be wrong..? Is there other ways to get the slope and confidence intervals from a lme model?
intervals(lmefit1)
Approximate 95% confidence intervals
Fixed effects:
lower est. upper
(Intercept) 66.040673 108.122242 150.203810
DietC -175.080336 -109.638518 -44.196700
Time 4.177387 5.434087 6.690788
DietC:Time 7.938101 11.180806 14.423511
attr(,"label")
[1] "Fixed effects:"
Random Effects:
Level: Place
lower est. upper
sd((Intercept)) 0.1478599 13.50651 1233.775
Within-group standard error:
lower est. upper
159.9128 174.8928 191.2761
Best regards Cotter
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