Applies an F-test to a non-linear regression model that includes a grouping variable (fit with
nlsList), comparing it to a model without a grouping variable. This is a convenient way to test whether there is an overall effect of the grouping variable on the non-linear relationship.
The full model, an object returned by
The reduced model, which is identical to the full model except the grouping variable has been removed, and it was fit with
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chick <- as.data.frame(ChickWeight) # Fit a simple model with nls fit0 <- nls(weight ~ a*Time^b, data=chick, start=list(a=10, b=1.1)) # Fit an nlsList model, with a grouping variable (Diet) fit1 <- nlsList(weight ~ a*Time^b | Diet, data=chick, start=list(a=10, b=1.1)) # Using an F-test, test whether the fit is significantly better when adding # a grouping variable anova_nlslist(fit1, fit0)
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