[R-sig-ME] How to test if two gamm-predictions are significantly different?

[Kenneth Frost]

Hi, Karel-

Could you provide a longer sketch of your situation? It is not clear to me what your control treatment is and how it relates to concentration or time.

Ken 

On 05/29/12, Karel Viaene  wrote:
> Dear R community,
> 
> A quick sketch of my situation:
> 
> I have two continuous explanatory variables ("concentration" and "time") 
> and a continuous response variable, "biomass".
> 
> I've fitted a gamm model to these data using the package mgcv and want 
> to predict at what concentration the biomass is significantly different 
> from the control treatment (i.e. a concentration of 0) for a given point 
> in time.
> 
> I've done this by predicting the biomass for a series of 1000 
> concentrations at a given point in time (using "predict"), constructing 
> 95% confidence intervals for these predictions by adding and subtracting 
> 1.96*SE and then selecting the lowest concentration where the two CI 
> show no overlap.
> 
> However I've realized that this technique is not adequate because two 
> points can also be significantly different at the 5% significance level 
> when the 95% CI do overlap and I want to calculate the lowest possible 
> concentration. I've read some literature about this and am considering 
> the following method:
> 
> * Calculate the difference between the control (C0) and a predicted 
> point (e.g. C1), thus C0-C1.
> * Construct a 95% CI for this difference by adding and subtracting 
> 1.96*sqrt(SE0^2 + SE1^2).
> * Do this for all predictions.
> * Select the lowest concentration where the 95% CI does not include 0.
> 
> Could you give me some feedback about this as I'm unsure if this method 
> can be used for gamms. Any comments or suggestions are much appreciated.
> 
> Many thanks in advance & kind regards
> 
> Karel
> 
> -- 
> Karel Viaene
> Ghent University
> Laboratory of Environmental Toxicology and Aquatic Ecology
> Plateaustraat 22
> 9000 Ghent, Belgium
> tel: +32 (0) 9 264 3779
> 
> 
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> 
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