[R] Interactions in a nls model

[Anthony Lawrence Nguy-Robertson]

Thank you R-forum for you generous help.

Gabor Grothendieck, I am not sure if anova in the form that you 
suggested is the most appropriate (This is probably more of a statistics 
related, rather than R related at this point). The way I understand 
anova is that you are testing the variance between the models. I know 
that the variance in the 'corn' models is greater than 'soybean' due to 
a biological reason. I don't think this approach is correct in my case 
since the anova analysis is comparing variance between different data sets.

However, using the approach suggested by Derek Ogle seems to produce 
results that make more sense since the anova analysis is between the 
entire data set and the influence of crop type on that model. For the 
couple of models I tested thus far, I think this is the approach I need 
to take. I am not a statitician, so I hope my descriptions make sense. 
Again I appreciate everyone's help in this matter.

Thanks,
Tony

On 2/9/2011 7:53 AM, Derek Ogle wrote:
> Anthony,
>
> The link below shows how I did a similar analysis but for a different nls model.  Perhaps it will be useful to you ...
>
> http://www.ncfaculty.net/dogle/fishR/gnrlex/VonBertalanffyCompare/VonBertalanffyCompare.pdf
>
> Good luck.
>
>    
>> -----Original Message-----
>> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
>> project.org] On Behalf Of Gabor Grothendieck
>> Sent: Tuesday, February 08, 2011 10:43 PM
>> To: Anthony Lawrence Nguy-Robertson
>> Cc: r-help at r-project.org
>> Subject: Re: [R] Interactions in a nls model
>>
>> On Tue, Feb 8, 2011 at 4:12 PM, Anthony Lawrence Nguy-Robertson
>> <anthony.robertson at huskers.unl.edu>  wrote:
>>      
>>> I am interested in testing two similar nls models to determine if the
>>>        
>> lines
>>      
>>> are statistically different when fitted with two different data sets;
>>>        
>> one
>>      
>>> corn, another soybean. I know I can do this in linear models by
>>>        
>> testing for
>>      
>>> interactions. See Introductory Statistics with R by Dallgaard p212-
>>>        
>> 218 for
>>      
>>> an example. I have two different data sets I am comparing to lai.
>>>        
>> ci.re
>>      
>>> should have very little difference between corn and soybean, while
>>>        
>> ci.gr,
>>      
>>> there should be a difference. If I use the simplistic form described
>>>        
>> in
>>      
>>> Dallgaard (see example in code below) it does not work correctly.
>>>        
>> What do I
>>      
>>> need to do to test for this interaction? Thank you!
>>>
>>> My data is located here: ftp://snrftp.unl.edu/Outgoing/example/
>>>
>>> Here is my example code:
>>>
>>> ###load data###
>>> data<- read.csv("example.csv", header=TRUE)
>>> eq<- function(x,a,b,c) {a+b*exp(x^c)}
>>>
>>> ##create non-linear models##
>>> nls.ci.re<- nls(lai~eq(ci.re,a,b,c),data=data, start=c(a=1,b=1,c=1))
>>> nls.ci.gr<- nls(lai~eq(ci.gr,a,b,c),data=data, start=c(a=1,b=1,c=1))
>>>
>>> #create non-linear models for corn#
>>> nls.ci.re.corn<-
>>>        
>> nls(lai~eq(ci.re,a,b,c),data=subset(data,crop=="corn"),
>>      
>>> start=c(a=1,b=1,c=1))
>>> nls.ci.gr.corn<-
>>>        
>> nls(lai~eq(ci.gr,a,b,c),data=subset(data,crop=="corn"),
>>      
>>> start=c(a=1,b=1,c=1))
>>>
>>> #create non-linear models for soybean#
>>> nls.ci.re.soybean<-
>>> nls(lai~eq(ci.re,a,b,c),data=subset(data,crop=="soybean"),
>>> start=c(a=1,b=1,c=1))
>>> nls.ci.gr.soybean<-
>>> nls(lai~eq(ci.gr,a,b,c),data=subset(data,crop=="soybean"),
>>> start=c(a=1,b=1,c=1))
>>>
>>> #test interactions according to Introductory Statistics with R by
>>>        
>> Dalgaard
>>      
>>> p. 213#
>>> corn.soybean.interactions.ci.re.a<-
>>>     abs((summary(nls.ci.re.corn)$coeff[1,1]-
>>>     summary(nls.ci.re.soybean)$coeff[1,1])/
>>>     sqrt(summary(nls.ci.re.corn)$coeff[1,2]^2+
>>>     summary(nls.ci.re.soybean)$coeff[1,2]^2))
>>>
>>> corn.soybean.interactions.ci.gr.a<-
>>>     abs((summary(nls.ci.gr.corn)$coeff[1,1]-
>>>     summary(nls.ci.gr.soybean)$coeff[1,1])/
>>>     sqrt(summary(nls.ci.gr.corn)$coeff[1,2]^2+
>>>     summary(nls.ci.gr.soybean)$coeff[1,2]^2))
>>>
>>> corn.soybean.interactions.ci.re.a.p.value<-
>>>
>>>        
>> pt(corn.soybean.interactions.ci.re.a,df=summary(nls.ci.re.corn)$df[2],l
>> ower.tail=FALSE)
>>      
>>> corn.soybean.interactions.ci.gr.a.p.value<-
>>>
>>>        
>> pt(corn.soybean.interactions.ci.gr.a,df=summary(nls.ci.gr.corn)$df[2],l
>> ower.tail=FALSE)
>>
>> There is an anova.nls method: anova(model1, model2)
>>
>>
>> --
>> Statistics&  Software Consulting
>> GKX Group, GKX Associates Inc.
>> tel: 1-877-GKX-GROUP
>> email: ggrothendieck at gmail.com
>>
>> ______________________________________________
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>> PLEASE do read the posting guide http://www.R-project.org/posting-
>> guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>      
> .
>
>    

-- 
Anthony L. Nguy-Robertson
Doctoral Student
University of Nebraska-Lincoln
School of Natural Resources
Center for Advanced Land Management Information Technologies (CALMIT)
223 Hardin Hall
3310 Holdrege Street
Lincoln, NE  68583
Office: 402-472-2565
Fax: 402-472-2946
Email: anguy-robertson at unlnotes.unl.edu