[R] Understanding lm-based analysis of fractional factorial experiments

[Peter Claussen]

On Mar 6, 2013, at 9:23 AM, Kjetil Kjernsmo <kjekje at ifi.uio.no> wrote:

> On 03/06/2013 04:18 PM, Peter Claussen wrote:
>> I'll ignore the rest of your question, in the hope that this will answer them sufficiently.
> 
> OK!
> 
>> You probably want a simple linear model, specified in R using "+" instead of "*".
>> 
>>> >leaf.lm <- lm(yavg ~ B + C + D + E + Q, data=leaf)
>>> >leaf.lm
>> Call:
>> lm(formula = yavg ~ B + C + D + E + Q, data = leaf)
>> 
>> Coefficients:
>> (Intercept)           B+           C+           D+           E+           Q+
>>     7.50084      0.22125      0.17625      0.02875      0.10375     -0.25960
>> 
>> Does this give you the numbers you expect?
> 
> Well, it partly gives the numbers I expect, but I want the interactions as well, so it is only a partial answer.


But you don't have enough data points to estimate all of the possible interactions; that's why you have NA in your original results. You could add the just the first order interactions manually, i.e.,  + B:C + B:D …

Peter

> 
> Best,
> 
> Kjetil
> 
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