title: lme summary in nlme-package (r) interpretation / fails to display all levels of fixed effects
body: <p>Need some help interpreting the summary() -function results.</p>
  
  <p>I am running a <code>lme</code> from the package <code>nlme</code> in R.</p>
  
  <p>I have a simple (and quite small) dataset with three grouping variables: origin, genotype and time, response is a continuous variable named Maxi.</p>
  
  <p>Origin = 2 levels, called Ka and La</p>
  
  <p>Genotype = 3 levels nested within origin Ka and 2 levels nested within origin La</p>
  
  <p>Time = 2 levels nested within each genotype</p>
  
  <p>I am interested in the main effects of Origin, Time and their interaction. In addition to testing I'd like to have their estimates. Here's the model I had in mind:</p>
  
  <pre><code>model = lme(fixed = Maxi ~ Origin*Time, random = ~ 1 |Genotype)
  </code></pre>
  
  <p><code>anova()</code>s etc work fine and there's actually no significant interaction, but</p>
  
  <p>here's <strong>the problem:</strong></p>
  
  <p>when I run summary(model), I get:</p>
  
  <pre><code>Fixed effects: Maxi ~ Origin * Time 
                                     Value Std.Error DF   t-value p-value
  (Intercept)                    15.399386 1.1127382 20 13.839181  0.0000
  OriginLa                       -1.986388 1.7702416  3 -1.122100  0.3435
  Timeeve                         0.074444 0.8942694 20  0.083246  0.9345
  OriginLa:Timeeve               -1.387448 1.5648876 20 -0.886612  0.3858
  </code></pre>
  
  <p>Where are my estimates for the other levels of the factors? I thought that to be able to interpret these fixed effects the summary-table would have to show all the levels in some manner? Or do I interpret this such that:</p>
  
  <pre><code>    the estimate for OriginKa is 15.399386
      the estimate for OriginLa is 15.399386-1.986388
      the estimate for Timemor  is 15.399386
      the estimate for Timeeve  is 15.399386+0.074444
  
  and then I can't even guess how to interpret the interaction estimate...
  </code></pre>
  
  <p>It doesn't feel intuitively right that the estimates would be the same for both a level of the Origin -factor and a level of the Time factor.</p>
  
  <p>Notes:</p>
  
  <ol>
  <li>I did NOT make my data into a groupedData (is it always necessary?)</li>
  <li>I wanted to include random = 1 ~ |Origin/Genotype in the model but that produced NaNs in the output, apparently the model became too complex?</li>
  </ol>
  
  <p>Any pointers?</p>
  
  <p>Here's the data needed to reproduce my problem:</p>
  
  <pre><code>Orig.Genot.Time Maxi
  Ka  Ka1     mor 14,59
  Ka  Ka1     eve 13,42
  Ka  Ka11    mor 14,08
  Ka  Ka11    eve 16,29
  Ka  Ka15    mor 14,38
  Ka  Ka15    eve 14,56
  La  La1     mor 17,82
  La  La1     eve 13,28
  Ka  Ka1     mor 16,44
  Ka  Ka1     eve 15,52
  Ka  Ka15    mor 13,76
  Ka  Ka15    eve 13,55
  Ka  Ka1     mor 19,15
  Ka  Ka1     eve 19,12
  La  La6     mor 10,54
  La  La6     mor 11,38
  La  La6     eve 10,48
  Ka  Ka15    mor 15,25
  Ka  Ka15    eve 16,51
  La  La1     mor 17,46
  La  La1     eve 15,57
  Ka  Ka1     mor 16,83
  Ka  Ka1     eve 15,63
  Ka  Ka15    mor 14,54
  Ka  Ka15    eve 15,09
  La  La1     mor 11,3
  La  La1     eve 11,94
  </code></pre>