Hello,

I'm posting this to receive some comments/hints about a rather statistical than R-technical question ... .

In an anova of a lme factor SSPos11 shows up non-significant, but in the t-test of the summay 2 of the 4 levels (one for constrast) are significant. See below for some truncated output.

I realize that the two test are different (F-test/t-test), but I'm looking for for a "meaning". Maye you have a schenario that explains how these differences can be created and how you'd go ahead and analyse it further.

When I use SSPos11 as te only fixed effect, it does it is not significant in either anova nor t-test, and a boxplot of the factor shows that the levels are all quite similar (similar variance and mean). Might the effect I observe be linked to an unbalance design in the multifactorial model?

	thanks a lot for your help,
	+kind regards,

	Arne

> anova(fit)
             numDF denDF  F-value p-value
(Intercept)      1   540 323.4442  <.0001
SSPos1           3   540  15.1206  <.0001
...
SSPos11          3   540   1.1902  0.3128
...

> summary(fit)
Linear mixed-effects model fit by REML
 Data: d.orig 
       AIC      BIC    logLik
  1007.066 1153.168 -469.5329

Random effects:
 Formula: ~1 | Method
        (Intercept)  Residual
StdDev:   0.4000478 0.4943817

Fixed effects: log(value + 7.5) ~ SSPos1 + SSPos2 + SSPos6 + SSPos7 + SSPos10 + SSPos11 + SSPos13 + SSPos14 + SSPos18 + SSPos19 +      
                  Value  Std.Error  DF   t-value p-value
(Intercept)   2.8621811 0.23125065 540 12.376964  0.0000
SSPos1C      -0.1647937 0.06293993 540 -2.618269  0.0091
SSPos1G      -0.3448095 0.05922479 540 -5.822047  0.0000
SSPos1T       0.1083988 0.06087095 540  1.780797  0.0755
...
SSPos11C     -0.1540292 0.06171635 540 -2.495761  0.0129
SSPos11G     -0.1428980 0.05993122 540 -2.384368  0.0175
SSPos11T     -0.0039434 0.06133920 540 -0.064289  0.9488
...


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