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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