[R-sig-ME] Crossing Interaction and lmer
Johannes Schliesser
J.Schliesser at uu.nl
Wed Oct 21 11:50:44 CEST 2009
Dear mixed model experts
I have troubles with a wired outcome with lmer().
I was testing effects on reaction times for two fixed factors, Identity
(levels identical "id" and non-identical ("ni") and Bonus Size ("h"igh and
"l"ow). Subjects "subj" and "items" were Random Effects. In fact, Bonus Size
is nested within Items, as half of the Items were of high, the other half of
low Bonus size.
The results indicate a strong crossing interaction:
| h | l | ALL |
|id |839. |861 | 850 |
|ni |879 |829 | 854 |
|ALL| 859 |845 |852 |
Subjects tend to be about 40 ms faster for identical than for non-identical in
the high bonus group, but about 30 ms slower for identical than for non-
identical in the low bonus group. Grand means for identical and non-identical
items differ only for 4 ms.
So far so good.
Classic ANOVA rejects all main effects but confirmes the interaction.
The lmer analysis instead suggests a fixed effect for identity:
----------
lmer.rtNA2 = lmer(rtNA~id*bonus+(1|subj)+(1|bonus/item), data = x4)
lmer.rtNA
Linear mixed model fit by REML
Formula: rtNA ~ id * bonus + (1 | subj) + (1 | item)
Data: x4
AIC BIC logLik deviance REMLdev
24346 24385 -12166 24360 24332
Random effects:
Groups Name Variance Std.Dev.
item (Intercept) 1926.9 43.896
subj (Intercept) 9648.6 98.227
Residual 19026.7 137.937
Number of obs: 1905, groups: item, 80; subj, 24
Fixed effects:
Estimate Std. Error t value
(Intercept) 839.804 22.132 37.95
idni 40.264 8.942 4.50
bonusl 22.841 13.278 1.72
idni:bonusl -73.346 12.644 -5.80
Correlation of Fixed Effects:
(Intr) idni bonusl
idni -0.202
bonusl -0.300 0.336
idni:bonusl 0.143 -0.707 -0.476
-----------------------------------
The lmer model seems to test Identical vs. Non-Identical for the High-Bonus
group only, but not overall (same as estimates for Bonus Size only in the "id"
row). pvals.fnc() asssigns significance for Identity and the interaction
Identity*Bonus Size.
I have the impression that this is missleading: we certainly cannot speak of
slower reaction times for non-identical stimuli than for identical.
Leaving out the Bonus Size as a fixed factor "lmer(rt~id+(1|subj)+(1|item),
data = x4)" gives a realistic t-value below 1 for Identity.
So, I ask:
Is the missleading handling of crossing interactions a bug ?
Or do I simply have to know that if there is a huge crossing interaction I
should not generalize the Fixed Factor effects ?
And more relevant: How do I get an analysis that is appropriate to the data ?
Thanks for your help
Johannes
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