On Fri, 30 Sep 2011, Martin Batholdy wrote:
Hi,
I currently running regression models on an experimental dataset.
The model contains one independent continuous variable and two
independent experimental conditions (one with two factors, the other
with three factors) and several covariates.
Now I get different results for a covariate in this model when I run
aov(modell) vs. lm(modell).
In the ancova model, one of the covariates seems to explain a
significant amount of variance. But in the lm-statistics this
variable doesn't exceed the p-threshold of p = 0.05.
How can that be?
Apples and oranges? You haven't given us any reproducible code, but I
believe the what you looked at for lm (which does not of itself give
p-values) was equivalent to using drop1, whereas aov gives a
sequential ANOVA table.
I suspect the problem is a lack of statistical understanding, so this
question might better be asked (with an example) of your local
statistical advisor.
thanks for any advice on this!
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--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
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