comparing 3 levels of fixed factor in lme4
Thank you John Maindonald. For more than 2 levels of the experimental condition, I learned that usually we find an F to test mean differences across the levels of the condition. In lme4, the model summary reports a t value, and I am replicating a study that uses lme4 to compare 3 levels of a fixed factor. My advising professor has told me that the t value can only be used to compare 2 means. Andrew Obermeier
On Jul 30, 2012, at 8:00 PM, John Maindonald <john.maindonald at anu.edu.au> wrote:
Perhaps Andrew has vaguely at the back of his mind the notion that for comparing >2 means, one should be using a multiple range test or an anova test, at all events if the aim is to achieve an experiment-wise 5% level. Tests based on the individual t-statistics are not independent. This is of course a somewhat controversial area. John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax : +61 2(6125)5549 Centre for Mathematics & Its Applications, Room 1194, John Dedman Mathematical Sciences Building (Building 27) Australian National University, Canberra ACT 0200. http://www.maths.anu.edu.au/~johnm On 30/07/2012, at 8:38 PM, peter dalgaard wrote:
On Jul 30, 2012, at 08:04 , Obermeier Andrew wrote:
In lme4, in models with 3 levels of the fixed factor, each of these gets a t value comparing it to a reference level. How is this done? It is my understanding that the t value can only be used to compare 2 means.
Then your understanding is wrong, and you need to read a text on basic linear modelling theory. Nothing specifically mixed-model or even R relevant about that. -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
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