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I have a data frame with this structure:

'data.frame':   39 obs. of  3 variables:
 $ topic   : Factor w/ 13 levels "Acido Folico",..: 1 2 3 4 5 6 7 8 9 10 ...
     $ variable: Factor w/ 3 levels "Both","Preconception",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ value   : int  14 1 36 17 5 9 19 9 19 25 ...

and i want to test the effect value ~ variable, considering that observation are grouped in topics. So I thought to use a repeated measure ANOVA, where "variable" is considered as a repeatead measure on every topic. the call is aov(value ~ variable + Error(topic/variable)).

My question is: if i want to do the same with lme how should I model the random effect?

~ 1 | topic/variable

or

~ variable | topic

the anova returns a significant F. for the lme, the first version gives a non significant effect, while the second is significant; so I suppose that the anova is more similar to the second.

Did I understood right?

Thanks

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