[R-sig-ME] Random slope with cross-level interaction
@@|@h@d|n@|ot|| @end|ng |rom gm@||@com
Sun Jul 19 17:45:49 CEST 2020
The interpretation of the interaction term do change whether you include
the main effect of not.
Usually having only the interaction term in the model requires a specific
hypothesis. Thus, the lower level terms (i.e., the main effects) are almost
The lmer function automatically includes the lower level terms even if you
just include an interaction term.
For example, if you setup your model as follow, the main effects of
fertilizer and wheatlanduse will be still taken into account.
Production = seed + fertilizer : wheatlanduse + (1 + fertilizer |
Salahadin (Sala) Lotfi
PhD Candidate of Cognitive Psychology & Neuroscience
University of Wisconsin-Milwaukee
Anxiety Disorders Laboratory
President, Association of Clinical and Cognitive Neuroscience, UWM
On Sun, Jul 19, 2020 at 5:02 AM Yashree Mehta <yashree19 using gmail.com> wrote:
> I have the following model:
> Production = seed + fertilizer + fertilizer : wheatlanduse + (1 +
> fertilizer | Household)
> As the formula indicates, the household level is specified as the random
> intercept. Fertilizer is specified as random slope , and has also been
> specified as a fixed effect.
> I am interested in cross-level interaction between fertilizer and the
> wheatlanduse variable. So, I have inserted "fertilizer : wheatlanduse".
> My question is: Do I have to include "wheatlanduse" as a main effect in the
> formula as well? Or is it acceptable to only have it as a part of the
> interaction term?
> Thank you,
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