Random slope with cross-level interaction
Hi Yashree, 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 always included. 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 | Household) Thanks, Sala ************* 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 at gmail.com> wrote:
Hi,
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,
Regards,
Yashree
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