Random slope with cross-level interaction
? Assuming that fertilizer is a numeric covariate and wheatlanduse is categorical, you might want lmer( Production ~ seed + fertilizer *wheatlanduse + (1 + fertilizer | Household) , contrasts=list(wheatlanduse=contr.sum), ...) ? that would mean that the main effect for fertilizer would represent the *average* effect across levels of wheatlanduse.? The estimated main effect of wheatlanduse will represent the expected differences across levels at zero fertilizer (or, if you center fertilizer by subtracting the mean, at the average fertilizer level) ?? I'm not sure what you mean by "cross-level interaction" ...
On 7/19/20 12:59 PM, Yashree Mehta wrote:
Hi Salahadin, Thanks for your reply. It is very helpful. Then, is there a way I can extract the coefficient estimate of the fixed effect of fertilizer as well as that of wheatlanduse as a main effect? Regards, Yashree On Sun, Jul 19, 2020 at 6:59 PM Yashree Mehta <yashree19 at gmail.com> wrote:
Hi Salahadin, Thanks for your reply. It is very helpful. Then, is there a way I can extract the coefficient estimate of the fixed effect of fertilizer as well as that of wheatlanduse as a main effect? Regards, Yashree On Sun, Jul 19, 2020 at 5:46 PM Salahadin Lotfi <salahadin.lotfi at gmail.com> wrote:
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 [[alternative HTML version deleted]] _______________________________________________ R-sig-mixed-models at r-project.org mailing list
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