mixed-models

问题 I am analysing some whale tourism data and am trying to construct linear mixed effect models in the nlme package to see if any of my explanatory variables affect encounter time between whales and tourists. (I am also open to running this model in lme4 .) My variables are: mins : encounter time (response variable) Id : individual whale ID (random effect) Vessel : vessel Id (random effect) Sex : sex of the animal Length : length of the animal Year Month (nested within Year ). So my random

问题 dput for data, copy from https://pastebin.com/1f7VuBkx (too large to include here) data.frame': 972 obs. of 7 variables: $ data_mTBS : num 20.3 22.7 0 47.8 58.7 ... $ data_tooth: num 1 1 1 1 1 1 1 1 1 1 ... $ Adhesive : Factor w/ 4 levels "C-SE2","C-UBq",..: 2 2 2 2 2 2 2 2 2 2 ... $ Approach : Factor w/ 2 levels "ER","SE": 1 1 1 1 1 1 1 1 1 1 ... $ Aging : Factor w/ 2 levels "1w","6m": 1 1 1 1 1 1 2 2 2 2 ... $ data_name : Factor w/ 40 levels "C-SE2-1","C-SE2-10",..: 11 11 11 11 11 11 11 11

来源： https://stackoverflow.com/questions/61000913/close-connections-to-julia-from-under-r

来源： https://stackoverflow.com/questions/61000913/close-connections-to-julia-from-under-r

来源： https://stackoverflow.com/questions/49351201/fixed-effects-regression-constant-intercept-using-lfe-felm-in-r

来源： https://stackoverflow.com/questions/57527535/how-to-add-multiple-random-effects-python-statsmodel

来源： https://stackoverflow.com/questions/57527535/how-to-add-multiple-random-effects-python-statsmodel

来源： https://stackoverflow.com/questions/63360751/specifying-random-effects-for-repeated-measures-in-logistic-mixed-model-in-r-lm

来源： https://stackoverflow.com/questions/63360751/specifying-random-effects-for-repeated-measures-in-logistic-mixed-model-in-r-lm

问题 I'm not sure this is possible, but I'm wondering if you can remove some of the not-as-interesting plots from the plot(allEffects(model)) output. I assume this is possible by editing some of the background mechanics that R uses to make the array of graphs. I've already used multiline to reduce the number of graphs from 20, but I'm only interested in 2 of 10 of my remaining plots because it most accurately represents one of my interaction effects from my model (generalized linear mixed model).