Published:
This post simulates a dataset where task performance increases depend on a continuous variable. I simulate the dataset, fit a GLMM, and plot the continuous x continous interaction from the model with CI. Read on here.
Published:
This is the first in a planned series of r-markdown explorations of logistic models, intended for bachelors or masters students. It covers the basics of the relationship between probability and log odds, basic data simulation, running and interpreting a logistic GLM, and plotting model predictions. Read on here. You’ll have to download and knit the Rmd file to view any of the latex equations properly (sorry!!!).
Published:
This post simulates a dataset where task performance increases depend on a continuous variable. I simulate the dataset, fit a GLMM, and plot the continuous x continous interaction from the model with CI. Read on here.
Published:
This is the first in a planned series of r-markdown explorations of logistic models, intended for bachelors or masters students. It covers the basics of the relationship between probability and log odds, basic data simulation, running and interpreting a logistic GLM, and plotting model predictions. Read on here. You’ll have to download and knit the Rmd file to view any of the latex equations properly (sorry!!!).
Published:
This post simulates a dataset where task performance increases depend on a continuous variable. I simulate the dataset, fit a GLMM, and plot the continuous x continous interaction from the model with CI. Read on here.
Published:
This is the first in a planned series of r-markdown explorations of logistic models, intended for bachelors or masters students. It covers the basics of the relationship between probability and log odds, basic data simulation, running and interpreting a logistic GLM, and plotting model predictions. Read on here. You’ll have to download and knit the Rmd file to view any of the latex equations properly (sorry!!!).