Dear All,
I am writing a paper on an ecological study and I am not really sure about the best way of presenting the statistical models.
Since the models proposed involve many covariates and interaction terms, I assume that a non-expert reader would be a bit confused by looking at a mathematical formula or just a paragraph explaining the predictors used. Following the indications from Zuur et al 2016 DOI: 10.1111/2041-210X.12577 I was thinking to use a mixed approach, and therefore include a small paragraph explaining my variables and a "simplified" mathematical explanation of the model.
Let's use a simple scenario (just to explain my idea): "In my study I measure the HEIGHT of many student (response variable) and I want to find a relationship with their AGE (dependant variable, continuous) and GENDER (dependant, fixed, categorical), but I also want to include the potential effect of their POST-CODE of origin (stupid example, just to use a random term)”.
(assuming that Gender is categorical with “j” levels, Post-Code with ”i” levels and I have “k” individuals)
So If in my model I have all the terms + interactions between gender and age, the mathematical formula would be :
Heightijk = αj + βj Ageik + Post-codei + εijk
εijk~N(0;σ2)
Post-codei ~N(0;σpost-code2) my random term
But I think this is not really “clear” at a first glance. So I was thinking to explain the model showing individual terms, interactions and random terms involved, excluding intercept and error (which are implied) such as
Heightijk = Ageik + Genderij + Ageik x Genderij + Post-codei
Post-codei ~N(0;σpost-code2)
This would be presented with a paragraph stating which the response and covariate involved are + the meaning of each subscript.
Would this be a clear way of presenting a model? Any advise would be much appreciated.
Thank you in advance for your help!