Answer by Stefan for The statistical model equivalent of this R formula
There is a cool package mentioned in the GLMM FAQs called equatiomatic.Reproducible example:remotes::install_github("datalorax/equatiomatic")#> Skipping install of 'equatiomatic' from a github...
View ArticleAnswer by Ben Bolker for The statistical model equivalent of this R formula
Depending on the venue, you might want to do this:set up any old linear model (needn't be quasibinomial) with the right formulause equatiomatic::extract_eq() to get the (horrible) LaTeX code for the...
View ArticleAnswer by R Carnell for The statistical model equivalent of this R formula
glm(formula = prop ~ A * B * C * D , family = quasibinomial, data = data, weights = w)Assume that $A,B,C,D$ are binomial variables with a base case at 0 and alternate at 1.$$logit(prop) =...
View ArticleThe statistical model equivalent of this R formula
This is how my model is written in R:glm(formula = prop ~ A * B * C * D , family = quasibinomial, data = data, weights = w)This is a quasibinomial generalized linear model used on the logit scale...
View ArticleAnswer by Stefan for The statistical model equivalent to this R formula
There is a cool package mentioned in the GLMM FAQs called equatiomatic.Reproducible example:remotes::install_github("datalorax/equatiomatic")#> Skipping install of 'equatiomatic' from a github...
View ArticleAnswer by Ben Bolker for The statistical model equivalent to this R formula
Depending on the venue, you might want to do this:set up any old linear model (needn't be quasibinomial) with the right formulause equatiomatic::extract_eq() to get the (horrible) LaTeX code for the...
View ArticleAnswer by R Carnell for The statistical model equivalent to this R formula
glm(formula = prop ~ A * B * C * D , family = quasibinomial, data = data, weights = w)Assume that $A,B,C,D$ are binomial variables with a base case at 0 and alternate at 1.$$logit(prop) =...
View ArticleThe statistical model equivalent to this R formula
This is how my model is written in R:glm(formula = prop ~ A * B * C * D , family = quasibinomial, data = data, weights = w)This is a quasibinomial generalized linear model used on the logit scale...
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