Prediction function for an exposure-response model

Usage

erglm_fun(object)

Arguments

object: An erglm model, as returned by erglm_model()

Value

A function with arguments param, data, and type.

The param argument should be a vector of coefficients; defaults to coef(object) (the fitted coefficients) if not supplied.
The data argument should be a data frame or tibble; defaults to object$data (the data the model was fitted to) if not supplied.
The type argument should be a string indicating the type of prediction to generate (defaults to "response")

Takes a fitted glm object as input and returns a function that will evaluate the underlying structural model with user-specified parameters or data (e.g., for VPCs or other counterfactual simulation scenarios). Uses stats::family(object)$linkinv, so this works for any glm() family, not just binomial/logistic models; tested for binomial, poisson, gaussian, and Gamma families. Named erglm_fun() for consistency with the companion emaxnls package's emax_fun(), which serves the same purpose for emaxnls/emaxlogistic models.

Examples

mod1 <- erglm_model(ae2 ~ aucss + sex, erglm_data, family = binomial())
mod1_fun <- erglm_fun(mod1)

# no arguments: reproduces the fitted model's own predictions
p1 <- mod1_fun()
p2 <- unname(predict(mod1, type = "response")) # same result

# user modifies the data set
erglm_data2 <- erglm_data[1:20, ]
p3 <- mod1_fun(data = erglm_data2) 
p4 <- unname(predict(mod1, newdata = erglm_data2, type = "response")) # same result

# user modifies the parameters
par2 <- coef(mod1)
int1 <- par2["(Intercept)"]
par2["(Intercept)"] <- 0
p5 <- mod1_fun(param = par2)