This function fits a statistical model to the given dataset using a specified formula
based on the dependent (y) and independent (x and formula) variables.
After fitting, the model is passed to a dedicated output handler (thekids_model_output)
for further processing or customization. Supported model types include linear regression,
negative binomial regression, and quantile regression.
Arguments
- data
A data frame containing the variables to be used in the model.
- y
Character string specifying the name of the dependent variable.
- x
Character string specifying the name of the primary independent variable.
- formula
Optional character string specifying additional terms to include in the formula. If not provided, the formula will be auto-generated as
y ~ x.- model
Character string specifying the type of model to fit. Currently supported are
"linear","negbin", or"quantile".- ...
Additional arguments passed to the underlying modeling functions.
Value
Model output relating to the appropriate modeling function
(e.g., lm, glm.nb, or rq).
This is the same object returned by thekids_model_output if the latter is
called directly.
Details
This function validates the specified model type and constructs a formula based
on the supplied arguments. The data is reduced to complete cases for the
variables included in the formula before fitting the model. The fitted model
is passed to thekids_model_output for further handling, allowing
for streamlined customization of model outputs.
For a more thorough example, see the vignette.
Examples
# Example 1: Linear model
if (FALSE) { # \dontrun{
data(mtcars)
thekids_model(mtcars, y = "mpg", x = "wt", model = "linear")
} # }
# Example 2: Linear model with factor
if (FALSE) { # \dontrun{
thekids_model(mtcars %>% mutate(cyl = as.factor(cyl)), y = "mpg", x = "cyl", model = "linear")
} # }
# Example 3: Quantile regression
if (FALSE) { # \dontrun{
library(quantreg)
data(engel)
thekids_model(engel, y = "foodexp", x = "income", model = "quantile", tau = 0.5)
} # }