extract_model_components {ssmodels} | R Documentation |
Extract Model Components for Selection Models
Description
This internal utility function extracts key components—such as model frames, matrices,
and response variables—from formulas and a data set. It is used by models like
HeckmanCL
, HeckmanGe
, HeckmanSK
, HeckmanBS
, and HeckmantS
.
Additionally, it can handle covariate matrices for modeling dispersion (sigma
) and
correlation (rho
) structures.
Usage
extract_model_components(
selection,
outcome,
data,
outcomeS = NULL,
outcomeC = NULL,
drop.levels = TRUE
)
Arguments
selection |
A formula for the selection equation. |
outcome |
A formula for the outcome equation. |
data |
A data frame containing all variables. |
outcomeS |
Optional formula or matrix for the dispersion model ( |
outcomeC |
Optional formula or matrix for the correlation model ( |
drop.levels |
Logical. If |
Details
If provided, outcomeS
and outcomeC
can be formulas or matrices for modeling
dispersion and correlation structures, respectively. The function ensures that the
selection equation response is binary.
Value
A list with the following components:
XS
Model matrix for the selection equation.
YS
Response vector for the selection equation.
NXS
Number of covariates in the selection model.
XO
Model matrix for the outcome equation.
YO
Response vector for the outcome equation.
NXO
Number of covariates in the outcome model.
Msigma
Matrix for the dispersion model (or
NULL
if not provided).NE
Number of covariates for the dispersion model (0 if not provided).
Mrho
Matrix for the correlation model (or
NULL
if not provided).NV
Number of covariates for the correlation model (0 if not provided).
YSLevels
Factor levels of the binary selection response.