observed_data_loglik: Observed-data log-likelihood

In sarahlotspeich/logreg2ph: Implements Sieve Maximum Likelihood Estimation (SMLE) Approach for Two-Phase Logistic Regression

Observed-data log-likelihood

Description

This function returns the value of the observed-data log-likelihood (equation (2) in Lotspeich et al. (2020)) for a given dataset and parameter values theta, gamma, and p.

Usage

observed_data_loglik(
  N,
  n,
  Y_unval = NULL,
  Y_val = NULL,
  X_unval = NULL,
  X_val = NULL,
  C = NULL,
  Bspline = NULL,
  comp_dat_all,
  theta_pred,
  gamma_pred,
  theta,
  gamma,
  p
)

Arguments

N	Phase I sample size
n	Phase II sample size
Y_unval	Column with the unvalidated outcome (can be name or numeric index)
Y_val	Column with the validated outcome (can be name or numeric index)
X_unval	Column(s) with the unvalidated predictors (can be name or numeric index)
X_val	Column(s) with the validated predictors (can be name or numeric index)
C	(Optional) Column(s) with additional error-free covariates (can be name or numeric index)
Bspline	Vector of columns containing the B-spline basis functions (can be name or numeric index)
comp_dat_all	Augmented dataset containing rows for each combination of unvalidated subjects' data with values from Phase II (a matrix)
theta_pred	Vector of columns in data that pertain to the predictors in the analysis model.
gamma_pred	Vector of columns in data that pertain to the predictors in the outcome error model.
theta	Parameters for the analysis model (a column vector)
gamma	Parameters for the outcome error model (a column vector)
p	B-spline coefficients for the approximated covariate error model (a matrix)

Value

Scalar value of the function

sarahlotspeich/logreg2ph documentation built on July 24, 2022, 6:34 p.m.