cv_loglik: Performs cross-validation to calculate the average predicted...

In sarahlotspeich/logreg2ph_R_only: Implements Sieve Maximum Likelihood Estimation (SMLE) Approach for Two-Phase Logistic Regression

Performs cross-validation to calculate the average predicted log likelihood for the logreg2ph method. This function can be used to select the B-spline basis that yields the largest average predicted log likelihood.

Description

Performs cross-validation to calculate the average predicted log likelihood for the logreg2ph method. This function can be used to select the B-spline basis that yields the largest average predicted log likelihood.

Usage

cv_loglik(
  seed = 1,
  interp = TRUE,
  nfolds = 5,
  Y_unval = NULL,
  Y_val = NULL,
  X_unval = NULL,
  X_val = NULL,
  C = NULL,
  Validated = NULL,
  Bspline = NULL,
  data,
  theta_pred = NULL,
  gamma_pred = NULL,
  TOL = 1e-04,
  MAX_ITER = 1000
)

Arguments

seed	(For reproducibility in assigning the folds) an integer to specify the random number generator.
interp	Indicator of whether the B-spline coefficients in the testing data should be linearly interpolated from the training data. Defaults to TRUE.
nfolds	Specifies the number of cross-validation folds. The default value is 5. Although nfolds can be as large as the sample size (leave-one-out cross-validation), it is not recommended for large datasets. The smallest value allowable is 3.
Y_unval	Column name with the unvalidated outcome. If Y_unval is null, the outcome is assumed to be error-free.
Y_val	Column name with the validated outcome.
X_unval	Column name(s) with the unvalidated predictors. If X_unval and X_val are null, all precictors are assumed to be error-free.
X_val	Column name(s) with the validated predictors. If X_unval and X_val are null, all precictors are assumed to be error-free.
C	(Optional) Column name(s) with additional error-free covariates.
Validated	Column name with the validation indicator. The validation indicator can be defined as Validated = 1 or TRUE if the subject was validated and Validated = 0 or FALSE otherwise.
Bspline	Vector of column names containing the B-spline basis functions.
data	A dataframe with one row per subject containing columns: Y_unval, Y_val, X_unval, X_val, C, Validated, and Bspline.
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.
TOL	Tolerance between iterations in the EM algorithm used to define convergence. Defaults to 1E-4.
MAX_ITER	Maximum number of iterations allowed in the EM algorithm. Defaults to 1000.

Value

avg_pred_loglike	Stores the average predicted log likelihood.
pred_loglike	Stores the predicted log likelihoood in each fold.
converged	Stores the convergence status of the EM algorithm in each run.

sarahlotspeich/logreg2ph_R_only documentation built on Jan. 20, 2025, 6:20 p.m.