gdfa_nonconstant: Gamma Discriminant Function Approach for Estimating Odds...

In vandomed/meuc: Measurement Error and Unmeasured Confounding

Description

See gdfa.

Usage

gdfa_nonconstant(y, xtilde, c = NULL, merror = FALSE,
  integrate_tol = 1e-08, integrate_tol_hessian = integrate_tol,
  estimate_var = TRUE, fix_posdef = TRUE, ...)

Arguments

y	Numeric vector of Y values.
xtilde	Numeric vector (or list of numeric vectors, if there are replicates) of Xtilde values.
c	Numeric matrix with C values (if any), with one row for each subject. Can be a vector if there is only 1 covariate.
merror	Logical value for whether there is measurement error.
integrate_tol	Numeric value specifying the tol input to hcubature.
integrate_tol_hessian	Same as integrate_tol, but for use when estimating the Hessian matrix only. Sometimes more precise integration (i.e. smaller tolerance) helps prevent cases where the inverse Hessian is not positive definite.
estimate_var	Logical value for whether to return variance-covariance matrix for parameter estimates.
fix_posdef	Logical value for whether to repeatedly reduce integrate_tol_hessian by factor of 5 and re-estimate Hessian to try to avoid non-positive definite variance-covariance matrix.
...	Additional arguments to pass to nlminb.

Value

List containing:

1. Numeric vector of parameter estimates.

2. Variance-covariance matrix.

3. Returned nlminb object from maximizing the log-likelihood function.

4. Akaike information criterion (AIC).

References

Whitcomb, B.W., Perkins, N.J., Zhang, Z., Ye, A., and Lyles, R. H. (2012) "Assessment of skewed exposure in case-control studies with pooling." Stat. Med. 31: 2461–2472.

vandomed/meuc documentation built on May 12, 2019, 6:17 p.m.