dosresmeta (version 2.0.1)

dosresmeta.control: Ancillary Parameters for Controlling the Fit in dosresmeta Models

Description

This internal function sets the parameter options used for fitting dose-response meta-analytical models, commonly to pre-specified default values. It is usually internally called by dosresmeta.fit.

Usage

dosresmeta.control(optim = list(), showiter = FALSE, maxiter = 1000,
  initPsi = NULL, igls.iter = 10, gr = FALSE,
  reltol = sqrt(.Machine$double.eps),
  set.negeigen = sqrt(.Machine$double.eps))

Value

A list with components named as the arguments.

Arguments

optim

list of parameters passed to the control argument of the function optim, which performs the quasi-Newton optimization in likelihood-based random-effects models. See optim.

showiter

logical. If TRUE, the progress of iterative optimization is shown.

maxiter

positive interger value. Maximum number of iterations in methods involving optimization procedures.

initPsi

either a matrix or a vector of its lower triangular elements (with diagonal, taken by column) from which starting values of the parameters of the between-study (co)variance matrix are derived, used in the optimization procedure for likelihood-based random-effects models. If NULL (the default, and recommended), the starting value is created internally through an iterative generalized least square algorithm.

igls.iter

number of iteration of the iterative generalized least square algorithm to be run in the hybrid optimization procedure of linkelihood-based models to provide the starting value.

gr

indicates if the gradient of the (re)ml likelihood should be provided. FALSE by default.

reltol

relative convergence tolerance in methods involving optimization procedures. The algorithm stops if it is unable to reduce the value by a factor of \(reltol * (abs(val) + reltol)\) at a step.

set.negeigen

positive value. Value to which negative eigenvalues are to be set in estimators where such method is used to force positive semi-definiteness of the estimated between-study (co)variance matrix.

Author

Alessio Crippa,

References

Gasparrini, A., Armstrong, B., Kenward, M. G. (2012). Multivariate meta-analysis for non-linear and other multi-parameter associations. Statistics in Medicine, 31(29), 3821-3839.

See Also

dosresmeta, dosresmeta-package, mvmeta.control

Examples

## Loading data
data("alcohol_cvd")

## print the iterations (see ?optim) and change the default for starting values
dosresmeta(formula = logrr ~ dose, type = type, id = id, se = se, 
           cases = cases, n = n, data = alcohol_cvd, proc = "1stage",
           control = list(showiter = TRUE, igls.iter = 20))