dosresmeta.control function

Ancillary Parameters for Controlling the Fit in dosresmeta Models

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.

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))

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.

Returns

A list with components named as the arguments.

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))

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

Author(s)

Alessio Crippa, alessio.crippa@ki.se