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Fit Multivariate Meta-Analysis

Source: R/metaVAR-meta.R
Meta.Rd

This function estimates fixed-, random-, or mixed-effects meta-analysis parameters using the estimated coefficients and sampling variance-covariance matrix from each individual.

Usage

Meta(
  y,
  v,
  x = NULL,
  alpha_values = NULL,
  alpha_free = NULL,
  alpha_lbound = NULL,
  alpha_ubound = NULL,
  gamma_values = NULL,
  gamma_free = NULL,
  gamma_lbound = NULL,
  gamma_ubound = NULL,
  tau_sqr_d_free = NULL,
  tau_sqr_d_values = NULL,
  tau_sqr_d_lbound = NULL,
  tau_sqr_d_ubound = NULL,
  tau_sqr_l_free = NULL,
  tau_sqr_l_values = NULL,
  tau_sqr_l_lbound = NULL,
  tau_sqr_l_ubound = NULL,
  random = TRUE,
  diag = FALSE,
  try = 1000,
  ncores = NULL,
  ...
)

Arguments

y

A list. Each element of the list is a numeric vector of estimated coefficients.

v

A list. Each element of the list is a sampling variance-covariance matrix of y.

x

An optional list. Each element of the list is a numeric vector of covariates for the mixed-effects model.

alpha_values

Numeric vector. Optional vector of starting values for alpha.

alpha_free

Logical vector. Optional vector of free (TRUE) parameters for alpha.

alpha_lbound

Numeric vector. Optional vector of lower bound values for alpha.

alpha_ubound

Numeric vector. Optional vector of upper bound values for alpha.

gamma_values

Numeric matrix. Optional matrix of starting values for gamma.

gamma_free

Logical matrix. Optional matrix of free (TRUE) parameters for gamma.

gamma_lbound

Numeric matrix. Optional matrix of lower bound values for gamma.

gamma_ubound

Numeric matrix. Optional matrix of upper bound values for gamma.

tau_sqr_d_free

Logical vector indicating free/fixed status of the elements of tau_sqr_d. If NULL, all element of tau_sqr_d are free.

tau_sqr_d_values

Numeric vector with starting values for tau_sqr_d. If NULL, defaults to a vector of ones.

tau_sqr_d_lbound

Numeric vector with lower bounds for tau_sqr_d. If NULL, no lower bounds are set.

tau_sqr_d_ubound

Numeric vector with upper bounds for tau_sqr_d. If NULL, no upper bounds are set.

tau_sqr_l_free

Logical matrix indicating which strictly-lower-triangular elements of tau_sqr_l are free. Ignored if diag = TRUE.

tau_sqr_l_values

Numeric matrix of starting values for the strictly-lower-triangular elements of tau_sqr_l. If NULL, defaults to a null matrix.

tau_sqr_l_lbound

Numeric matrix with lower bounds for tau_sqr_l. If NULL, no lower bounds are set.

tau_sqr_l_ubound

Numeric matrix with upper bounds for tau_sqr_l. If NULL, no upper bounds are set.

random

Logical. If random = TRUE, estimates random effects. If random = FALSE, tau_sqr is a null matrix.

diag

Logical. If diag = TRUE, tau_sqr is a diagonal matrix. If diag = FALSE, tau_sqr is a symmetric matrix.

try

Positive integer. Number of extra optimization tries.

ncores

Positive integer. Number of cores to use.

...

Additional arguments to pass to OpenMx::mxTryHard().

References

Cheung, M. W.-L. (2015). Meta-analysis: A structural equation modeling approach. Wiley. doi:10.1002/9781118957813

Neale, M. C., Hunter, M. D., Pritikin, J. N., Zahery, M., Brick, T. R., Kirkpatrick, R. M., Estabrook, R., Bates, T. C., Maes, H. H., & Boker, S. M. (2015). OpenMx 2.0: Extended structural equation and statistical modeling. Psychometrika, 81(2), 535–549. doi:10.1007/s11336-014-9435-8

See also

Other Meta-Analysis of VAR Functions: MetaVARMx()

Author

Ivan Jacob Agaloos Pesigan