Fit Multivariate Meta-Analysis

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,
  beta0_values = NULL,
  beta0_free = NULL,
  beta0_lbound = NULL,
  beta0_ubound = NULL,
  beta1_values = NULL,
  beta1_free = NULL,
  beta1_lbound = NULL,
  beta1_ubound = NULL,
  tau_values = NULL,
  tau_free = NULL,
  tau_lbound = NULL,
  tau_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.

beta0_values

Numeric vector. Optional vector of starting values for beta0.

beta0_free

Logical vector. Optional vector of free (TRUE) parameters for beta0.

beta0_lbound

Numeric vector. Optional vector of lower bound values for beta0.

beta0_ubound

Numeric vector. Optional vector of upper bound values for beta0.

beta1_values

Numeric matrix. Optional matrix of starting values for beta1.

beta1_free

Logical matrix. Optional matrix of free (TRUE) parameters for beta1.

beta1_lbound

Numeric matrix. Optional matrix of lower bound values for beta1.

beta1_ubound

Numeric matrix. Optional matrix of upper bound values for beta1.

tau_values

Numeric matrix. Optional matrix of starting values for t(chol(tau_sqr)).

tau_free

Numeric matrix. Optional matrix of free (TRUE) parameters for t(chol(tau_sqr)).

tau_lbound

Numeric matrix. Optional matrix of lower bound values for t(chol(tau_sqr)).

tau_ubound

Numeric matrix. Optional matrix of upper bound values for t(chol(tau_sqr)).

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 optional arguments to pass to mxTryHardctsem.

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