Master Estimation Function — estimation • mars

The primary estimation function for conducting the optimization. The function is typically called through the mars function, but can be called here directly.

estimation(
  formula = NULL,
  effect_name = NULL,
  studyID = NULL,
  effectID = NULL,
  variance = NULL,
  data,
  estimation_method = "REML",
  optim_method = "L-BFGS-B",
  structure = "UN",
  varcov_type,
  weights = NULL,
  intercept = FALSE,
  N = NULL,
  missing = "remove",
  robustID = NULL,
  multivariate_covs = NULL,
  tol = 1e-10,
  ...
)

Arguments

formula: The formula used for specifying the fixed and random structure. Used for univariate and multilevel structures.
effect_name: Character string representing the name of the effect size column in the data.
studyID: Character string representing the study ID
effectID: Character string representing the effect size ID
variance: Character string representing the name of the variance of the effect size in the data.
data: Data used for analysis
estimation_method: Type of estimation used, either "REML" or "MLE", REML is the default
optim_method: Optimization method that is passed to the optim function. Default is 'L-BFGS-B'.
structure: Between studies covariance structure, default is "UN" or unstructured. See details for more specifics.
varcov_type: Type of variance covariance matrix computed. Default is 'cor_weighted' for correlations or 'smd_outcome' for standardized mean differences.
weights: User specified matrix of weights.
intercept: Whether a model intercept should be specified, default is FALSE meaning no intercept. See details for more information.
N: Character string representing the sample size of the studies.
missing: What to do with missing data, default is 'remove'
robustID: A character vector specifying the cluster group to use for computing the robust standard errors.
multivariate_covs: A one-sided formula to specify the covariates used in a multivariate analysis.
tol: Tolerance for estimating, passed to optim
...: Additional arguments to pass to optim.

Value

Output is a named list; The output returns the estimated parameters, fit statistics, estimation inputs.