impute_covariance_matrix() and pattern_covariance_matrix().impute_covariance_matrix() and pattern_covariance_matrix(), because they have been superseded by metafor::vcalc().linear_contrast() to handle specified contrasts that are scalars when variance-covariance matrix is computed with a working model that is not inverse-variance.packageVersion() in R-devel.geepack::geeglm() models.rma.ls models (location-scale models estimated using metafor::rma.uni(scale = )).Wald_test() when vcov of contrasts is not positive definite.linear_contrast() to handle specified contrasts that are scalars.get_data function for gls and lme objects to allow use of expressions in addition to object names.ivreg::ivreg objects when estimated by ordinary least squares (support for objects estimated by 2SM and 2SMM is not yet implemented).plm::plm() when method = "FD" to account for bug fixes in version 2.6-2 of plm.plm objects estimated by random effects, which occurred when a user-specified clustering variable was at a higher level than the random effects.plm objects with nested random effects (effects = "nested").plm objects. See ?plm.Wald_test() labeled results when test = "Naive-Fp".New function linear_contrast() calculates robust confidence intervals and p-values for linear contrasts of regression coefficients from a fitted model. Works with constrain_pairwise() and other constrain_*() helper functions.
Corrected precision of unit test leading to error on M1mac.
Wald_test() gains an option for test = "Naive-Fp", which uses denominator degrees of freedom equal to the number of clusters minus the number of coefficients in the fitted model.coef_test() and conf_int() gain an option for test = "naive-tp", which uses denominator degrees of freedom equal to the number of clusters minus the number of coefficients in the fitted model.Corrected a bug in the Satterthwaite degrees of freedom calculations for models that include only an intercept.
Output of coef_test() and conf_int() now include a variable containing the coefficient names, so that the results are "tidy."
conf_int() now includes an option to report a p-value for each coefficient.
coef_test() now reports degrees of freedom for test = 'z' and test = 'naive-t'.
vcovCR() now provides a more informative error message when the clustering variable is a constant.
vcovCR() now handles models estimated using analytic weights, where some weights are equal to zero. Results are consistent with omitting observations with weights of zero.
Added more informative error messages for Wald_test() and conf_int(), triggered if the test argument does not match any of the available tests.
Corrected a bug in findCluster.rma.mv(), which threw an error if a random effects factor in the rma.mv model had unobserved levels.
Corrected a bug in Wald_test(), which threw an error for tests of intercept-only models.
Fixed a minor bug in print method for Wald_test() results, which threw an error when the p-value was NA.
New functionality for impute_covariance_matrix():
New function pattern_covariance_matrix(), which creates a covariance matrix based on a specified pattern of correlations between different categories of effects.
rma.mv objects, which previously led to incorrect identification of clustering variables in models with multiple levels of random effects, where at least one set of random effects has inner | outer structure.Wald_test() now uses new helper functions constrain_zero(), constrain_equal(), and constrain_pairwise() to specify constraint matrices.
Wald_test() gains an argument tidy. When TRUE, results for a list of tests will be tidied into a single data.frame.
Output of Wald_test() now includes both numerator and denominator degrees of freedom.
Corrected bug in methods for plm objects, which occurred when "within" models included cluster-level interactions. Previously main effects of cluster-level variables were not getting dropped from model_matrix.plm().
Corrected bugs in methods for robu objects
constrain_equal() and constrain_zero() when called on robu objects.Added methods for lmerMod objects fitted by lme4::lmer().
Updated internals to use inherits() instead of checking class() directly.
Added t statistics to output of coef_test().
Fixed a bug in get_index_order(), an internal function used with plm objects. Previously, the function assumed that both individual and time indices were specified in the plm call. The new function works even when zero or one indices are specified.
impute_covariance_matrix() now drops unobserved factor levels.
updated method for handling residuals from rma.uni and rma.mv objects, for consistency with metafor 2.1-0.
Added conf_int() to provide easy cluster-robust confidence intervals.
Added examples to documentation for conf_int() and coef_test().
Added coefs option to coef_test() to allow testing of subsets of coefficients.
Updated tests to use carData instead of car package.
Added methods for ivreg objects.
Added methods for mlm objects.
Updated residuals_CS.plm to account for changes in plm 1.6-6.
Added methods for glm objects.
Provide facility to cluster at higher level than highest random effects for lme and gls objects.
Added impute_covariance_matrix() utility function for multivariate meta-analysis.
Updated methods for plm objects to account for changes in plm 1.6-6.
Added documentation of type options in vcovCR().
Added examples for all vcovCR() methods.
Added bread() methods for all supported model classes.
vcovCR() is now calculated using bread(), and carries attributes for bread, est_mat, and adjustment matrices.
vcovCR() gains a form argument to obtain just the meat of the sandwich, or to use a user-specified bread matrix.
Refactored internal functions for degrees of freedom calculation to improve speed and memory usage.
Bug fixes:
nobs.plm() method to handle first-differenced models