plot_dgirt()has been replaced by argument
group_name, which takes the name of a single grouping variable. This is a quick workaround for compatibility with breaking changes in ggplot2 3.0.0.
shape()when 1) at least two
group_namesare specified in an order other than alphabetic and 2) geographic
aggregate_dataindicating zero trials. (They don’t represent item responses.) Preserving them has the effect that unobserved groups, defined partially or entirely by the values of the grouping variables in zero-trial rows in
aggregate_data, can be included in a model.
aggregate_datais used without
item_data, 2) no demographic groups are specified via
group_names, and 3) geographic
modifier_datamust cover all combinations of the geo and time variables in the item response data (individual or aggregated), but because of a bug in the validation of the geographic data, this requirement was not always enforced. In some cases a warning would appear instead of an error.
shape()now accepts aggregated item response data unaccompanied by individual-level item response data. The
item_namesarguments are no longer required.
shape()for trimming raked weights. Note that trimming occurs before raked weights are rescaled to have mean 1, and the rescaled weights can be larger than
dgmrp()taking for reuse a previously compiled Stan model, as found in the
@stanmodelslot of a
dgmrp()can be used to specify arbitrary
.stanfiles on the disk in addition to those included with the package.
get_item_n()methods properly accepts a vector of variable names when combined with
dgmrp()for fitting single-issue MRP models with hierarchical covariates
dgmrp_fitfor models fitted with
dgmrp(), inheriting from a new virtual class
dgirt()now returns a
dgirt_fit-class object that also inherits from
group_nameschange in 0.2.5
Error in .doLoadActions(where, attach))
group_namesis no longer required. If omitted, the geographic variable given by
geo_namewill define groups.
aggregate_item_namesis no longer required. It defaults to the observed values of the
strata_names. It takes a formula or list of formulas and allows more complicated preweighting.
shape()specifies variables to be kept in
aggregate_datamay include geographic areas, demographics, or time periods that don’t appear in
plot_rhats()for model checking.
get_time_elapsedgives model run times. These also appear in