- The
group_names
argument toplot_dgirt()
has been replaced by argumentgroup_name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.
- Avoid an error during testing, on R built
--without-long-double
.
- Fix an issue introduced in v0.2.12 that led to an unexpected error in
shape()
when 1) at least twogroup_names
are specified in an order other than alphabetic and 2) geographicmodifier_data
is used.
- Allow modeling of unobserved groups using aggregated data. The previous
behavior was to drop rows in
aggregate_data
indicating 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 inaggregate_data
, can be included in a model. - Fix an unexpected error when 1)
aggregate_data
is used withoutitem_data
, 2) no demographic groups are specified viagroup_names
, and 3) geographicmodifier_data
is used. - Fix the check for missing
modifier_data
. Geographicmodifier_data
must 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.
- Add poststratification over posterior samples (closes #21).
shape()
now accepts aggregated item response data unaccompanied by individual-level item response data. Theitem_data
anditem_names
arguments are no longer required.- Add a
max_raked_weight
argument toshape()
for trimming raked weights. Note that trimming occurs before raked weights are rescaled to have mean 1, and the rescaled weights can be larger thanmax_raked_weight
. - Remove the unused function
expand_rownames()
. - Bugfixes.
- Remove Rcpp dependency by rewriting
dichotomize()
in R. - Avoid estimating models (using RStan) during tests, with the goal of rendering moot variation in build environments. This addresses a test failure during CRAN's r-release-osx-x86_64 build.
- Switch from compiling Stan models at install time to compiling them at runtime, avoiding an Rcpp module issue.
- Add
model
argument todgirt()
anddgmrp()
taking for reuse a previously compiled Stan model, as found in the@stanmodel
slot of adgirt_fit
- ordgmrp_fit
-class object. - The
version
argument todgirt()
anddgmrp()
can be used to specify arbitrary.stan
files on the disk in addition to those included with the package. - Argument
by
toget_n()
andget_item_n()
methods properly accepts a vector of variable names when combined withaggregate
arguments.
- Improve Stan models for shorter run times
- Add
dgmrp()
for fitting single-issue MRP models with hierarchical covariates - Add class
dgmrp_fit
for models fitted withdgmrp()
, inheriting from a new virtual classdgo_fit
dgirt()
now returns adgirt_fit
-class object that also inherits fromdgo_fit
class- Bugfixes
- Package renamed dgo: Dynamic Estimation of Group-level Opinion
- Tweaks to pass CRAN checks: clean up examples and docs
- Use roxygen2 for classes, methods, and
NAMESPACE
- Fix checks on
P
,S
related togroup_names
change in 0.2.5 - Fix Rcpp module issue from 0.2.6 (
Error in .doLoadActions(where, attach)
) - Export
expand_rownames()
- Fix error in
dgirt_plot
- Fix path in
tools/make_cpp.R
group_names
is no longer required. If omitted, the geographic variable given bygeo_name
will define groups.aggregate_item_names
is no longer required. It defaults to the observed values of theitem
column inaggregate_data
.raking
argument toshape()
replacesstrata_names
. It takes a formula or list of formulas and allows more complicated preweighting.id_vars
argument toshape()
specifies variables to be kept initem_data
.aggregate_data
may include geographic areas, demographics, or time periods that don't appear initem_data
.- Fix: use a smaller epsilon than the default in survey::rake() for convergence with non-frequency weights.
- New
dgirtfit
methodsrhats()
andplot_rhats()
for model checking. - New
dgirtfit
methodget_time_elapsed
gives model run times. These also appear insummary
output.