Version 3.37 of the survey package is on CRAN now.
svyquantilenow takes account of design degrees of freedom in computing confidence intervals and in turning confidence intervals into standard error estimates. This means results will change (slightly, and for the better).
svyivregfor two-stage least squares with instrumental variables. (described here)
withPVfor ‘plausible value’ analyses now supports replicate-weight designs. ‘Plausible values’ are how education people describe multiple imputation. The difference between this and the functions based on the
mitoolspackage is that
withPVworks with multiple columns in the same data frame (having, obviously, different names for a given variable in each imputed set) but
with.svyimputationListworks with multiple complete data frames (having the same name for a given variable in each imputed set). The basic
withPVideas are described here
svrepdesignhas specific options
type="JK2for JK2 replicate weights (used by the California Health Interview Survey) and
type="ACS"for the replicate weights in the American Community Survey1
svrepdesignis now much more likely to give warnings if you unnecessarily specify the
rscales=arguments when it could have worked them out itself – because you might have got it wrong.
You can’t use
RODBC database connections as data tables any more. Instead, you can use the
odbc package, which follows the R-DBI interface.
Things that are still on the to-do list
- Make all the functions produce influence functions so that
svybycan compare arbitrary statistics between groups without needed replicate weights. This isn’t especially hard, but it’s a lot of changes that need to be got right.
- Linear mixed models: I have two students working on improvements to the
svylmepackage. It might end up as part of
surveyafter that. Or not.
- Nonlinear least squares. If I get motivated, or if the people who complained about its non-existence on Stack Overflow actually ask for it.
and a synonym
type="successive-difference"for the ACS approach to computing weights (because it would be confusing to call it
type="ACS"if it were actually, for example, a Central Asian survey of horse breeds)↩