- The Pstar data generated in
copulaCorrection
is improved with the corrections proposed by Qian, Koschmann, and Xie (2024).
- Fix CRAN notes regarding documentation
- Add CITATION file and references to forthcoming JSS publication
- Fix missing package alias
- Replace data set
dataCopDisCont
with a new one
- Fix tests due to changes in package dependencies
- Replace data sets with new ones
- Fix tidy HTML warnings in documentation and parsing of news.md reported in daily CRAN checks
- Fix broken correctness tests for
latentIV
on M1mac.
- Update maintainer email.
- Fix documentation to conform to HTML5.
- In method
multilevelIV
matrices could not be constructed if all groups were of the same size. Thanks to pinson06 for reporting.
- In the
copulaCorrection
method with a single endogenous regressor the correlation coefficient rho was wrongly constraint to [0, 1] instead of to [-1, 1]. Further, rho was not included in parts of the calculations. Special thanks to Fredrik Falkenström for reporting this observation!
- Allow using the method
copulaCorrection
with a single endogenous regressor
- Add a formal assumption test for method
hetErrorsIV
to detect weak instruments
- The log-likelihood function underlying
copulaCorrection
case 1 is refactored and implemented using Rcpp and RcppEigen what makes it considerably faster - Improved checks of user input that disallow any non-finite values in the data
- New data was generated for
dataHetIV
- None. Version bump in order to resubmit to CRAN after package was archived.
- Add support for predictions through method
predict
for every model
- Fix wrong calculations for the fitted values and residuals in the enhanced OLS cases of
copulaCorrection
- Improved documentation
- To tweak the lmer model fit in
multilevelIV
to their linking, users can supply a parameterlmer.control
- Warning in
confint
if there are NAs in the bootstrapped estimates forcopulaCorrection
- Updated vignette
- The coefficient estimates for
multilevelIV
are more consistent and independent of data sorting due to different standard settings for fittinglmer
- Bootstrapped parameter estimates for
copualCorrection
result in fewer NAs when using L-BFGS-B as optimization method
- The augmented OLS method in
copulaCorrection
also bootstraps parameter estimates - The summary output for results from
copulaCorrection
was adapted to reflect that standard errors are bootstrapped - Removed support for the S3 method
labels
because of inconsistent behavior across methods
- Bootstrapping for
copulaCorrection
case 1 is now considerably faster - New data was generated for
dataMultilevelIV
- The sigma matrix in
latentIV
is constructed as in the paper by Ebbes et al. what improves results. Special thanks to Jordan Henderson for investigating and pointing this out! - In
latentIV
, the parameter for group membership (theta5
) is now transformed back and reported correctly. - The vcov matrix for
latentIV
is corrected for the transformation intheta5
. - The bootstrapping in
copulaCorrection
case 1 now creates samples of the same length as the original data - The (percentile) confidence intervals and vcov for results from
copulaCorrection
now rely on bootstraping
- The reworked method
multilevelIV
and accompanying data was added back to the package - Vignette
REndo-introduction
was added to showcase package usage - Users can supply a parameter
optimx.args
to tweak the LL optimization to their liking
- Method
confint
was added for methodslatentIV
andcopulaCorrection
- Examples and documentation were improved for all methods
- New data was generated for
dataHetIV
- The default number of iterations for all optimizations was increased to 100'000
- To avoid infrequent warnings, the parameter
sigma
used incopulaCorrection
was constrained to > 0 - Various spelling mistakes were fixed
- Remodeled all methods' user-interface
- Added detailed input checks for every provided parameter
- Adapted all visible outputs
- Parameter
verbose
allows to turn on or off printing - Updated documentation to reflect all changes and added theoretical background
- Formulas support transformations
- Improve all code to be more reliable and stable
- Provide new example datasets and accompanying documentation for all methods
- Added extensive testing for all aspects of the package
- Increased numerical stability for log-likelihood optimization methods
latentIV
andcopualCorrection
- Many
- The multilevel function is temporarily removed from the package due to ongoing work on it