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Developed to perform the estimation and inference for regression coefficient parameters in longitudinal marginal models using the method of quadratic inference functions. Like generalized estimating equations, this method is also a quasi-likelihood inference method. It has been showed that the method gives consistent estimators of the regression coefficients even if the correlation structure is misspecified, and it is more efficient than GEE when the correlation structure is misspecified. Based on Qu, A., Lindsay, B.G. and Li, B. (2000) <doi:10.1093/biomet/87.4.823>.
Version: | 1.5 |
Depends: | R (≥ 3.5.0) |
Imports: | MASS |
Published: | 2019-07-20 |
DOI: | 10.32614/CRAN.package.qif |
Author: | Zhichang Jiang [aut], Peter Song [aut], Michael Kleinsasser [cre] |
Maintainer: | Michael Kleinsasser <mkleinsa at umich.edu> |
BugReports: | https://github.com/umich-biostatistics/qif/issues |
License: | GPL-2 |
NeedsCompilation: | yes |
Materials: | README |
CRAN checks: | qif results |
Reference manual: | qif.pdf |
Package source: | qif_1.5.tar.gz |
Windows binaries: | r-devel: qif_1.5.zip, r-release: qif_1.5.zip, r-oldrel: qif_1.5.zip |
macOS binaries: | r-release (arm64): qif_1.5.tgz, r-oldrel (arm64): qif_1.5.tgz, r-release (x86_64): qif_1.5.tgz, r-oldrel (x86_64): qif_1.5.tgz |
Reverse imports: | vsmi |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.