Package: qif 1.5

Michael Kleinsasser

qif: Quadratic Inference Function

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>.

Authors:Zhichang Jiang [aut], Peter Song [aut], Michael Kleinsasser [cre]

qif_1.5.tar.gz
qif_1.5.zip(r-4.5)qif_1.5.zip(r-4.4)qif_1.5.zip(r-4.3)
qif_1.5.tgz(r-4.4-x86_64)qif_1.5.tgz(r-4.4-arm64)qif_1.5.tgz(r-4.3-x86_64)qif_1.5.tgz(r-4.3-arm64)
qif_1.5.tar.gz(r-4.5-noble)qif_1.5.tar.gz(r-4.4-noble)
qif_1.5.tgz(r-4.4-emscripten)qif_1.5.tgz(r-4.3-emscripten)
qif.pdf |qif.html
qif/json (API)

# Install 'qif' in R:
install.packages('qif', repos = c('https://umich-biostatistics.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/umich-biostatistics/qif/issues

Uses libs:
  • openblas– Optimized BLAS
Datasets:

On CRAN:

3.18 score 1 packages 2 scripts 108 downloads 1 exports 1 dependencies

Last updated 5 years agofrom:59fac88280. Checks:OK: 4 NOTE: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-win-x86_64NOTENov 04 2024
R-4.5-linux-x86_64NOTENov 04 2024
R-4.4-win-x86_64NOTENov 04 2024
R-4.4-mac-x86_64NOTENov 04 2024
R-4.4-mac-aarch64NOTENov 04 2024
R-4.3-win-x86_64OKNov 04 2024
R-4.3-mac-x86_64OKNov 04 2024
R-4.3-mac-aarch64OKNov 04 2024

Exports:qif

Dependencies:MASS