Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	834506
MD5	33811BECABFD2D741E9B6EF65E592362
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.8-1
SHA-1	10668AA0B27555C5A0CF5D044FAB123406BE34E2
SHA-256	B7A59C282FACEE52D6BD74B322A90E1D6F3E43C7C19484175E93E43874095FB4

Key	Value
FileSize	836968
MD5	024242A947C03132AFBD892899DBAE6F
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.8-1
SHA-1	299F0590769B9D676C14859206AD099328710F13
SHA-256	02AF6E1B8D73D5272E2A1915ED502590ED22C16DC9B9915B65ABF6EE9C420903

Key	Value
FileSize	834628
MD5	A99775E199297496250118C40AA66961
PackageDescription	GNU R regression modeling strategies tools by Frank Harrell Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model. . See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://hesweb1.med.virginia.edu/biostat/s/Design.html
PackageMaintainer	Dirk Eddelbuettel <edd@debian.org>
PackageName	r-cran-design
PackageSection	math
PackageVersion	2.0.8-1
SHA-1	007828E2FD536FF059CB8C40CC2EC4EF1E847A3D
SHA-256	88B5B37861770BA6CEBBA7E53DC9884EDCF56546B57F92682733007351CC6C4C