Package: pmsampsize
Version: 1.0.0
Date: 2019-01-02
Title: Calculates the Minimum Sample Size Required for Developing a
        Multivariable Prediction Model
Authors@R: c(person("Joie", "Ensor", role = c("aut", "cre"), email = "j.ensor@keele.ac.uk"),
             person("Emma C.", "Martin", role = "aut", email = "emma.martin@leicester.ac.uk"),
	     person("Richard D.", "Riley", role = "aut", email = "r.riley@keele.ac.uk"))
Maintainer: Joie Ensor <j.ensor@keele.ac.uk>
Depends: R (>= 2.10)
Suggests: stats
Description: Computes the minimum sample size required for the development of a new multivariable prediction model using the criteria proposed by Riley et al. (2018) <doi: 10.1002/sim.7992>. pmsampsize can be used to calculate the minimum sample size for the development of models with continuous, binary or survival (time-to-event) outcomes. Riley et al. (2018) <doi: 10.1002/sim.7992> lay out a series of criteria the sample size should meet. These aim to minimise the overfitting and to ensure precise estimation of key parameters in the prediction model.
License: GPL (>= 3)
RoxygenNote: 6.1.1
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-01-02 19:42:24 UTC; prc87
Author: Joie Ensor [aut, cre],
  Emma C. Martin [aut],
  Richard D. Riley [aut]
Repository: CRAN
Date/Publication: 2019-01-08 16:30:03 UTC
