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Last data update: 2014.03.03

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ibd : INCOMPLETE BLOCK DESIGNS

Package: ibd
Version: 1.2
Date: 2014-09-05
Title: INCOMPLETE BLOCK DESIGNS
Author: B N Mandal <mandal.stat@gmail.com>
Maintainer: B N Mandal <mandal.stat@gmail.com>
Depends: R (>= 3.1.1), lpSolve, MASS, car, lsmeans, multcompView
Description: This package contains several utility functions related to incomplete block designs. The package contains function to generate efficient incomplete block designs with given numbers of treatments, blocks and block size. The package also contains function to generate an incomplete block design with specified concurrence matrix. There are functions to generate balanced treatment incomplete block designs and incomplete block designs for test versus control treatments comparisons with specified concurrence matrix. Package also allows performing analysis of variance of data and computing least square means of factors from experiments using a connected incomplete block design. Tests of hypothesis of treatment contrasts in incomplete block design set up is supported.
License: GPL (>= 2)
Packaged: 2014-09-08 01:05:30 UTC; User
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-09-08 06:58:26

● Data Source: CranContrib
● 0 images, 28 functions, 1 datasets
● Reverse Depends: 0

afex : Analysis of Factorial Experiments

Package: afex
Type: Package
Title: Analysis of Factorial Experiments
Depends: R (>= 3.1.0), lme4 (>= 1.1-8), reshape2, lsmeans (>= 2.17)
Suggests: ascii, xtable, parallel, plyr, optimx, nloptr, knitr,
lattice, multcomp, testthat, mlmRev, dplyr
Imports: stringr, coin, Matrix (>= 1.1.1), pbkrtest (>= 0.4-1), car,
stats, utils, methods
Description: Provides convenience functions for analyzing factorial
experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow
specification of between, within (i.e., repeated-measures), or mixed between-
within (i.e., split-plot) ANOVAs for data in long format (i.e., one observation
per row), potentially aggregating multiple observations per individual and
cell of the design. mixed() fits mixed models using lme4::lmer() and computes
p-values for all fixed effects using either Kenward-Roger approximation for
degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or
likelihood ratio tests (LMMs and GLMMs). afex uses type 3 sums of squares as
default (imitating commercial statistical software).
URL: https://github.com/singmann/afex
License: GPL (>= 3)
Encoding: UTF-8
VignetteBuilder: knitr
Authors@R: c(person(given="Henrik", family="Singmann", role=c("aut", "cre"), email="singmann+afex@gmail.com"), person(given="Ben", family="Bolker",
role=c("aut")), person(given="Jake", family="Westfall", role=c("aut")), person(given="Frederik", family="Aust", role=c("aut")),
person(given="SÃ¸ren", family="HÃ¸jsgaard", role=c("ctb")), person(given="John", family="Fox", role=c("ctb")), person(given="Michael A.",
family="Lawrence", role=c("ctb")), person(given="Ulf", family="Mertens", role=c("ctb")) )
Version: 0.16-1
Date: 2016-04-04
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-04-03 22:10:13 UTC; henrik
Author: Henrik Singmann [aut, cre],
Ben Bolker [aut],
Jake Westfall [aut],
Frederik Aust [aut],
SÃ¸ren HÃ¸jsgaard [ctb],
John Fox [ctb],
Michael A. Lawrence [ctb],
Ulf Mertens [ctb]
Maintainer: Henrik Singmann <singmann+afex@gmail.com>
Repository: CRAN
Date/Publication: 2016-04-04 01:11:31

● Data Source: CranContrib
● 0 images, 20 functions, 0 datasets
● Reverse Depends: 1