'ls_means.R' 'ranova.R' 'step.R' 'terms_utils.R' 'utils.R'

person("Per", "Bruun Brockhoff", role = c("aut", "ths"),
person("Sofie", "Pødenphant Jensen", role=c("ctb", "cre"), email="sofp@dtu.dk"))
Maintainer: Sofie Pødenphant Jensen <sofp@dtu.dk>

person("Rune", "Haubo Bojesen Christensen", role =  c("aut", "cre"),
person("Sofie", "Pødenphant Jensen", role=c("ctb"), email="sofp@dtu.dk"))
Rune Haubo Bojesen Christensen [aut, cre],
Maintainer: Rune Haubo Bojesen Christensen <Rune.Haubo@gmail.com>

Title: Bootstrap Methods for Nested Linear Mixed-Effects Models
Authors@R: c(person("Adam", "Loy", email = "loyad01@gmail.com",
role = c("aut", "cre")), person("Spenser", "steele", role = "aut"))
Description: Bootstrap routines for nested linear mixed effects models fit using
either 'lme4' or 'nlme'. The provided 'bootstrap()' function implements the
parametric, semi-parametric (i.e., CGR), residual, cases, and random effect
Imports: boot, plyr, dplyr, Matrix, nlmeU, RLRsim
Suggests: lme4 (>= 1.1-7), nlme, testthat, mlmRev

parametric, residual, cases, semi-parametric (i.e., CGR),  and random effect
block (REB) bootstrap procedures. An overview of these procedures can be found
Imports: boot, plyr, dplyr (>= 0.8.0), Matrix, nlmeU, RLRsim

role = c("aut", "cre")), person("Spenser", "Steele", role = "aut"),
person("Jenna", "Korobova", role = "aut"))
parametric, residual, cases, random effect block (REB), and wild bootstrap
procedures. An overview of these procedures can be found
Imports: catchr, dplyr (>= 0.8.0), Matrix, nlmeU, ggplot2, ggdist,
HLMdiag, purrr, forcats, stats, statmod, magrittr
Suggests: lme4 (>= 1.1-7), nlme, testthat, mlmRev, knitr, rmarkdown,

Imports: dplyr (>= 0.8.0), Matrix, nlmeU, ggplot2, ggdist, HLMdiag,
purrr, forcats, stats, statmod, tidyr, magrittr

person("Spenser", "Steele", role = "aut"),
purrr, forcats, stats, statmod, tidyr, magrittr, tibble

Title: Functions for estimation and inference of selection in
Description: This R package provide methods for estimation and
statistical inference on directional and fluctuating selection