Title: An R-package for estimating absolute protein quantities from
Author: George Rosenberger, Hannes Roest, Christina Ludwig, Barry Grant
Suggests: lattice, randomForest, ROCR, reshape2, testthat

Author: aLFQ: George Rosenberger, Hannes Roest, Christina Ludwig. AAindex: Barry Grant.
Imports: data.table, plyr, caret, seqinr
Suggests: lattice, randomForest, ROCR, reshape2, testthat, protiq

Imports: data.table, plyr, caret, seqinr, lattice, randomForest, ROCR,

Title: Estimating Absolute Protein Quantities from Label-Free LC-MS/MS
Author: George Rosenberger, Hannes Roest, Christina Ludwig, Ruedi Aebersold, Lars Malmstroem

Title: Automated Fitting of Moderated Nonlinear Factor Analysis Through
person("Veronica", "Cole", email = "vcole@email.unc.edu", role = c("aut","cre")),
person("Nisha", "Gottfredson", email = "gottfredson@email.unc.edu", role = c("aut")),
person("Michael", "Giordano", email = "mgiordano@email.unc.edu", role = c("aut")),
person("Tim", "Janssen", email = "tim_janssen@brown.edu", role = c("ctb")))
Description: Automated generation, running, and interpretation of moderated
nonlinear factor analysis models for obtaining scores from observed
variables. This package creates 'Mplus' input files which may be run iteratively
to test two different types of covariate effects on items:
(1) latent variable impact (both mean and variance); and (2) differential
item functioning. After sequentially testing for all effects, it also creates a final
model by including all significant effects after adjusting for multiple comparisons.
Finally, the package creates a scoring model which uses the final values of parameter
estimates to generate latent variable scores.
Imports: grDevices, graphics, stats, utils, ggplot2, MplusAutomation,
reshape2, gridExtra, stringr, plyr, devtools

Package: aMNLFA
Title: Automated Moderated Nonlinear Factor Analysis Using 'Mplus'
Version: 1.0.0
Authors@R: c(
person("Veronica", "Cole", email = "colev@wfu.edu", role = c("aut","cre")),
person("Nisha", "Gottfredson", email = "gottfredson@email.unc.edu", role = c("aut")),
person("Michael", "Giordano", email = "mgiordano@email.unc.edu", role = c("aut")),
person("Tim", "Janssen", email = "tim_janssen@brown.edu", role = c("ctb")))
Description: Automated generation, running, and interpretation of moderated
nonlinear factor analysis models for obtaining scores from observed
variables, using the method described by Gottfredson and colleagues (2019) <doi:10.1016/j.addbeh.2018.10.031>.
This package creates 'Mplus' input files which may be run iteratively
to test two different types of covariate effects on items:
(1) latent variable impact (both mean and variance); and (2) differential
item functioning. After sequentially testing for all effects, it also creates a final
model by including all significant effects after adjusting for multiple comparisons.
Finally, the package creates a scoring model which uses the final values of parameter
estimates to generate latent variable scores.
Depends: R (>= 3.1.0),
Imports: grDevices, graphics, stats, utils, ggplot2, MplusAutomation,
reshape2, gridExtra, stringr, plyr, devtools, dplyr
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-06-25 01:26:52 UTC; colev
Author: Veronica Cole [aut, cre],
Nisha Gottfredson [aut],
Michael Giordano [aut],
Tim Janssen [ctb]
Maintainer: Veronica Cole <colev@wfu.edu>
Repository: CRAN
Date/Publication: 2021-06-25 07:50:05 UTC