Authors@R: c(person("Humberto", "Llinas", email = "hllinas@uninorte.edu.co", role = c("aut"), comment = c(ORCID = "0000-0002-2976-5109")),
person("Omar", "Fabregas", email = "ofabregas@uninorte.edu.co", role = c("aut"), comment = c(ORCID = "0000-0001-6853-6280")),
person("Jorge", "Villalba", email = "jlvia1191@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2888-9660")))
Author: Humberto Llinas [aut] (<https://orcid.org/0000-0002-2976-5109>),
Jorge Villalba [aut, cre] (<https://orcid.org/0000-0002-2888-9660>)
Description: When the values of the outcome variable Y are either 0 or 1,
the function lsm() calculates the estimation of the log likelihood
This model is characterized by Llinas (2006, ISSN:2389-8976) in section 2.3
The function LogLik() works (almost perfectly) when the number of independent
variables K is high, but for small K it calculates wrong values in some cases.
For this reason, when Y is dichotomous and the data are grouped in J populations,
it is recommended to use the function lsm() because it works very well for all K.
Imports: stats, dplyr (>= 1.0.0), ggplot2 (>= 1.0.0)

Author: Russell V. Lenth, The University of Iowa
Description: This package provides the function \code{\link{lsmeans}}
for outputting so-called least-squares means for factor
combinations in an 'lm', 'lme', or 'lmer' object. It can also
compute contrasts or linear combinations of these least-squares
means, and several standard contrast families are provided.

Suggests: nlme, lme4, pbkrtest, multcomp
Description: This package provides the function 'lsmeans' for
outputting so-called least-squares means for factor

Suggests: nlme, lme4, pbkrtest, multcomp, lattice

Description: This package provides the function 'lsmeans' for outputting so-called least-squares means for factor combinations in an 'lm', 'lme', or 'lmer' object. It can also compute contrasts or linear combinations of these least-squares means, and several standard contrast families are provided.

Suggests: nlme, lme4, pbkrtest, lattice, multcompView
Description: This package provides methods for obtaining least-squares means for various linear models. It can also compute contrasts or linear combinations of these least-squares means, comparisons of slopes, interaction plots, and compact letter displays.