R/Examp2.6.1.R

In VetResearchLMM: Linear Mixed Models - An Introduction with Applications in Veterinary Research

#' @title    Examp2.6.1 from Duchateau, L. and Janssen, P. and Rowlands, G. J. (1998).\emph{Linear Mixed Models. An Introduction with applications in Veterinary Research}. International Livestock Research Institute.
#' @name     Examp2.6.1
#' @docType  data
#' @keywords datasets
#' @description Examp2.6.1 is used for inspecting probability distribution and to define a plausible process through
#' linear models and generalized linear models.
#' @author \enumerate{
#'          \item  Muhammad Yaseen (\email{myaseen208@@gmail.com})
#'          }
#' @references \enumerate{
#' \item Duchateau, L. and Janssen, P. and Rowlands, G. J. (1998).\emph{Linear Mixed Models. An Introduction with applications in Veterinary Research}.
#'              International Livestock Research Institute.
#'  }
#' @seealso
#'    \code{\link{ex124}}
#' @examples
#' #-------------------------------------------------------------
#' ## Example 2.6.1 p-76
#' #-------------------------------------------------------------
#'  # PROC MIXED DATA=ex125;
#'  # CLASS drug dose region;
#'  # MODEL pcv=drug dose drug*dose / ddfm=satterth;
#'  # RANDOM region drug*region;
#'  # CONTRAST 'drug dif' drug -1 1 drug*dose -0.5 -0.5 0.5 0.5;
#'  # CONTRAST 'all' drug 1 -1 dose 0  0 drug*dose 0.5  0.5 -0.5 -0.5,
#'  #                drug 0  0 dose 1 -1 drug*dose 0.5 -0.5  0.5 -0.5,
#'  #                drug 0  0 dose 0  0 drug*dose 0.5 -0.5 -0.5  0.5;
#'  # RUN;
#'
#' str(ex125)
#' ex125$Region1 <- factor(ex125$Region)
#' if (requireNamespace("lme4", quietly = TRUE) &&
#'     requireNamespace("lmerTest", quietly = TRUE)) {
#'   fm2.14 <-
#'     lmerTest::lmer(
#'            formula    = Pcv ~ dose * Drug + (1 | Region / Drug)
#'          , data       = ex125
#'          , REML       = TRUE
#'          , control    = lme4::lmerControl()
#'          , start      = NULL
#'          , verbose    = 0L
#'          , contrasts  = list(dose = "contr.SAS", Drug = "contr.SAS")
#'          , devFunOnly = FALSE
#'          )
#'   if (requireNamespace("report", quietly = TRUE)) {
#'     fm2.14 |>
#'       report::report()
#'   }
#'   if (requireNamespace("emmeans", quietly = TRUE)) {
#'     emm2.14 <- emmeans::emmeans(fm2.14, ~ dose | Drug, lmer.df = "asymptotic")
#'     print(emm2.14)
#'     print(emmeans::contrast(emm2.14, method = "pairwise"))
#'   }
#'   summary(fm2.14)
#'   anova(object = fm2.14, ddf = "Satterthwaite")
#'
#'   Contrasts3 <-
#'     matrix(
#'       c(0, 0, -1, -0.5),
#'       ncol = 4,
#'       byrow = TRUE,
#'       dimnames = list(c("C1"), rownames(summary(fm2.14)$coef))
#'     )
#'   Contrasts3
#'   if (requireNamespace("multcomp", quietly = TRUE)) {
#'     summary(multcomp::glht(fm2.14, linfct = Contrasts3))
#'   }
#'   if (utils::packageVersion("lmerTest") >= "3.0") {
#'     lmerTest::contest(fm2.14, Contrasts3, joint = FALSE)
#'   }
#' }
#'
NULL