R/data-combinedtattoo.R

In modeldiagramR: Generate Model Diagrams for Linear Mixed Effect Models

#' Data from a repeated measures study on tattoo sweat rates
#'
#' Results of a study of 10 subjects on sweat rates and sodium
#' concentrations, paired between two locations on each subject
#' I digitized the plotted data to create the provided data set, results do not
#' exactly match the original results.
#'
#' Subject demographics are
#' assumed to be correctly matched but were merged
#' based on the information in a plot and in a separate table
#'
#'
#' @format a \code{data.frame} with 20 observations on 10 variables from 10 subjects:
#' \describe{
#'   \item{Subject}{Subject ID from 1 to 10 0}
#'   \item{SweatRate}{Rate of sweat from a location, mg per cm-squared per min}
#'   \item{Tat_not}{Tattoo location or Not}
#'   \item{Na_conc}{Na concentration, mMol/L}
#'   \item{Height_cm}{Height of subject in cm}
#'   \item{Weight_kg}{Weight of subject in kg}
#'   \item{Age_yr}{Age of subject in years}
#'   \item{Side}{Side of subject, left or right}
#'   \item{Location}{Location of tattoo, categorical}
#'   \item{Tattoo_Age}{Age of tattoo (replicated both subject observations), years}
#' }
#'
#' @name combinedtattoo
#' @docType data
#' @references Luetkemeier, M., Hanisko, J., and K. Aho (2017) Skin Tattoos Alter Sweat Rate and Na+ Concentration. Medicine & Science in Sports & Exercise 49(7):p 1432-1436. DOI: 10.1249/MSS.0000000000001244
#' @source Digitized version of published Figures 1 and 2 combined with Table 1 (does not exactly match published numerical summaries!)
#' @keywords data tattoo repeated measures mixed models
#' @examples
#' library(dplyr)
#' data("combinedtattoo")
#' combinedtattoo <- combinedtattoo %>%
#'   mutate(SubjectF = factor(Subject))
#'
#' \donttest{
#' # Exploratory Data Plots
#' library(ggthemes)
#' library(ggplot2)
#' library(viridis)
#' p1 <- combinedtattoo %>%
#'   ggplot(aes(x = Tat_not, y = SweatRate, group = SubjectF)) +
#'     geom_line(aes(color = SubjectF)) +
#'     scale_color_viridis_d(end = 0.8)
#' p2 <- combinedtattoo %>%
#'   ggplot(aes(x = Tat_not, y = Na_conc, group = SubjectF)) +
#'     geom_line(aes(color = SubjectF)) +
#'     scale_color_viridis_d(end = 0.8)
#' p3 <- combinedtattoo %>%
#'   ggplot(aes(x = Weight_kg, y = SweatRate)) +
#'     geom_point(aes(color = Subject)) +
#'     scale_color_viridis_c(end = 0.8) +
#'     geom_smooth(method = "lm") +
#'     facet_wrap(~Tat_not)
#'
#' library(patchwork)
#' (p1 + p2) / (p3)
#' }
#'
#' library(lmerTest)
#' \donttest{
#' lmer1 <- lmer(SweatRate ~ Tat_not + (1|Subject),
#'               data = combinedtattoo)
#' summary(lmer1)
#'
#' model_diagram(lmer1)
#' }
#'
#' lmerFL <- lmer(SweatRate ~ Tat_not*Weight_kg + (1|Subject),
#'                data = combinedtattoo)
#' summary(lmerFL)
#'
#' model_diagram(lmerFL)
"combinedtattoo"