#' Initial Data Inspection
#'
#' @description This function does an intial inspection on the data.
#'
#' @usage initialInspectCortisol(dat, calibName, calibValue, nVar, drop)
#' @param dat
#' A data frame
#' @param calibVar
#' The name of the calibration variable (usually STAND or A)
#' @param calibValue
#' The value for calibration (usually 0)
#' @param cpmVar
#' The name for the CPM variable (usually CPM)
#' @param idVar
#' The ID variable; is often "N".
#' @param drop
#' Which participant to drop.
#' @export
#' @examples
#'
#' dat = data.frame(N = 1:10,
#' CPM = c(44396.5, 47774.5, 23676.0, 24290.3, 23541.0,
#' 20108.7, 20101.3, 19383.7, 17013.7, 17678.7),
#' STAND = c(NA, NA, 0, 0, 1,
#' 1, 3, 10, 30, 100))
#' # The First Pass #
#'
#' initialInspectCortisol(dat, "STAND", 0, "CPM")
#'
#' # Deleting Observations #
#'
#' initialInspectCortisol(dat, "STAND", 0, "CPM", "N", 1)
#'
#' @importFrom ggplot2 ggplot
#' @importFrom ggplot2 geom_point
#' @importFrom ggplot2 geom_smooth
#' @importFrom ggplot2 %+%
#' @importFrom ggplot2 aes
#' @importFrom ggplot2 scale_y_continuous
#' @importFrom ggplot2 ggtitle
initialInspectCortisol = function(dat, calibVar, calibValue, cpmVar,
idVar = NULL, drop = NULL) {
if(calibVar %in% names(dat) == FALSE) stop(paste(calibVar, "is not in your data.", sep = " "))
if (is.null(drop)) {
initialDat = dat[dat[, calibVar] %in% calibValue, ]
} else {
initialDat = dat[dat[, calibVar] %in% calibValue & corDat[, idVar] != drop, ]
if(idVar %in% names(dat) == FALSE) stop(paste(idVar, "is not in your data.", sep = " "))
}
standOnly = dat[dat[[calibVar]] == 0,]
cpmMean = mean(standOnly[[cpmVar]], na.rm = TRUE)
bindings = (dat[[cpmVar]]/cpmMean) * 100
logVals = log((100 - bindings) / bindings)
logStd = log(dat[[calibVar]])
plotDat = cbind(dat, bindings, logVals, logStd)
logStdMod = lm(logVals ~ logStd, data = plotDat[plotDat$logStd >= 0, ])
logStdConstant = logStdMod$coefficients[[1]]
logStdCoef = logStdMod$coefficients[[2]]
logModSum = summary(logStdMod)
logModRSqr = logModSum$adj.r.squared
resultReturn = paste("Your R-square is", round(logModRSqr, 5))
p1 = ggplot(plotDat, aes(logStd, plotDat[[calibVar]])) +
geom_smooth(span = .5) +
geom_point() +
scale_y_continuous(name = "STAND") +
ggtitle(resultReturn) +
ggtheme()
p2 = ggplot(plotDat, aes(logVals, plotDat[[calibVar]])) +
geom_point() +
scale_y_continuous(name = "STAND") +
ggtheme()
p3 = ggplot(plotDat, aes(logVals, plotDat[[calibVar]])) +
geom_smooth(method = "lm") +
geom_point() +
scale_y_continuous(name = "STAND") +
ggtheme()
p4 = ggplot(plotDat, aes(logVals, logStd)) +
geom_smooth() +
geom_point() +
ggtheme()
p5 = ggplot(plotDat, aes(logVals, logStd)) +
geom_point() +
ggtheme()
multiplot(p1, p2, p3, p4, p5)
return(plotDat)
logModSum
}
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