R/aps.R

In aplore3: Datasets from Hosmer, Lemeshow and Sturdivant, "Applied Logistic Regression" (3rd Ed., 2013)

#' APS data
#' 
#' aps dataset.
#' 
#' @format A data.frame with 508 rows and 11 variables:
#' \describe{
#' \item{id}{Identification Code (1 - 508)}
#' \item{place}{Placement (1: Outpatient, 2: Day Treatment, 3:
#' Intermediate Residential, 4: Residential)}
#' \item{place3}{Placement Combined (1: Outpatient or Day Treatment, 2:
#' Intermediate Residential, 3: Residential )}
#' \item{age}{Age at Admission (Years)}
#' \item{race}{Race (1: White, 2: Non-white)}
#' \item{gender}{Gender (1: Female, 2: Male)}
#' \item{neuro}{Neuropsychiatric Disturbance (1: None, 2: Mild, 3:
#' Moderate, 4: Severe)}
#' \item{emot}{Emotional Disturbance (1: Not Severe, 2: Severe) }
#' \item{danger}{Danger to Others (1: Unlikely, 2:
#' Possible, 3: Probable, 4: Likely)}
#' \item{elope}{Elopement Risk (1: No Risk, 2: At Risk)}
#' \item{los}{Length of Hospitalization (Days)}
#' \item{behav}{Behavioral Symptoms Score (0 - 9)}
#' \item{custd}{State Custody (1: No, 2: Yes)}
#' \item{viol}{History of Violence (1: No, 2: Yes)}
#' }
#' @source Hosmer, D.W., Lemeshow, S. and Sturdivant, R.X. (2013) Applied
#' Logistic Regression, 3rd ed., New York: Wiley
#' @examples
#' head(aps, n = 10)
#' summary(aps)
#' 
#'
#' ## Table 8.2 p. 274
#' library(nnet)
#' modt8.2 <- multinom(place3 ~ viol, data = aps)
#' summary(modt8.2)
#' exp(coef(modt8.2)[, "violYes"])
#' t(exp(confint(modt8.2)["violYes", ,]))
#' ## To test differences between b_2 and b_1 we need the estimated variance
#' ## covariance matrix for the fitted model (Table 8.3 p. 274). 
#' vcov(modt8.2) # 'raw'
#' ## To have exactly the same output as the text we need to rearrange just a
#' ## minimum
#' VarCovM <- vcov(modt8.2)[c(2, 1, 4, 3), c(2, 1, 4, 3)]
#' VarCovM[upper.tri(VarCovM)] <- NA
#' VarCovM
#' ## Testing against null model. 
#' modt8.2Null <- multinom(place3 ~ 1, data = aps)
#' anova(modt8.2, modt8.2Null, test = "Chisq")
#' 
"aps"