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#' meningitis- Meningococcal Disease Data with missing data in the response variable
#'
#' @description The dataset meningitis is from a brief outbreak of meningococcal disease at the University of Illinois, Urbana-Champaign campus in the years 1991 and 1992. The dataset is available in the LogXact software and also analyzed in Imrey et al. (1996). Maiti and Pradhan (2009) fitted a logistic regression using the model CaseCntrl ~ Numill + Numsleep + Smoke + Set + Reftime.
#'
#' @format A data frame with several rows and columns representing various variables:
#' \describe{
#' \item{CaseCntrl}{Case control status}
#' \item{Numnill}{Number of illnesses}
#' \item{Numsleep}{Number of sleep disturbances}
#' \item{Smoke}{Smoking status}
#' \item{Set}{Set variable}
#' \item{Reftime}{Reference time}
#' }
#'
#' @references
#' Cytel Inc (2010). LogXact 9 User Manual: Discrete Regression Analysis. Cambridge, Massachusetts: Cytel Inc.
#'
#' Imrey, P. B., Jackson, L. A., Ludwinski, P. H., England, A. C. II, Fox, B. C., Isdale, L. B., Reeves, M. W., and Wenger, J. D. (1996). Outbreak of serogroup C meningococcal disease associated with campus bar patronage. American Journal of Epidemiology 143, 624–630.
#'
#' Maiti, T., Pradhan, V. (2009). Bias reduction and a solution of separation of logistic regression with missing covariates. Biometrics, 65, 1262-1269.
#'
#' Pradhan, V., Nychka, D. and Bandyopadhyay, S. (2024). Beyond the Odds: Fitting Logistic Regression with Missing Data in Small Samples (submitted).
#'
#' @examples
#' # Examples using Firth (1993) type bias reduction. Complete case analysis or
#' # biascorrection=FALSE encounters separation
#' fit <- emBinRegMAR(CaseCntrl~Numnill+Numsleep+Smoke+Set+Reftime,
#' data=meningitis, biascorrectn=TRUE)
#' # display summary of the beta estimates of the model
#' fit$beta
#' # display summary of the alpha estimates of the model used
#' # for non-ignorability setting of the missing responses
#' fit$alpha
"meningitis"
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