R/data.R

In bblpo/diaglm: Do multiple diagnoses for linear model output. Plot and save the diagnoses. It also tests the best possible transformation of variables to counter violations.

#' A dataset.
#' From original article: Kittilson, Miki Caul and Russell J. Dalton. (2011). “Virtual Civil Society: The New Frontier of Social Capital?” Political Behavior: Volume 33, Issue 4, pp 625-644
#'
#' society. The newly added variables are as follows:
#' \itemize{
#'   \item tolerance_scale. the response variable for model 1 of Table 4, Kittilson and Dalton (2011)
#'   \item duty_based_index. the response variable for model 2 of Table 4, Kittilson and Dalton (2011)
#'   \item engagement_index. the response variable for model 3 of Table 4, Kittilson and Dalton (2011)
#'   \item Factor1. the response variable for model 5 of Table 4, Kittilson and Dalton (2011)
#'   \item Factor2. the response variable for model 6 of Table 4, Kittilson and Dalton (2011)
#'   \item Factor3. the response variable for model 7 of Table 4, Kittilson and Dalton (2011)
#'   \item Factor4. the response variable for model 8 of Table 4, Kittilson and Dalton (2011)
#' }
#'
#' @format A data frame with 1001 rows and 804 variables
#' @source \url{https://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/4607}
#' @docType data
#' @keywords datasets
#' @name data
#' @usage data(data)
#' @examples
#' data(data)
#' mod<-lm(data$tolerance_scale~data$sg_participation+data$virtual_si+as.numeric(data$EDUC)+as.numeric(data$yrbrn)+data$IVRACE2+data$IVRACE3+data$gndr+as.numeric(data$lrscale))
#' summary(mod)
NULL