R/ordinal-marg-effects-error-check.R

In bayesMeanScale: Bayesian Post-Estimation on the Mean Scale

ordinalMargErrorCheckF <- function(model, marginal_effect, at, start_value, end_value, centrality){

  # make sure it's the right model #
  
  if(!all(c('stanreg', 'polr') %in% class(model))){
    stop("Only models fit using 'stan_polr' are supported!")
  }
  
  # make sure the link function is supported #
  
  if(!model$method %in% c("logistic", "probit", "cloglog")){
    stop('The link function of your model is not supported!')
  }

  # check for correct length of arguments #

  if(!(length(marginal_effect)==length(start_value) & length(start_value)==length(end_value))){
    stop("The arguments for 'marginal_effect,' 'start_value,' and 'end_value' must all have the same length!")
  }

  # check that marginal effects have the right names #

  if(!all(marginal_effect %in% names(model$model))){
    stop("The names of the marginal effects don't match up with the names in the model data!")
  }

  # check that the names for the at values are correct #

  if(!is.null(at) & !all(names(at) %in% names(model$model))){
    stop("The names for the at values don't match up with the names in the model data!")
  }

  # check that the start and end values are either vectors of length 1 or lists #

  if(length(start_value) > 1 & !is.list(start_value)){
    stop("When specifying multiple start values, they must be contained in a list to preserve data type!")
  }

  if(length(end_value) > 1 & !is.list(end_value)){
    stop("When specifying multiple end values, they must be contained in a list to preserve data type!")
  }
  
  # check that the centrality measure is supported #
  
  if(!(centrality %in% c('mean', 'median'))){
    stop("Centrality options are 'mean' or 'median'!")
  }

}