kappaGold (version 0.4.0)

simulKappa: Simulate rating data and calculate agreement with gold standard

Description

The function generates simulation data according to given categories and probabilities. and can repeatedly apply function kappam_gold(). Currently, there is no variation in probabilities from rater to rater, only sampling variability from multinomial distribution is at work.

Usage

simulKappa(nRater, cats, nSubj, probs, mcSim = 10, simOnly = FALSE)

Value

dataframe of kappa-gold on the simulated datasets or (when simOnly=TRUE) list of length mcSim with each element a simulated data set with goldrating in first column and then the raters.

Arguments

nRater

numeric. number of raters.

cats

categories specified either as character vector or just the numbers of categories.

nSubj

numeric. number of subjects per gold standard category. Either a single number or as vector of numbers per category, e.g. for non-balanced situation.

probs

numeric square matrix (nCat x nCat) with classification probabilities. Row i has probabilities of rater categorization for subjects of category i (gold standard).

mcSim

numeric. Number of Monte-Carlo simulations.

simOnly

logical. Need only simulation data? Default is FALSE.

Details

This function is future-aware for the repeated evaluation of kappam_gold() that is triggered by this function.

Examples

# repeatedly estimate agreement with goldstandard for simulated data
simulKappa(nRater = 8, cats = 3, nSubj = 11,
           # assumed prob for classification by raters
           probs = matrix(c(.6, .2, .1, # subjects of cat 1
                            .3, .4, .3, # subjects of cat 2
                            .1, .4, .5  # subjects of cat 3
           ), nrow = 3, byrow = TRUE))