modelkappa: Function to calculate model-based kappa of agreement and...

In AyaMitani/modelkappa: Calculates model-based kappa for agreement and association and their standard errors

Description

The data must be provided in case level or equivalently in ‘long’ format that includes item (or patient) identifiers, rater identifiers, and ratings (or categories).

Usage

modelkappa(data, category, item, rater)

Arguments

data	an optional data frame containing the variables providing category, item, and rater.
category	a numerical vector that identifies the ratings or results (binary or >2 categories).
item	a numerical vector that identifies the items to be rated (e.g. mammogram ids).
rater	a numerical vector that identifies the raters (e.g. radiologist ids).

Value

Outputs the estimated summary measures containing Number of observations, Number of categories, Number of items, Number of raters, Model-based kappa for agreement, its standard errors and 95 If number of categories is >2, then will also output Model-based kappa for association, its standard errors and 95

Author(s)

Aya Mitani

Examples

data(holmdata)
modelkappa(data=holmdata, cat=Cat, item=Item, rater=Rater)

AyaMitani/modelkappa documentation built on Nov. 20, 2019, 6:21 a.m.