Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial. Hallgren, K. A. Tutorials in quantitative methods for psychology, 8(1):23–34, 2012.
Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial [link]Paper  abstract   bibtex   
Many research designs require the assessment of inter-rater reliability (IRR) to demonstrate consistency among observational ratings provided by multiple coders. However, many studies use incorrect statistical procedures, fail to fully report the information necessary to interpret their results, or do not address how IRR affects the power of their subsequent analyses for hypothesis testing. This paper provides an overview of methodological issues related to the assessment of IRR with a focus on study design, selection of appropriate statistics, and the computation, interpretation, and reporting of some commonly-used IRR statistics. Computational examples include SPSS and R syntax for computing Cohen’s kappa and intra-class correlations to assess IRR.
@article{hallgren_computing_2012,
	title = {Computing {Inter}-{Rater} {Reliability} for {Observational} {Data}: {An} {Overview} and {Tutorial}},
	volume = {8},
	issn = {1913-4126},
	shorttitle = {Computing {Inter}-{Rater} {Reliability} for {Observational} {Data}},
	url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3402032/},
	abstract = {Many research designs require the assessment of inter-rater reliability (IRR) to demonstrate consistency among observational ratings provided by multiple coders. However, many studies use incorrect statistical procedures, fail to fully report the information necessary to interpret their results, or do not address how IRR affects the power of their subsequent analyses for hypothesis testing. This paper provides an overview of methodological issues related to the assessment of IRR with a focus on study design, selection of appropriate statistics, and the computation, interpretation, and reporting of some commonly-used IRR statistics. Computational examples include SPSS and R syntax for computing Cohen’s kappa and intra-class correlations to assess IRR.},
	number = {1},
	urldate = {2015-09-18},
	journal = {Tutorials in quantitative methods for psychology},
	author = {Hallgren, Kevin A.},
	year = {2012},
	pmid = {22833776},
	pmcid = {PMC3402032},
	keywords = {icc, kapp, kin610, tutorial},
	pages = {23--34},
}

Downloads: 0