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Agreement among raters is of great importance in many domains. For
example, in medicine, diagnoses are often provided by more than one
doctor to make sure the proposed treatment is optimal. In criminal
trials, sentencing depends, among other things, on the complete
agreement among the jurors. In observational studies, researchers
increase reliability by examining discrepant ratings. This book is
intended to help researchers statistically examine rater agreement
by reviewing four different approaches to the technique. The first
approach introduces readers to calculating coefficients that allow
one to summarize agreements in a single score. The second approach
involves estimating log-linear models that allow one to test
specific hypotheses about the structure of a cross-classification
of two or more raters' judgments. The third approach explores
cross-classifications or raters' agreement for indicators of
agreement or disagreement, and for indicators of such
characteristics as trends. The fourth approach compares the
correlation or covariation structures of variables that raters use
to describe objects, behaviors, or individuals. These structures
can be compared for two or more raters. All of these methods
operate at the level of observed variables. This book is intended
as a reference for researchers and practitioners who describe and
evaluate objects and behavior in a number of fields, including the
social and behavioral sciences, statistics, medicine, business, and
education. It also serves as a useful text for graduate-level
methods or assessment classes found in departments of psychology,
education, epidemiology, biostatistics, public health,
communication, advertising and marketing, and sociology. Exposure
to regression analysis and log-linear modeling is helpful.
Agreement among raters is of great importance in many domains. For
example, in medicine, diagnoses are often provided by more than one
doctor to make sure the proposed treatment is optimal. In criminal
trials, sentencing depends, among other things, on the complete
agreement among the jurors. In observational studies, researchers
increase reliability by examining discrepant ratings. This book is
intended to help researchers statistically examine rater agreement
by reviewing four different approaches to the technique.
The first approach introduces readers to calculating coefficients
that allow one to summarize agreements in a single score. The
second approach involves estimating log-linear models that allow
one to test specific hypotheses about the structure of a
cross-classification of two or more raters' judgments. The third
approach explores cross-classifications or raters' agreement for
indicators of agreement or disagreement, and for indicators of such
characteristics as trends. The fourth approach compares the
correlation or covariation structures of variables that raters use
to describe objects, behaviors, or individuals. These structures
can be compared for two or more raters. All of these methods
operate at the level of observed variables.
This book is intended as a reference for researchers and
practitioners who describe and evaluate objects and behavior in a
number of fields, including the social and behavioral sciences,
statistics, medicine, business, and education. It also serves as a
useful text for graduate-level methods or assessment classes found
in departments of psychology, education, epidemiology,
biostatistics, public health, communication, advertising and
marketing, and sociology. Exposure to regression analysis and
log-linear modeling is helpful.
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