Model-Based Reliability to Check for Disparities in Ratings of Internal and External Applicants
Result description
ZÁKLADNÍ ÚDAJE: Abstractband. VIII. European Congress on Methodology. Abstract Book. Jena: Institut für Psychologie, Friedrich-Schiller-Universität, 2018. s. 102-102. 2018 European Congress on Methodology /8./. 25.07.2018-27.07.2018, Jena. Grant CEP: GA ČR GJ15-15856Y. ABSTRAKT: In this work we address disparities in ratings of internal and external applicants. We develop model-based inter-rater reliability (IRR) estimate to account for various sources of measurement error, their hierarchical structure and the presence of covariates, such as assessed status, that have the potential to moderate IRR. Using dataset of ratings of applicants to teaching positions in Spokane district in Washington, USA, we first test for bias in ratings of applicants external to the district, which is shown to be significant even after including various measures of teacher quality in the model. Moreover, withmodel-based IRR, we show that consistency between raters is significantly lower when rating external applicants. We further address how IRR affects the predictive power of measurement in different scenarios and conclude the work by discussing policy implications and applications of our model-based IRR estimate for teacher hiring practices.
Keywords
GeneralizabilityLinear Mixed ModelsReliabilityVariance Decomposition
The result's identifiers
Result code in IS VaVaI
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Model-Based Reliability to Check for Disparities in Ratings of Internal and External Applicants
Original language description
ZÁKLADNÍ ÚDAJE: Abstractband. VIII. European Congress on Methodology. Abstract Book. Jena: Institut für Psychologie, Friedrich-Schiller-Universität, 2018. s. 102-102. 2018 European Congress on Methodology /8./. 25.07.2018-27.07.2018, Jena. Grant CEP: GA ČR GJ15-15856Y. ABSTRAKT: In this work we address disparities in ratings of internal and external applicants. We develop model-based inter-rater reliability (IRR) estimate to account for various sources of measurement error, their hierarchical structure and the presence of covariates, such as assessed status, that have the potential to moderate IRR. Using dataset of ratings of applicants to teaching positions in Spokane district in Washington, USA, we first test for bias in ratings of applicants external to the district, which is shown to be significant even after including various measures of teacher quality in the model. Moreover, withmodel-based IRR, we show that consistency between raters is significantly lower when rating external applicants. We further address how IRR affects the predictive power of measurement in different scenarios and conclude the work by discussing policy implications and applications of our model-based IRR estimate for teacher hiring practices.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
GJ15-15856Y: Estimation of psychometric measures as part of admission test development
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Basic information
Result type
O - Miscellaneous
OECD FORD
Statistics and probability
Year of implementation
2018