A multilevel cross‐classified modelling approach to peer review of grant proposals: the effects of assessor and researcher attributes on assessor ratings

By U. Jayasinghe, Herbert W. Marsh, Nigel W. Bond. 2003

142 citations recorded by the source corpus.

Subfields: Public Health, Environmental and Occupational Health, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/69357c0e1214b767937821d6e71f05cac59576ce

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In Public Health, Environmental and Occupational Health

In Statistics and Probability

Citations in the corpus

The multilevel latent covariate model: a new, more reliable approach to group-level effects in contextual studies. (2008, background): “…examples of group-level constructs that rely on this aggregation process are multiple L1 assessors’ evaluations of the L2 quality of grant proposals (Jayasinghe et al., 2003), L1 students’ evaluations of L2 teaching effectiveness (Marsh, 1987, 2007), and multiple interchangeable L1 markers…”
Women's underrepresentation in science: sociocultural and biological considerations. (2009, background): “…proposal awards, and salary and promotion reviews, the best evidence in this area indicates that grant applications are not influenced by gender (Jayasinghe et al., 2003, 2006; Leboy, 2007), and the best evidence on salary and hiring (e.g., Ginther & Kahn, 2006) indicates that gender…”
A multilevel modelling approach to investigating the predictive validity of editorial decisions: do the editors of a high profile journal select manuscripts that are highly cited after publication? (2011, methodology): “With our proposed multilevel logistic modelling approach towards investigating the predictive validity of selection decisions, we follow the study by Jayasinghe et al. (2003), which proposed a multilevel modelling approach to the data analysis for examination of the reliability and fairness of peer…”
A multidisciplinary survey on discrimination analysis (2013, methodology): “For instance, Jayasinghe et al. (2003) adopt multilevel regression to take into account correlations in the cluster of ratings of a reviewer, and in the cluster of ratings in the same field of study.”
Evaluating expert judgments (2007, methodology): “For precedent on the use of this procedure for assessing inter-coder reliability, see Jayasinghe et al. (2003).”
The Consequences of Ignoring Individuals' Mobility in Multilevel Growth Models (2012, unknown): “Jayasinghe, Marsh, and Bond (2003) investigated the effect of assessor and researcher attributes on assessor ratings using CCREMs in which assessor ratings at Level 1 were crossclassified by assessors and proposals.”
Bias in peer review (2013, unknown): “Research has also shown improvements in inter-rater reliability with the addition of more reviewers per grant application (Jayasinghe et al., 2003).”
Looking Across and Looking Beyond the Knowledge Frontier: Intellectual Distance, Novelty, and Resource Allocation in Science (2016, background): “An ad hoc evaluation team might include a few, perhaps five to seven (Langfeldt 2006), specialized researchers whose phenomenological interest, research methods, and/or topical focus relate to the research proposal(s) in question (Jayasinghe et al. 2003).”