Implications of systematic nominator missingness for peer nomination data

Matching components of self-report and peer-nomination personality measures.

Two common methods of measuring personality variables are examined with respect to the ways in which they control respondent biases. A form of the mental-test theory model is developed which makes explicit differences in score components that result from different methodological constraints imposed by the two methods. From the model, it is possible to specify the operations necessary to provide...

KETAMINE Nomination 1.0 BASIS OF NOMINATION

A Latent Factor Model for Spatial Data with Informative Missingness.

A large amount of data is typically collected during a periodontal exam. Analyzing these data poses several challenges. Several types of measurements are taken at many locations throughout the mouth. These spatially-referenced data are a mix of binary and continuous responses, making joint modeling difficult. Also, most patients have missing teeth. Periodontal disease is a leading cause of toot...

Exploiting Data Missingness in Bayesian Network Modeling

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Detecting bullying in early elementary school with a computerized peer-nomination instrument.

In this study we describe the PEERS Measure, a computerized assessment instrument that takes an innovative approach to using the peer-nomination method to identify bullying among elementary school children in Grades 1-2. Its psychometric characteristics were measured in 4,017 children from 190 school classes. The intercorrelations between the peer-nomination scores showed congruence of the data...