LG Futures, The University of Huddersfield and the University of Plymouth were commissioned by the Ministry of Housing, Communities and Local Government (MHCLG) and the Department for Education (DfE) to develop a new model to show relative need to spend on Children and Young People's Services across local authorities in England. This formed part…

Background: Counts are familiar outcomes in education research settings, including those involving tests of interventions. Clustered data commonly occur in education research studies, given that data are often collected from students within classrooms or schools. There is a wide array of distributions and models that can be used for clustered…

Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…

When selecting a multilevel model to fit to a dataset, it is important to choose both a model that best matches characteristics of the data's structure, but also to include the appropriate fixed and random effects parameters. For example, when researchers analyze clustered data (e.g., students nested within schools), the multilevel model can be…

This study is focused on the threat of retention associated with test-based promotion in Grade 3. Through analyzing the Early Childhood Longitudinal Study Kindergarten Class of 1998-1999 data, we found that schools having such a policy apparently increased math instructional time but not reading instructional time in Grade 3. On average, the…