Results 231 to 240 of about 451,054 (288)

How can welfare regime and production regime theories explain differences in schools’ ability grouping policies? A comparative study using the PISA school survey

British Educational Research Journal, EarlyView.
Abstract Research evidence is mixed on the consequences of ability grouping policies, but most research has found an overrepresentation of disadvantaged social demographics in low‐ability groups. However, researchers have neglected to explain why ability grouping policies vary between countries.
Monica Reichenberg, Girma Berhanu, Lena Fridlund   +2 more
wiley   +1 more source

System failure? Exploring the interplay of fear of failure, competition, cooperation and sense of belonging in education in England and Flanders

British Educational Research Journal, EarlyView.
Abstract Fear of failure is damaging in a host of ways yet is rife in many schools. Drawing on self‐worth theory, we explore whether fear of academic failure is higher in education systems with features that increase students' experiences of competition. To do this, we compare two very different education systems: England, where, for instance, national
Carolyn Jackson, Mieke Van Houtte
wiley   +1 more source

Evidence for mood instability in patients with bipolar disorder: Applying multilevel hidden Markov modeling to intensive longitudinal ecological momentary assessment data.

Sebastian Mildiner Moraga, Fionneke M. Bos, Bennard Doornbos, Richard Bruggeman, Lian van der Krieke, Evelien Snippe, Emmeke Aarts   +6 more
openalex   +2 more sources

A multilevel downscaling model for enhancing nocturnal aerosol optical depth reanalysis from CAMS over the Beijing-Tianjin-Hebei region, China

Shiyao Wang, Fuxing Li, Gerrit de Leeuw, Cheng Fan, Zhengqiang Li   +4 more
openalex   +1 more source

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Multilevel Model Prediction

Psychometrika, 2006
Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling—model disturbances, random coefficients, and future response ...
Frees, Edward W., Kim, Jee-Seon
openaire   +1 more source

Multilevel Mixture Factor Models

Multivariate Behavioral Research, 2012
Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure.
Varriale R., Vermunt J. K.
openaire   +2 more sources

Multilevel models

2009
Abstract This article addresses multilevel models in which units are nested within one another. The focus is primarily two-level models. It also describes cross-unit heterogeneity. Moreover, it assesses the fixed and random effects from the multilevel model.
  +5 more sources

Multilevel Models

2018
This chapter introduces a statistical approach for analyzing nested data structures that both accounts for the dependence of observations due to hierarchical arrangements and allows for testing hypotheses at multiple levels. The most common application of multilevel models is for analyses of objects (e.g., people) nested within groups or clusters of ...
Peter Miksza, Kenneth Elpus
openaire   +1 more source

Multilevel Modeling

2017
Bernd Neumayr, Christoph G. Schuetz
  +5 more sources

Multilevel Modeling

2020
Simon Sherry, Anna MacKinnon
openaire   +2 more sources