250 research outputs found
The Choice between fixed and random effects models: some considerations for educational research.
We discuss the use of fixed and random effects models in the context of educational research and set out the assumptions behind the two modelling approaches. To illustrate the issues that should be considered when choosing between these approaches, we analyse the determinants of pupil achievement in primary school, using data from the Avon Longitudinal Study of Parents and Children. We conclude that a fixed effects approach will be preferable in scenarios where the primary interest is in policy-relevant inference about the effects of individual characteristics, but the process through which pupils are selected into schools is poorly understood or the data are too limited to adjust for the effects of selection. In this context, the robustness of the fixed effects approach to the random effects assumption is attractive, and educational researchers should consider using it, even if only to assess the robustness of estimates obtained from random effects models. On the other hand, when the selection mechanism is fairly well understood and the researcher has access to rich data, the random effects model should naturally be preferred because it can produce policy-relevant estimates while allowing a wider range of research questions to be addressed. Moreover, random effects estimators of regression coefficients and shrinkage estimators of school effects are more statistically efficient than those for fixed effects.fixed effects, random effects, multilevel modelling, education, pupil achievement
The Choice Between Fixed and Random Effects Models: Some Considerations for Educational Research
We discuss fixed and random effects models in the context of educational research and set out the assumptions behind the two approaches. To illustrate the issues, we analyse the determinants of pupil achievement in primary school, using data from the Avon Longitudinal Study of Parents and Children. We conclude that a fixed effects approach will be preferable in scenarios where the primary interest is in policy-relevant inference of the effects of individual characteristics, but the process through which pupils are selected into schools is poorly understood or the data are too limited to adjust for the effects of selection. In this context, the robustness of the fixed effects approach to the random effects assumption is attractive, and educational researchers should consider using it, even if only to assess the robustness of estimates obtained from random effects models. When the selection mechanism is fairly well understood and the researcher has access to rich data, the random effects model should be preferred because it can produce policy-relevant estimates while allowing a wider range of research questions to be addressed. Moreover, random effects estimators of regression coefficients and shrinkage estimators of school effects are more statistically efficient than those for fixed effects.fixed effects, random effects, multilevel modelling, education, pupil achievement
Disability Law in a Pandemic: The Temporal Folds of Medico-legal Violence
Disabled people are subject to disability laws – such as guardianship, mental health and mental capacity legislation – which only apply to them, and which enable legal violence on the basis of disability (‘disability-specific lawful violence’). While public health laws during the COVID-19 pandemic enabled coercive interventions in the general population, disabled people have additionally been subject to the continued, and at times intensified, operation of disability laws and their lawful violence. In this article we engage with scholarship on law, temporality and disability to explore the amplification of disability-specific lawful violence during the pandemic. We show how this amplification has been made possible through the folding of longstanding assumptions about disabled people – as at risk of police contact; as vulnerable, unhealthy and contaminating – into the immediate crisis of the pandemic; ignoring structural drivers of oppression, and responsibilising disabled people for their circumstances and the violence they experience
Revisiting fixed- and random-effects models: some considerations for policy-relevant education research
The use of fixed (FE) and random effects (RE) in two-level hierarchical linear regression is discussed in the context of education research. We compare the robustness of FE models with the modelling flexibility and potential efficiency of those from RE models. We argue that the two should be seen as complementary approaches. We then compare both modelling approaches in our empirical examples. Results suggest a negative effect of special educational needs (SEN) status on educational attainment, with selection into SEN status largely driven by pupil level rather than school-level factors
A population-based study of chronic hepatitis C in immigrants and non-immigrants in Quebec, Canada
The choice between fixed and random effects models: some considerations for educational research
We discuss the use of fixed and random effects models in the context of educational research and set out the assumptions behind the two modelling approaches. To illustrate the issues that should be considered when choosing between these approaches, we analyse the determinants of pupil achievement in primary school, using data from the Avon Longitudinal Study of Parents and Children. We conclude that a fixed effects approach will be preferable in scenarios where the primary interest is in policy-relevant inference of the effects of individual characteristics, but the process through which pupils are selected into schools is poorly understood or the data are too limited to adjust for the effects of selection. In this context, the robustness of the fixed effects approach to the random effects assumption is attractive, and educational researchers should consider using it, even if only to assess the robustness of estimates obtained from random effects models. On the other hand, when the selection mechanism is fairly well understood and the researcher has access to rich data, the random effects model should naturally be preferred because it can produce policy-relevant estimates while allowing a wider range of research questions to be addressed. Moreover, random effects estimators of regression coefficients and shrinkage estimators of school effects are more statistically efficient than those for fixed effects
Distribution and Ecology of Invasive Ants
This project examines exactly how invasive specific types of ants are, and what effect that has on the ecosystem. To do so, most of the research must be compiled for the first time, as there is a lack of knowledge and research on this subject. Through former research, Tillberg finds that there are invasive pavement ants in Oregon state parks, but due to a lack of research on the species, their impact is unknown. The research will follow a paired design, comparing similar areas with and without pavement ants, to discover what differences this invasive species has on habitats
Distribution and Ecology of Invasive Ants
This project examines exactly how invasive specific types of ants are, and what effect that has on the ecosystem. To do so, most of the research must be compiled for the first time, as there is a lack of knowledge and research on this subject. Through former research, Tillberg finds that there are invasive pavement ants in Oregon state parks, but due to a lack of research on the species, their impact is unknown. The research will follow a paired design, comparing similar areas with and without pavement ants, to discover what differences this invasive species has on habitats
2018 MAX-C/ExoMars Mission: The Orleans Mars-Analogue Rock Collection for Instrument Testing
International audienceIn order to reply to the exobiological goals of the 2018 MAX-C/ExoMars mission, the Orléans-OSUC analogue rock collection and database contains well characterised Mars analogue rocks and minerals for use in instrument testing and in situ missions
Integrin-linked kinase in muscle is necessary for the development of insulin resistance in diet-induced obese mice
Diet-induced muscle insulin resistance is associated with expansion of extracellular matrix (ECM) components, such as collagens, and the expression of collagen-binding integrin, α2β1. Integrins transduce signals from ECM via their cytoplasmic domains, which bind to intracellular integrin-binding proteins. The integrin-linked kinase (ILK)-PINCH-parvin (IPP) complex interacts with the cytoplasmic domain of β-integrin subunits and is critical for integrin signaling. In this study we defined the role of ILK, a key component of the IPP complex, in diet-induced muscle insulin resistance. Wild-type (ILK(lox/lox)) and muscle-specific ILK-deficient (ILK(lox/lox)HSAcre) mice were fed chow or a high-fat (HF) diet for 16 weeks. Body weight was not different between ILK(lox/lox) and ILK(lox/lox)HSAcre mice. However, HF-fed ILK(lox/lox)HSAcre mice had improved muscle insulin sensitivity relative to HF-fed ILK(lox/lox) mice, as shown by increased rates of glucose infusion, glucose disappearance, and muscle glucose uptake during a hyperinsulinemic-euglycemic clamp. Improved muscle insulin action in the HF-fed ILK(lox/lox)HSAcre mice was associated with increased insulin-stimulated phosphorylation of Akt and increased muscle capillarization. These results suggest that ILK expression in muscle is a critical component of diet-induced insulin resistance, which possibly acts by impairing insulin signaling and insulin perfusion through capillaries
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