Centre for Multilevel Modelling

This project aims to refine and disseminate a recently proposed multilevel modelling approach to studying intersectionality of individual outcomes. That is, the notion that individuals' various social and political identities result in unique combinations of discrimination and privilege. More information

Quite recently, teachers were asked to predict students’ GCSE and A-level marks because exams could not take place due to the Covid-19 crisis. This sparked public debates about a concern that has been frequently highlighted over the last decades: teacher judgements might be biased putting students from certain groups of the population at disadvantage.

Social or ethnic teacher bias is problematic because teachers have an important influence on students’ self-esteem, academic motivation and school achievement. Moreover, in many countries they make critical decisions about ability groupings, school tracking and grade retention. If teachers underassess the performance, effort or enjoyment in school of certain students, they can harm students’ self-esteem and hinder them to achieve the education and life outcomes they could have attained through their abilities. Research shows that positive teacher-student relationships, which are characterised by openness and mutual understanding, are highly beneficial for students, especially in primary school. Teachers’ inaccurate and possibly biased perceptions of students can be detrimental for teacher-student relationships. More information

The awarding of the 2020 GCSE and A-Level exam grades in England was widely viewed as a ‘fiasco’. When COVID-19 forced the cancellation of exams, DfE and Ofqual asked centres (schools and colleges) to submit Centre Assessment Grades (CAGs) and rankings. Namely, the grades and rank orders within their centres that teachers thought students would have achieved had they sat their exams. Ofqual, tasked with preventing grade inflation and ensuring grading consistency, viewed students’ CAGs as overly optimistic and so replaced them with calculated grades predicted via their Direct Centre-level Performance (DCP) algorithm. The result was that 40% of CAGs were downgraded by one or more grades. After public outcry, Education Secretary Gavin Williamson instructed Ofqual to revert to the original CAGs. Students are accepted into universities and employment based on their GCSE and A-level grades. Their grades directly impact their immediate future. It is therefore vitally important for society to understand the extent to which students’ grades were unfairly awarded in 2020 and 2021 with biases potentially varying across individual centres and by student and school characteristics. Our overarching aim is therefore to conduct an independent and rigorous secondary data analysis of the 2020 and 2021 GCSE and A-level exam grades to explore not just what went wrong statistically, but to identify what could be improved statistically when predicting grades in future years. More information

This project aims to better understand  multilevel models for studying the stability of school value-added effects for school accountability and improvement. Particular focus will be on studying their sensitivity to sample size requirements, student mobility, and changing student intake sociodemographic composition. More information

Gallery of Multilevel Papers

This three-day course held in January and July every year provides an introduction to multilevel modelling and includes software practicals in your choice of software: MLwiN, R or Stata. We focus on multilevel modelling for continuous and binary responses (dependent or outcome variables) when the data are clustered (nested or hierarchical). More information

Graduated modules starting from an introduction to quantitative research, progressing to multilevel modelling of continuous and binary data. More information and course modules.

Including Random Intercept Models, Residuals, Measuring Dependency, Covariance and Correlation Matrices, and Random Slope Models.  More information.

The Advanced Quantitative Methods (AQM) pathway of the SWDTP offers ESRC +3 and 1+3 postgraduate research training in the application of advanced quantitative methods in the social sciences and health. More information.