MPhil/PhD Statistics (Assessing inequality in the Criminal Justice System using novel causal inference methods and Bayesian spatial models)

点击翻译按钮获取中文摘要

The aim of this project is to use causal inference methods to corroborate the conclusions of the Lammy Review (2017) by quantifying the impact of discrimination in sentencing using Data First: Criminal Justice System Linked Datasets.The overall aims are to understand:Whether and how early life course events such as education and being in care are impacted by systematic discriminationHow early experiences impact involvement with the Criminal Justice system later in life and whether discrimination continues to play a part Whether there are regional differences (e.g. London vs the rest of England)The following methods are to be used:Longitudinal mediation analysis to determine the impact of being in care and educational attainment on later outcomes such as violence and arrest and how discrimination confounds these relationships;Proximal causal inference to determine the impact of discrimination on the pathway between life events in relation to violence and involvement with the Criminal Justice System;Bayesian Spatial analysis to address spatial/regional differences in discrimination.