Session: Tackling selection bias in sentencing data analysis

Time: Thursday 5th July, 09:15 - 10:45

Convenors:

Dr Jose Pina-Sanchez (University of Leeds)
Dr Sara Geneletti (London School of Economics)

Abstract Details

Analyses of judicial decisions tend to focus on the duration of custodial sentences. These types of sentences are however quite rare (8\% of the total in England and Wales), which generates a problem of selection bias. We suggest a new approach based on finite mixture modelling, Bayesian statistics and aggregated views from judges, capable of modelling simultaneously all types of sentences. Distributions of the relative severity of the four major sentence outcomes (fines, community orders, suspended sentences, and custody) are specified into the same mixture model, making the most of the information available in sentence data.

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Presenter: Jose Pina-Sanchez

Tackling Selection Bias in Sentence Data Analysis

The level of the session is: Accessible

Presentation details

Presentation 1

Start time: 09:15

Presentation title: Tackling selection bias in sentencing data analysis

Presenters:

Dr Jose Pina-Sánchez (University of Leeds)
Dr Sara Geneletti (London School of Economics)