Introduction to methods for analysis of combined individual and aggregate social science data

Best, Nicky and Fisher, Stephen and Key, Jane (2011) Introduction to methods for analysis of combined individual and aggregate social science data. In: Introduction to methods for analysis of combined individual and aggregate social science data, 21 March 2011, Oxford. (Unpublished)

[thumbnail of BIAS_HRR_workshop.pdf]
Preview
PDF
BIAS_HRR_workshop.pdf - Presentation

Download (3MB) | Preview

Abstract

The lecture notes from this workshop provide an introduction to a new class of multilevel models – termed hierarchical related regressions (HRR) – for estimating individual-level associations using a combination of aggregate (group level) and individual-level data. HRR differs from other methods by enabling analysts to model individual and aggregate data simultaneously, while including information on the dependent variable at the aggregate level (e.g. constituency election results), and data from aggregation units not available at the individual level (e.g. census data from all constituencies or output areas in the country). The workshop will also discuss HRR as a method of improving ecological inference (analyses that aim to make inference on the relationship between individual-level quantities using aggregate data). The HRR models combine features of standard ecological regression models for aggregate data and multilevel models for clustered individual-level data, and have been shown to reduce bias and improve precision in many situations.

Item Type: Conference or Workshop Item (Lecture)
Subjects: 5. Quantitative Data Handling and Data Analysis > 5.3 Small Area Estimation
5. Quantitative Data Handling and Data Analysis > 5.5 Regression Methods
5. Quantitative Data Handling and Data Analysis > 5.6 Multilevel Modelling
5. Quantitative Data Handling and Data Analysis > 5.17 Quantitative Approaches (other)
Depositing User: BIAS user
Date Deposited: 29 Jun 2011 09:21
Last Modified: 14 Jul 2021 13:54
URI: https://eprints.ncrm.ac.uk/id/eprint/1821

Actions (login required)

View Item
View Item