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Risk Analysis

, Volume 19, Issue 4, pp 675–683 | Cite as

Simultaneous Analysis of Individual and Aggregate Responses in Psychometric Data Using Multilevel Modeling

  • Ian H. Langford
  • Claire Marris
  • Anné-Lise McDonald
  • Harvey Goldstein
  • Jon Rasbash
  • Tim O'Riordan
Article

Abstract

Psychometric data on risk perceptions are often collected using the method developed by Slovic, Fischhoff, and Lichtenstein, where an array of risk issues are evaluated with respect to a number of risk characteristics, such as how dreadful, catastrophic or involuntary exposure to each risk is. The analysis of these data has often been carried out at an aggregate level, where mean scores for all respondents are compared between risk issues. However, this approach may conceal important variation between individuals, and individual analyses have also been performed for single risk issues. This paper presents a new methodological approach using a technique called multilevel modelling for analysing individual and aggregated responses simultaneously, to produce unconditional and unbiased results at both individual and aggregate levels of the data. Two examples are given using previously published data sets on risk perceptions collected by the authors, and results between the traditional and new approaches compared. The discussion focuses on the implications of and possibilities provided by the new methodology.

risk perceptions psychometric paradigm multilevel modeling random coefficient models 

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Copyright information

© Society for Risk Analysis 1999

Authors and Affiliations

  • Ian H. Langford
    • 1
  • Claire Marris
    • 2
  • Anné-Lise McDonald
    • 1
  • Harvey Goldstein
    • 3
  • Jon Rasbash
    • 3
  • Tim O'Riordan
    • 1
  1. 1.Centre for Social and Economic Research on the Global Environment (CSERGE)University of East Anglia, Norwich and University CollegeLondon; Multilevel Models Project, Mathematical Sciences, Institute of Education, University of London
  2. 2.Independent ResearcherParisFrance
  3. 3.Multilevel Models Project, Mathematical Sciences, Institute of EducationUniversity of LondonUSA

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