Forthcoming, Journal of Peace Research, 45 (5), September 2008.

Bias in epidemiological studies of conflict mortality by Neil F. Johnson¹, Michael Spagat², Sean Gourley¹, Jukka-Pekka Onnela¹, Gesine Reinert³ is a working paper with the Households in Conflict Network in their new series on Research Design.

¹ Department of Physics, Oxford University, Oxford OX1 3PU, U. K.
² Department of Economics, Royal Holloway, University of London, TW20 0EX, U. K.
³ Department of Statistics, Oxford University, Oxford OX1 3TG, U. K.

ABSTRACT:
Cluster sampling has recently been used to estimate the mortality in various conflicts around the world. The Burnham et al. (2006) study on Iraq employs a new variant of this cluster sampling methodology. The stated methodology of Burnham et al. (2006) is to (1) select a random main street, (2) choose a random cross street to this main street, and (3) select a random household on the cross street to start the process. We show that this new variant of the cluster sampling methodology can introduce an unexpected, yet substantial, bias into the resulting estimates as such streets are a natural habitat for patrols, convoys, police stations, road-blocks, cafes and street-markets. This bias comes about because the residents of households on cross-streets to the main streets are more likely to be exposed to violence than those living further away. Here we develop a mathematical model to gauge the size of the bias and use the existing evidence to propose values for the parameters that underlie the model. Our research suggests that the Burnham et al. (2006) study of conflict mortality in Iraq may represent a substantial overestimate of mortality. We provide a sensitivity analysis to help readers to tune their own judgments on the extent of this bias by varying the parameter values. Future progress on this subject will benefit from the release of high-resolution data by the authors of Burnham et al. (2006).

Matlab code used for calculations in the paper (.pdf file)

Matlab code used for claculation in the paper (.m file) hosted by Claire Blackman

Matlab code used for calculations in the paper (.m file) hosted by Economics