A generalized estimating equation method for fitting autocorrelated ordinal score data with an application in horticultural research

N. R. Parsons, R. N. Edmondson and S. G. Gilmour

Journal of the Royal Statistical Society Series C, 2006, vol. 55, issue 4, 507-524

Abstract: Summary. Generalized estimating equations for correlated repeated ordinal score data are developed assuming a proportional odds model and a working correlation structure based on a first‐order autoregressive process. Repeated ordinal scores on the same experimental units, not necessarily with equally spaced time intervals, are assumed and a new algorithm for the joint estimation of the model regression parameters and the correlation coefficient is developed. Approximate standard errors for the estimated correlation coefficient are developed and a simulation study is used to compare the new methodology with existing methodology. The work was part of a project on post‐harvest quality of pot‐plants and the generalized estimating equation model is used to analyse data on poinsettia and begonia pot‐plant quality deterioration over time. The relationship between the key attributes of plant quality and the quality and longevity of ornamental pot‐plants during shelf and after‐sales life is explored.

Date: 2006
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