Statistical Inference Based on Pooled Data: A Moment-Based Estimating Equation Approach |
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Authors: | Howard D. Bondell Aiyi Liu Enrique F. Schisterman |
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Affiliation: | a Department of Statistics, North Carolina State University, Raleigh, USAb Division of Epidemiology, Statistics and Prevention Research, National Institute of Child Health and Human Development, Bethesda, MD, USA |
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Abstract: | We consider statistical inference on parameters of a distribution when only pooled data are observed. A moment-based estimating equation approach is proposed to deal with situations where likelihood functions based on pooled data are difficult to work with. We outline the method to obtain estimates and test statistics of the parameters of interest in the general setting. We demonstrate the approach on the family of distributions generated by the Box-Cox transformation model, and, in the process, construct tests for goodness of fit based on the pooled data. |
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Keywords: | Pooling biospecimens set-based observations moments Box-Cox transformation goodness-of-fit lognormal distribution |
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