Case‐control data analysis for randomly pooled biomarkers

Pooled study designs, where individual biospecimens are combined prior to measurement via a laboratory assay, can reduce lab costs while maintaining statistical efficiency. Analysis of the resulting pooled measurements, however, often requires specialized techniques. Existing methods can effectively estimate the relation between a binary outcome and a continuous pooled exposure when pools are matched on disease status. When pools are of mixed disease status, however, the existing methods may not be applicable. By exploiting characteristics of the gamma distribution, we propose a flexible method for estimating odds ratios from pooled measurements of mixed and matched status. We use simulation studies to compare consistency and efficiency of risk effect estimates from our proposed methods to existing methods. We then demonstrate the efficacy of our method applied to an analysis of pregnancy outcomes and pooled cytokine concentrations. Our proposed approach contributes to the toolkit of available methods for analyzing odds ratios of a pooled exposure, without restricting pools to be matched on a specific outcome.     

Skew or third moment of bacterial generation times

We studied two statistical hypotheses for the occurrence of cellular division and compared these hypotheses to available data. The two models were tested by observed distributions of cellular size during steady-state growth. The 30-year-old sloppy size model could be rejected, whereas the recently developed incremental size proposal could not. The latter proposition was accepted by default. We concluded that the time between successive divisions is not simply derived from extant size at cellular division, but rather from interdivisional size increment. We therefore propose that cellular division is regulated by the need of cells at birth to accumulate a certain amount of mass or something related to mass before division. Received: 22 December 1996 / Accepted: 6 August 1997     

Negative skewness and negative correlations in spatial competition models

We consider a population of identical biological entities that compete with each other for space and derive, under rather weak assumptions, some statistical properties of the sizes (e.g. biomasses) of the individuals. It is proved, for example, that, during the early stages of competition, their size distribution becomes negatively skewed and the sizes of neighbouring individuals become negatively correlated. The results are proved for a regular periodic array of centres of the individuals where they can be compared with data on plantations.