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Significant membership to multiple populations (e.g. >5%, Senn and Pemberton (2009)) is interpreted as admixture: The model was run using a burn-in of 5 × 10 and a run of 10 Markov chain Monte Carlo steps, under the standard model of admixed ancestry (with the parameter alpha inferred from the data, using a uniform prior) and the model of correlated allele frequency (λ = 1).
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The observed relationship and interpretation of data using a uniform-stress model has revealed fundamental differences in the nature of the microstructure present in carbon fiber produced from polyethylene compared to carbon fiber produced from polyacrylonitrile (PAN) or pitch precursors.
To create an overview of the cross-sectional relations between POP exposure and all reproductive end points and to enable a systematic and coherent assessment of strength, exposure response, and internal consistency of associations, we summarized the data using a simplified, uniform approach building on comprehensive statistical analyses in previous papers (Table 1).
Corresponding authors of these studies (n = 19) were contacted by electronic and regular mail (two electronic reminders) and invited to submit data using a standardized data extraction sheet and uniform analysis plan.
We corrected some obvious errors and re-analyzed the previous data setset using a uniform rule.
As a second objective, we considered MKL and the gain to be made by using a weighted combination of different types of data over using a uniform combination.
Data were collected using a uniform data sheet.
The data were collected using a uniform questionnaire.
Furthermore, all the procedures were performed at a single institution by 2 senior surgeons, and postoperative data were collected using a uniform, controlled protocol through the joint registry; consequently, the likelihood of differential measurement bias is reduced.
Acquisition and display of M-mode data uses a real-time uniform-frequency clock signal.
Data processing, including Irreproducible Discovery Rate (IDR) analysis, was done using a uniform data processing pipeline for both datasets.
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