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Full-Text Articles in Physical Sciences and Mathematics
Estimation Of Hiv Incidence Using Multiple Biomakers, Ron Brookmeyer, Jacob Konikoff, Oliver Laeyendecker, Susan Eshleman
Estimation Of Hiv Incidence Using Multiple Biomakers, Ron Brookmeyer, Jacob Konikoff, Oliver Laeyendecker, Susan Eshleman
Ron Brookmeyer
The incidence of human immunodeficiency virus (HIV) is the rate at which new HIV infections occur in populations. The development of accurate, practical, and cost-effective approaches to estimation of HIV incidence is a priority among researchers in HIV surveillance because of limitations with existing methods. In this paper, we develop methods for estimating HIV incidence rates using multiple biomarkers in biological samples collected from a cross-sectional survey. An advantage of the method is that it does not require longitudinal follow-up of individuals. We use assays for BED, avidity, viral load, and CD4 cell count data from clade B samples collected …
Application Of A Data Mining Framework For The Identification Of Agricultural Production Areas In Wa , Yunous Vagh, Leisa Armstrong, Dean Diepeveen
Application Of A Data Mining Framework For The Identification Of Agricultural Production Areas In Wa , Yunous Vagh, Leisa Armstrong, Dean Diepeveen
Leisa Armstrong
This paper will propose a data mining framework for the identification of agricultural production areas ill WA. The data mining (DM) framework was developed with the aim of enhancing the analysis of agricultural datasets compared to currently used statistical methods. The DM framework is a synthesis of different technologies brought together for the purpose of enhancing the interrogation of these datasets. The DM framework is based on the data, information, knowledge and wisdom continuum as a horizontal axis, with DM and online analytical processing (OLAP) forming the vertical axis. In addition the DM framework incorporates aspects of data warehousing phases, …
Beyond Multiple Regression: Using Commonality Analysis To Better Understand R2 Results, Russell Warne
Beyond Multiple Regression: Using Commonality Analysis To Better Understand R2 Results, Russell Warne
Russell T Warne
Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated independent variables. Commonality analysis—heretofore rarely used in gifted education research—is a statistical method that partitions the explained variance of a dependent variable into nonoverlapping parts according to the independent variable(s) that are related to each portion. This Methodological Brief includes an example of commonality analysis and equations for researchers who wish to conduct their …