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Many statistical techniques are available for estimating PMTCT of HIV while adjusting for covariates.
It is additionally important because it has many useful properties and is central to many statistical techniques.
Clinical prediction rules have been developed to assist the clinician in decision making of isolation, with utilization of many statistical techniques such as logistic regression and neural networks, for example [ 27].
Whether used in the investigation of prognostic factors or treatment effect modifiers, many statistical techniques produce measures of association that can be difficult for clinicians to apply to individual patients.
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Many statistical modelling techniques are being developed, but there remains a need to determine the most appropriate mapping techniques.
This problem arises because many statistical analysis techniques applicable to surveillance, such as Generalised Linear Mixed Models [ 4] (GLMM), depend on the assumption that observations are statistically independent.
Problematically, many statistical modeling techniques utilized in studies of neighborhood effects control for heterogeneity (variance), effectively discounting the complex relationships between environment and health that may be of particular interest (18).
Alternative approaches have been used to model the distribution of HPAI H5N1 in other regions (Williams et al., 2008), and distribution modeling can be achieved through many different statistical techniques (Elith et al., 2006).
9 Many of the statistical techniques have been employed on only gene expression data with few applied on two or more different types of data (e.g., proteomic, gene expression, and sequencing data) to predict the response of the cancer cells to drug compounds.
Therefore many statistical and numerical modeling techniques have been suggested for the ϕ′ value.
This approach, and many new bioinformatics and statistical techniques, take a gene-centric approach to analysis.
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