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Compared with the analysis for each trait separately, Bayesian joint mapping improves statistical power, provides stronger evidence of QTL detection, and increases precision in estimation of parameter and QTL position.
As such, confirmatory factor analysis focuses analyses on the activation of hypothesized networks as a whole, improves statistical power by modeling measurement error, and provides a theory-based approach to data reduction with a robust statistical basis.
This analysis method avoids multiple testing issues and improves statistical power compared to the conventional approach.
Our results showed that incorporating information regarding functional variants obtained from existing prediction algorithms improves statistical power under certain conditions, particularly when the proportion of causative variants is moderate.
Simulation studies showed that the use of predicting algorithms to identify potentially functional variants improves statistical power under certain conditions, especially when the proportion of functional variants is moderate.
Similar to each of the first five dimensions, the sixth dimension also improves statistical power.
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Longitudinal analysis on the measures produced by these methods are shown to have improved statistical power.
Many studies use GEO data to shape hypotheses and improve statistical power.
We demonstrate that FGRF has comparable statistical power with existing methods when there is no genetic heterogeneity, but can improve statistical power when there is genetic heterogeneity across families.
Females were oversampled to improve statistical power for sex-specific analyses.
However, translating a reduction in COV to improve statistical power requires additional assumptions, e.g., regarding the potential treatment effect [50].
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