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Alternatively, one may use regression of y on p to provide a fast approximation (Haley and Knott 1992).
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Bearing this in mind, researchers may use linear regression, which is simple and implemented in most statistical packages, in QTL association under selective genotyping.
However, given that the returns to innovation are highly skewed and that growth rates distributions are heavy-tailed, it may be misleading to use regression techniques that focus on the 'average effect for the average firm'.
Noticing the importance of age effect, one may use a linear regression with age included as a covariate when analyze methylation data with multiple conditions, such as cancer types.
In the context of an AD-MA, this is known as meta-regression and may use study level covariates or aggregated patient level information.
Second, researchers may use logistic or Cox proportional hazards regression analyses for risk prediction, which do account for differences in effects sizes between individual variants.
It may be argued that using regression interval mapping (and not maximum likelihood analysis) on selectively genotyped animals might lead to an estimated bias [ 25].
In the full study, this may mean data imputation using regression techniques, but in the pilot study, there will be insufficient data to carry out the regressions robustly and last observation carried forward may be used to prevent omission of patients.
Pollster.com and FiveThirtyEight.com use regression-based analyses — a method of smoothing data to account for outliers.
We decided to try using Amazon Machine Learning (AML) to train a model and perform predictions using regression analysis.
Using regression analysis.
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