The analysis of multi-environment trials (MET) data in plant breeding and agricultural research is inherently challenging, with conventional ANOVA-based methods exhibiting limitations as the ...

Existing results on residual variance estimation in high-dimensional linear models depend on sparsity in the underlying signal. Our results require no sparsity assumptions and imply that the residual ...

Rubin continued, “We encourage health economists, health technology assessment entities, patients, investors, and innovators to treat this GCEA paper as a user guide on how to do better cost ...

Hands-on short course on analysis of variance (ANOVA) using SPSS. Learn how to choose, run, interpret and report a variety of ANOVA models within the general linear model (GLM) function.

Notable in this new edition:Fully updated and expanded text reflects the most recent developments in the AVE methodRearranged and reorganized discussions of application and theory enhance text's ...

Conclusion We demonstrate the application of multilevel linear spline models for examining growth trajectories when both antenatal and postnatal measures of growth are available. The approach may be ...

Variance quantifies the spread of data points in a dataset and offers valuable insights into how consistent or varied the data is. By using Excel’s built-in functions, you can quickly find variance ...

Unlike other models like first-touch or last-touch, which give full credit to either the first or last interaction, the linear model appreciates the contribution of multiple touchpoints in marketing ...