Genetic divergence for agronomic traits in common bean lines can be analyzed with and without multicollinearity and by different hierarchical methods, which can lead to errors in the interpretation of ...

Abstract: The objective of this work was to evaluate the interference of sample size on multicollinearity diagnosis in path analysis. From the analyses of productive traits of cherry tomato, two ...

In contrast to statistical inference on the regression coefficients, Multicollinearity does not impact the model’s overall fit to the observed response variable data and prediction (Alin, 2010). The ...

The paper considers the problem of detecting multicollinearity in a fuzzy linear regression model. An approach is proposed to identify the fuzzy linear dependence of vectors. This approach allows ...

Influential observation is one which either individually or together with several other observations has a demonstrably large impact on the values of various estimates of regression coefficient. It ...

Discover the impact of heteroscedasticity and multicollinearity on econometrics data. Explore detection methods and find the best approach for accurate estimation. Study results reveal the ...

Recent reports of an inverse association between dietary calcium intake and hypertension stimulated this analysis of the relationship of blood pressure to more than 20 dietary factors among a group of ...