Interpretation of regression coefficients under a latent variable regression model

By Alison J. Burnham, John F. MacGregor, R. Viveros. 2001

47 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/89aeedbf9d772dfedce9ddf23011bbc18d8bbff2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Santiago A. Bortolato
2. E. Arancibia
3. Natalia Sorol
4. Alejandro C. Olivieri
5. Nicolaas (Klaas) M. Faber

In Statistics and Probability

1. Santiago A. Bortolato
2. E. Arancibia
3. Alejandro C. Olivieri
4. Natalia Sorol

Citations in the corpus

• Visible/near infrared-partial least-squares analysis of Brix in sugar cane juice: A test field for variable selection methods (2010, background): “It should be noticed that the intuitive power of regression coefficients to aid in variable selection has been challenged [13–15].”
• Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. (2003, unknown): “For other methods and more challenging data sets, more elaborate calculations are often necessary (Burnham et al. 1996, 1999, 2001; Denham 1997).”