Implications of confounding from unmodeled interactions between explanatory variables when using latent variable regression models to make inferences
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Chemometrics"
DOI: 10.1002/cem.3531
Abstract: With linear dependency between the explanatory variables, partial least squares (PLS) regression is commonly used for regression analysis. If the response variable correlates to a high degree with the explanatory variables, a model with excellent… read more here.
Keywords: explanatory variables; make inferences; implications confounding; confounding unmodeled ... See more keywords
Leveraging summary statistics to make inferences about complex phenotypes in large biobanks
Sign Up to like & getrecommendations! Published in 2019 at "Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing"
DOI: 10.1142/9789813279827_0036
Abstract: As genetic sequencing becomes less expensive and data sets linking genetic data and medical records (e.g., Biobanks) become larger and more common, issues of data privacy and computational challenges become more necessary to address in… read more here.
Keywords: leveraging summary; complex phenotypes; make inferences; inferences complex ... See more keywords