Consistent Estimation of Generalized Linear Models with High Dimensional Predictors via Stepwise Regression Article Swipe
Alex Pijyan
,
Qi Zheng
,
Hyokyoung G. Hong
,
Yi Li
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/e22090965
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3390/e22090965
Predictive models play a central role in decision making. Penalized regression approaches, such as least absolute shrinkage and selection operator (LASSO), have been widely used to construct predictive models and explain the impacts of the selected predictors, but the estimates are typically biased. Moreover, when data are ultrahigh-dimensional, penalized regression is usable only after applying variable screening methods to downsize variables. We propose a stepwise procedure for fitting generalized linear models with ultrahigh dimensional predictors. Our procedure can provide a final model; control both false negatives and false positives; and yield consistent estimates, which are useful to gauge the actual effect size of risk factors. Simulations and applications to two clinical studies verify the utility of the method.
Related Topics
Concepts
Lasso (programming language)
Linear regression
Regression
Stepwise regression
Feature selection
Linear model
Generalized linear model
Regression analysis
Computer science
Mathematics
Statistics
Model selection
False positive paradox
False positives and false negatives
Econometrics
Artificial intelligence
World Wide Web
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/e22090965
- https://www.mdpi.com/1099-4300/22/9/965/pdf?version=1599114614
- OA Status
- gold
- Cited By
- 10
- References
- 58
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3081922164
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3081922164Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/e22090965Digital Object Identifier
- Title
-
Consistent Estimation of Generalized Linear Models with High Dimensional Predictors via Stepwise RegressionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-08-31Full publication date if available
- Authors
-
Alex Pijyan, Qi Zheng, Hyokyoung G. Hong, Yi LiList of authors in order
- Landing page
-
https://doi.org/10.3390/e22090965Publisher landing page
- PDF URL
-
https://www.mdpi.com/1099-4300/22/9/965/pdf?version=1599114614Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1099-4300/22/9/965/pdf?version=1599114614Direct OA link when available
- Concepts
-
Lasso (programming language), Linear regression, Regression, Stepwise regression, Feature selection, Linear model, Generalized linear model, Regression analysis, Computer science, Mathematics, Statistics, Model selection, False positive paradox, False positives and false negatives, Econometrics, Artificial intelligence, World Wide WebTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 2, 2023: 2, 2022: 3Per-year citation counts (last 5 years)
- References (count)
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58Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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