A randomization method to control the type I error rates in best subset regression
Journal of Modern Applied Statistical Methods, ISSN: 1538-9472, Vol: 7, Issue: 2, Page: 398-407
2008
- 3Citations
- 303Usage
- 4Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations3
- Citation Indexes3
- CrossRef2
- Usage303
- Downloads266
- Abstract Views37
- Captures4
- Readers4
Article Description
A randomization method for the assessment of statistical significance for best subsets regression is given. The procedure takes into account the number of potential predictors and the inter-dependence between predictors. The approach corrects a non-trivial problem with Type I errors and can be used to assess individual variable significance. © 2008 JMASM, Inc.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=82055189719&origin=inward; http://dx.doi.org/10.22237/jmasm/1225512240; https://jmasm.com/index.php/jmasm/article/view/374; https://digitalcommons.wayne.edu/jmasm/vol7/iss2/5; https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1453&context=jmasm; https://dx.doi.org/10.22237/jmasm/1225512240
The Netherlands Press
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know