The impact of predictor variable(s) with skewed cell probabilities on wald tests in binary logistic regression
Journal of Modern Applied Statistical Methods, ISSN: 1538-9472, Vol: 16, Issue: 2, Page: 40-80
2017
- 6Citations
- 2,498Usage
- 20Captures
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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.
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Metrics Details
- Citations6
- Citation Indexes6
- CrossRef5
- Usage2,498
- Downloads2,306
- 2,306
- Abstract Views192
- Captures20
- Readers20
- 20
Article Description
A series of simulation studies are reported that investigated the impact of a skewed predictor(s) on the Type I error rate and power of the Wald test in a logistic regression model. Five simulations were conducted for three different regression models. A detailed description of the impact of skewed cell predictor probabilities and sample size provide guidelines for practitioners wherein to expect the greatest problems.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85037027547&origin=inward; http://dx.doi.org/10.22237/jmasm/1509494640; https://jmasm.com/index.php/jmasm/article/view/927; https://digitalcommons.wayne.edu/jmasm/vol16/iss2/4; https://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=2457&context=jmasm; https://dx.doi.org/10.22237/jmasm/1509494640
The Netherlands Press
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