Re-sampling Techniques in Count Data Regression Models
Modeling count variables is a common task in many application areas such as economics, social sciences, and medicine. The classical Poisson regression model for count data is often used and it is limited in these disciplines since count data sets typically exhibit overdispersion, so negative binomia...
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| Format: | Article |
| Language: | Arabic |
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College of Computer Science and Mathematics, University of Mosul
2012-12-01
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| Series: | المجلة العراقية للعلوم الاحصائية |
| Subjects: | |
| Online Access: | https://stats.mosuljournals.com/article_67727_afe83c7a71922ae1727a1c968f90d61a.pdf |
| _version_ | 1817968176663625728 |
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| author | Zakariya Y. Algamal |
| author_facet | Zakariya Y. Algamal |
| author_sort | Zakariya Y. Algamal |
| collection | DOAJ |
| description | Modeling count variables is a common task in many application areas such as economics, social sciences, and medicine. The classical Poisson regression model for count data is often used and it is limited in these disciplines since count data sets typically exhibit overdispersion, so negative binomial regression can be used. We use a jackknife- after- bootstrap procedure to assess the error in the bootstrap estimated parameters. The method is illustrated through two real examples. The results suggest that the jackknife- after- bootstrap method provides a reliable alternative to traditional methods particularly in small to moderate samples. |
| first_indexed | 2024-04-13T20:05:34Z |
| format | Article |
| id | doaj.art-fe661c31c8b1468bbf50cc02b912ef22 |
| institution | Directory Open Access Journal |
| issn | 1680-855X 2664-2956 |
| language | Arabic |
| last_indexed | 2024-04-13T20:05:34Z |
| publishDate | 2012-12-01 |
| publisher | College of Computer Science and Mathematics, University of Mosul |
| record_format | Article |
| series | المجلة العراقية للعلوم الاحصائية |
| spelling | doaj.art-fe661c31c8b1468bbf50cc02b912ef222022-12-22T02:32:03ZaraCollege of Computer Science and Mathematics, University of Mosulالمجلة العراقية للعلوم الاحصائية1680-855X2664-29562012-12-01122152510.33899/iqjoss.2012.6772767727Re-sampling Techniques in Count Data Regression ModelsZakariya Y. AlgamalModeling count variables is a common task in many application areas such as economics, social sciences, and medicine. The classical Poisson regression model for count data is often used and it is limited in these disciplines since count data sets typically exhibit overdispersion, so negative binomial regression can be used. We use a jackknife- after- bootstrap procedure to assess the error in the bootstrap estimated parameters. The method is illustrated through two real examples. The results suggest that the jackknife- after- bootstrap method provides a reliable alternative to traditional methods particularly in small to moderate samples.https://stats.mosuljournals.com/article_67727_afe83c7a71922ae1727a1c968f90d61a.pdfpoisson regressionoverdispersionnegative binomial regressionbootstrapjackknifeafter |
| spellingShingle | Zakariya Y. Algamal Re-sampling Techniques in Count Data Regression Models المجلة العراقية للعلوم الاحصائية poisson regression overdispersion negative binomial regression bootstrap jackknife after |
| title | Re-sampling Techniques in Count Data Regression Models |
| title_full | Re-sampling Techniques in Count Data Regression Models |
| title_fullStr | Re-sampling Techniques in Count Data Regression Models |
| title_full_unstemmed | Re-sampling Techniques in Count Data Regression Models |
| title_short | Re-sampling Techniques in Count Data Regression Models |
| title_sort | re sampling techniques in count data regression models |
| topic | poisson regression overdispersion negative binomial regression bootstrap jackknife after |
| url | https://stats.mosuljournals.com/article_67727_afe83c7a71922ae1727a1c968f90d61a.pdf |
| work_keys_str_mv | AT zakariyayalgamal resamplingtechniquesincountdataregressionmodels |