Model justification and stratification for confounding of Chlamydia trachomatis disease
This study involves statistical analysis of reported cases of sexually transmitted diseases (STDs) of Chlamydia infection in the United States. The data are collected from 2007 to 2016. The research studies incidence of sexually transmitted diseases and survival among different age groups and gender...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Intercollegiate Biomathematics Alliance
2019-01-01
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| Series: | Letters in Biomathematics |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23737867.2019.1654418 |
| _version_ | 1819020099714023424 |
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| author | Sarada Ghosh G. P. Samanta |
| author_facet | Sarada Ghosh G. P. Samanta |
| author_sort | Sarada Ghosh |
| collection | DOAJ |
| description | This study involves statistical analysis of reported cases of sexually transmitted diseases (STDs) of Chlamydia infection in the United States. The data are collected from 2007 to 2016. The research studies incidence of sexually transmitted diseases and survival among different age groups and gender and race factors which influence the incidence in the target population. In this work, log-binomial, logit model, probit model and complementary log–log model are used to establish a suitable model (using different criteria) that can predict the survival of infected people with STDs based on their age, gender and race. Here we have also focused on stratification: a statistical technique that allows to control for confounding by creating two or more categories. The Mantel–Haenszel formula allows to calculate an overall, unconfounded, that is adjusted, effect estimate for a specific outcome by combining (pooling) stratum-specific relative risks and odds ratios. Simulation is based on R-software. |
| first_indexed | 2024-12-21T03:45:50Z |
| format | Article |
| id | doaj.art-0532466a5b4c47bda46e777828f9918b |
| institution | Directory Open Access Journal |
| issn | 2373-7867 |
| language | English |
| last_indexed | 2024-12-21T03:45:50Z |
| publishDate | 2019-01-01 |
| publisher | Intercollegiate Biomathematics Alliance |
| record_format | Article |
| series | Letters in Biomathematics |
| spelling | doaj.art-0532466a5b4c47bda46e777828f9918b2022-12-21T19:17:05ZengIntercollegiate Biomathematics AllianceLetters in Biomathematics2373-78672019-01-010011310.1080/23737867.2019.16544181654418Model justification and stratification for confounding of Chlamydia trachomatis diseaseSarada Ghosh0G. P. Samanta1Indian Institute of Engineering Science and TechnologyIndian Institute of Engineering Science and TechnologyThis study involves statistical analysis of reported cases of sexually transmitted diseases (STDs) of Chlamydia infection in the United States. The data are collected from 2007 to 2016. The research studies incidence of sexually transmitted diseases and survival among different age groups and gender and race factors which influence the incidence in the target population. In this work, log-binomial, logit model, probit model and complementary log–log model are used to establish a suitable model (using different criteria) that can predict the survival of infected people with STDs based on their age, gender and race. Here we have also focused on stratification: a statistical technique that allows to control for confounding by creating two or more categories. The Mantel–Haenszel formula allows to calculate an overall, unconfounded, that is adjusted, effect estimate for a specific outcome by combining (pooling) stratum-specific relative risks and odds ratios. Simulation is based on R-software.http://dx.doi.org/10.1080/23737867.2019.1654418Chlamydia trachomatisbinomial regressionlinear modelsodds ratiorelative risk |
| spellingShingle | Sarada Ghosh G. P. Samanta Model justification and stratification for confounding of Chlamydia trachomatis disease Letters in Biomathematics Chlamydia trachomatis binomial regression linear models odds ratio relative risk |
| title | Model justification and stratification for confounding of Chlamydia trachomatis disease |
| title_full | Model justification and stratification for confounding of Chlamydia trachomatis disease |
| title_fullStr | Model justification and stratification for confounding of Chlamydia trachomatis disease |
| title_full_unstemmed | Model justification and stratification for confounding of Chlamydia trachomatis disease |
| title_short | Model justification and stratification for confounding of Chlamydia trachomatis disease |
| title_sort | model justification and stratification for confounding of chlamydia trachomatis disease |
| topic | Chlamydia trachomatis binomial regression linear models odds ratio relative risk |
| url | http://dx.doi.org/10.1080/23737867.2019.1654418 |
| work_keys_str_mv | AT saradaghosh modeljustificationandstratificationforconfoundingofchlamydiatrachomatisdisease AT gpsamanta modeljustificationandstratificationforconfoundingofchlamydiatrachomatisdisease |