Evaluating epidemiological evidence: A simple test
Epidemiological studies that investigate the relationships between health behaviors and diseases may be affected by both known and unknown confounding factors. Alcohol use is one of these behaviors that have been intensively investigated in epidemiological studies. This manuscript introduced a simpl...
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| Format: | Journal Article |
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Ivyspring International Publisher
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/3911 |
| _version_ | 1848744364446056448 |
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| author | Liang, Wenbin |
| author_facet | Liang, Wenbin |
| author_sort | Liang, Wenbin |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Epidemiological studies that investigate the relationships between health behaviors and diseases may be affected by both known and unknown confounding factors. Alcohol use is one of these behaviors that have been intensively investigated in epidemiological studies. This manuscript introduced a simple test that can identify confounded epidemiological studies. This approach is sensitive to both known and unknown confounders. It provides a new perspective to develop measures for evidence selection in the future. |
| first_indexed | 2025-11-14T06:00:17Z |
| format | Journal Article |
| id | curtin-20.500.11937-3911 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:00:17Z |
| publishDate | 2013 |
| publisher | Ivyspring International Publisher |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-39112017-09-13T14:31:37Z Evaluating epidemiological evidence: A simple test Liang, Wenbin evidence-based medicine causality epidemiology bias health behaviors Epidemiological studies that investigate the relationships between health behaviors and diseases may be affected by both known and unknown confounding factors. Alcohol use is one of these behaviors that have been intensively investigated in epidemiological studies. This manuscript introduced a simple test that can identify confounded epidemiological studies. This approach is sensitive to both known and unknown confounders. It provides a new perspective to develop measures for evidence selection in the future. 2013 Journal Article http://hdl.handle.net/20.500.11937/3911 10.7150/ijms.6455 Ivyspring International Publisher fulltext |
| spellingShingle | evidence-based medicine causality epidemiology bias health behaviors Liang, Wenbin Evaluating epidemiological evidence: A simple test |
| title | Evaluating epidemiological evidence: A simple test |
| title_full | Evaluating epidemiological evidence: A simple test |
| title_fullStr | Evaluating epidemiological evidence: A simple test |
| title_full_unstemmed | Evaluating epidemiological evidence: A simple test |
| title_short | Evaluating epidemiological evidence: A simple test |
| title_sort | evaluating epidemiological evidence: a simple test |
| topic | evidence-based medicine causality epidemiology bias health behaviors |
| url | http://hdl.handle.net/20.500.11937/3911 |