دورية أكاديمية

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study

التفاصيل البيبلوغرافية
العنوان: A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study
المؤلفون: Haghighi, Mona, Johnson, Suzanne Bennett, Qian, Xiaoning, Lynch, Kristian F., Vehik, Kendra, Huang, Shuai, Rewers, Marian, Barriga, Katherine, Baxter, Judith, Eisenbarth, George, Frank, Nicole, Gesualdo, Patricia, Hoffman, Michelle, Norris, Jill, Ide, Lisa, Robinson, Jessie, Waugh, Kathleen, She, Jin Xiong, Schatz, Desmond, Hopkins, Diane, Steed, Leigh, Choate, Angela, Silvis, Katherine, Shankar, Meena, Huang, Yi Hua, Yang, Ping, Wang, Hong Jie, Leggett, Jessica, English, Kim, McIndoe, Richard, Dequesada, Angela, Haller, Michael, Anderson, Stephen W., Ziegler, Anette G., Boerschmann, Heike, Bonifacio, Ezio, Bunk, Melanie, Försch, Johannes, Henneberger, Lydia, Hummel, Michael, Hummel, Sandra, Joslowski, Gesa, Kersting, Mathilde, Knopff, Annette, Kocher, Nadja, Koletzko, Sibylle, Krause, Stephanie, Lauber, Claudia, Mollenhauer, Ulrike, Peplow, Claudia, Pflüger, Maren, Pöhlmann, Daniela, Ramminger, Claudia, Rash-Sur, Sargol, Roth, Roswith, Schenkel, Julia, Thümer, Leonore, Voit, Katja, Winkler, Christiane, Zwilling, Marina, Simell, Olli G., Nanto-Salonen, Kirsti, Ilonen, Jorma, Knip, Mikael, Veijola, Riitta, Simell, Tuula, Hyöty, Heikki, Virtanen, Suvi M., Kronberg-Kippilä, Carina, Torma, Maija, Simell, Barbara, Ruohonen, Eeva, Romo, Minna, Mantymaki, Elina, Schroderus, Heidi, Nyblom, Mia, Stenius, Aino, Lernmark, Åke, Agardh, Daniel, Almgren, Peter, Andersson, Eva, Andrén-Aronsson, Carin, Ask, Maria, Karlsson, Ulla Marie, Cilio, Corrado, Bremer, Jenny, Ericson-Hallström, Emilie, Gard, Thomas, Gerardsson, Joanna, Gustavsson, Ulrika, Hansson, Gertie, Hansen, Monica, Hyberg, Susanne, Håkansson, Rasmus, Ivarsson, Sten, Johansen, Fredrik, Larsson, Helena, Lernmark, Barbro, Markan, Maria, Massadakis, Theodosia, Melin, Jessica, Månsson-Martinez, Maria, Nilsson, Anita, Nilsson, Emma, Rahmati, Kobra, Rang, Sara, Järvirova, Monica Sedig, Sibthorpe, Sara, Sjöberg, Birgitta, Törn, Carina, Wallin, Anne, Wimar, Åsa, Hagopian, William A., Yan, Xiang, Killian, Michael, Crouch, Claire Cowen, Hay, Kristen M., Ayres, Stephen, Adams, Carissa, Bratrude, Brandi, Fowler, Greer, Franco, Czarina, Hammar, Carla, Heaney, Diana, Marcus, Patrick, Meyer, Arlene, Mulenga, Denise, Scott, Elizabeth, Skidmore, Jennifer, Small, Erin, Stabbert, Joshua, Stepitova, Viktoria, Becker, Dorothy, Franciscus, Margaret, Dalmagro-Elias Smith, Maryellen, Daftary, Ashi, Krischer, Jeffrey P., Abbondondolo, Michael, Ballard, Lori, Brown, Rasheedah, Cuthbertson, David, Eberhard, Christopher, Gowda, Veena, Lee, Hye Seung, Liu, Shu, Malloy, Jamie, McCarthy, Cristina, McLeod, Wendy, Smith, Laura, Smith, Stephen, Smith, Susan, Uusitalo, Ulla, Yang, Jimin, Akolkar, Beena, Briese, Thomas, Erlich, Henry, Oberste, Steve
المصدر: Scientific Reports; 6, no 30828 (2016) ; ISSN: 2045-2322
بيانات النشر: Nature Publishing Group
سنة النشر: 2016
المجموعة: Lund University Publications (LUP)
مصطلحات موضوعية: Public Health, Global Health, Social Medicine and Epidemiology
الوصف: Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: https://lup.lub.lu.se/record/a2de59dd-9346-47ed-955f-c875e0383197Test; http://dx.doi.org/10.1038/srep30828Test; pmid:27561809; scopus:84984691670
DOI: 10.1038/srep30828
الإتاحة: https://doi.org/10.1038/srep30828Test
https://lup.lub.lu.se/record/a2de59dd-9346-47ed-955f-c875e0383197Test
رقم الانضمام: edsbas.743FCBCD
قاعدة البيانات: BASE