{"title":"牙科研究的相关性:为什么重要以及如何处理。","authors":"Eldon Sorensen, Chandler Pendleton, Xian Jin Xie","doi":"10.11607/jomi.10285","DOIUrl":null,"url":null,"abstract":"<p><p>In dental research, it is particularly common for studies to collect data that are fundamentally correlated. Some common dental situations in which correlation arises include patients being observed across multiple teeth and/or across multiple time points, such as before and after treatment, or groups of patients being clustered (ie, familial units). For a number of traditional statistical tests and modeling techniques, the assumption of independence between observations is imperative in order to receive valid results and make accurate conclusions. This article describes how ignoring inherent correlations in data can lead to erroneous results when using traditional methods as well as the types of modeling techniques that are available to handle correlated data. Furthermore, two simulation studies are performed to further illustrate and prove the advantages of adequately handling correlated data in statistical analyses. Int J Oral Maxillofac Implants 2023;38:417-421. doi: 10.11607/jomi.10285.</p>","PeriodicalId":50298,"journal":{"name":"International Journal of Oral & Maxillofacial Implants","volume":"38 3","pages":"417-421"},"PeriodicalIF":1.7000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Correlation in Dental Studies: Why It Matters and What to Do About It.\",\"authors\":\"Eldon Sorensen, Chandler Pendleton, Xian Jin Xie\",\"doi\":\"10.11607/jomi.10285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In dental research, it is particularly common for studies to collect data that are fundamentally correlated. Some common dental situations in which correlation arises include patients being observed across multiple teeth and/or across multiple time points, such as before and after treatment, or groups of patients being clustered (ie, familial units). For a number of traditional statistical tests and modeling techniques, the assumption of independence between observations is imperative in order to receive valid results and make accurate conclusions. This article describes how ignoring inherent correlations in data can lead to erroneous results when using traditional methods as well as the types of modeling techniques that are available to handle correlated data. Furthermore, two simulation studies are performed to further illustrate and prove the advantages of adequately handling correlated data in statistical analyses. Int J Oral Maxillofac Implants 2023;38:417-421. doi: 10.11607/jomi.10285.</p>\",\"PeriodicalId\":50298,\"journal\":{\"name\":\"International Journal of Oral & Maxillofacial Implants\",\"volume\":\"38 3\",\"pages\":\"417-421\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Oral & Maxillofacial Implants\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.11607/jomi.10285\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DENTISTRY, ORAL SURGERY & MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Oral & Maxillofacial Implants","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.11607/jomi.10285","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
Correlation in Dental Studies: Why It Matters and What to Do About It.
In dental research, it is particularly common for studies to collect data that are fundamentally correlated. Some common dental situations in which correlation arises include patients being observed across multiple teeth and/or across multiple time points, such as before and after treatment, or groups of patients being clustered (ie, familial units). For a number of traditional statistical tests and modeling techniques, the assumption of independence between observations is imperative in order to receive valid results and make accurate conclusions. This article describes how ignoring inherent correlations in data can lead to erroneous results when using traditional methods as well as the types of modeling techniques that are available to handle correlated data. Furthermore, two simulation studies are performed to further illustrate and prove the advantages of adequately handling correlated data in statistical analyses. Int J Oral Maxillofac Implants 2023;38:417-421. doi: 10.11607/jomi.10285.
期刊介绍:
Edited by Steven E. Eckert, DDS, MS ISSN (Print): 0882-2786
ISSN (Online): 1942-4434
This highly regarded, often-cited journal integrates clinical and scientific data to improve methods and results of oral and maxillofacial implant therapy. It presents pioneering research, technology, clinical applications, reviews of the literature, seminal studies, emerging technology, position papers, and consensus studies, as well as the many clinical and therapeutic innovations that ensue as a result of these efforts. The editorial board is composed of recognized opinion leaders in their respective areas of expertise and reflects the international reach of the journal. Under their leadership, JOMI maintains its strong scientific integrity while expanding its influence within the field of implant dentistry. JOMI’s popular regular feature "Thematic Abstract Review" presents a review of abstracts of recently published articles on a specific topical area of interest each issue.