Analysis of periodontal data using mixed effects models
조영일, 김해영,
소속 상세정보
조영일 ( Cho Young-Il ) - Sungshin Women’s University Department of Psychology
김해영 ( Kim Hae-Young ) - Korea University College of Health Science Department of Health Policy Management
KMID : 0363020150450010002
Abstract
A fundamental problem in analyzing complex multilevel-structured periodontal data is the violation of independency among the observations, which is an assumption in traditional statistical models (e.g., analysis of variance and ordinary least squares regression). In many cases, aggregation (i.e., mean or sum scores) has been employed to overcome this problem. However, the aggregation approach still exhibits certain limitations, such as a loss of power and detailed information, no cross-level relationship analysis, and the potential for creating an ecological fallacy. In order to handle multilevel-structured data appropriately, mixed effects models have been introduced and employed in dental research using periodontal data. The use of mixed effects models might account for the potential bias due to the violation of the independency assumption as well as provide accurate estimates.
키워드
Linear models ; Statistics ; Statistical data interpretation
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