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http://dx.doi.org/10.12812/ksms.2011.13.2.195

Generation and Extension of Models for Repeated Measurement Design by Generalizability Design  

Choi, Sung-Woon (Department of Industrial Engineering, Kyungwon University)
Publication Information
Journal of the Korea Safety Management & Science / v.13, no.2, 2011 , pp. 195-202 More about this Journal
Abstract
The study focuses on the Repeated Measurements Design (RMD) which observations are periodically made for identical subjects within definite time periods. One of the purposes of this design is to monitor and keep track of replicated records within regular period over years. This paper also presents the classification models of RMD that is developed according to the number of factors in Between-Subject (BS) variates and Within-Subject (WS) variates. The types of models belong to each number of factors: One factor is 0BS 1WS. Two factors are 1BS 1WS and 0BS 2WS. Three factors are 1BS 2WS and 2BS 1WS. Lastly, the four factors include model of 2BS 2WS In addition, the study explains the generation mechanism of models for RMD using Generalizability Design (GD). GD is a useful method for practitioners to identify linear model of experimental design, since it generates a Venn diagram. Lastly, the research develops three types of 1BS 2WS RMDs with crossed factors and nested factors. Those are random models, mixed models and fixed models and they are presented by using Generalizability Design, $(S:A{\times}B){\times}C$. Moreover, the example of applications and its implementation steps of models developed in the study are presented for better comprehension.
Keywords
RMD; Classification Models; GD; 0BS 1WS; 1BS 1WS; 0BS 2WS; 1BS 2WS; 2BS 1WS; 2BS 2WS; Crossed and Nested Factors; Random Models; Mixed Models; Implementation Steps;
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Times Cited By KSCI : 1  (Citation Analysis)
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