• 대한예방의학회:학술대회논문집
• /
• 2004.07a
• /
• pp.21-37
• /
• 2004

• The Korean Journal of Applied Statistics
• /
• v.21 no.2
• /
• pp.291-299
• /
• 2008

This paper discusses model building for repeated binary response data with different time-dependent covariates each occasion. Since repeated measurements data are having correlated structure, weighed least squares(WLS) methodology is applied. Repeated measures designs are usually having different sizes of experimental units like split-plot designs. However repeated measures designs differ from split-plot designs in that the levels of one or more factors cannot be randomly assigned to one or more of the sizes of experimental units in the experiment. In this case, the levels of time cannot be assigned at random to the time intervals. Because of this nonrandom assignment, the errors corresponding to the respective experimental units may have a covariance matrix. So, the estimates of effects included in a suggested logit model are obtained by using covariance structures.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1263-1272
• /
• 2014

Longitudinal categorical data commonly occur from medical, health, and social sciences. In these data, the correlation of repeated outcomes is taken into account to explain the effects of covariates exactly. In this paper, we introduce marginalized random effects models that are used for the estimation of the population-averaged effects of covariates. We also review how these models have been developed. Real data analysis is presented using the marginalized random effects.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.6
• /
• pp.1263-1270
• /
• 2010

Sixty patients were divided into three groups. Each group of twenty persons had fed on different diet foods over 5 weeks. Cholesterol had been measured repeatedly five times at an interval of a week during 5 weeks. It resulted from mixed model analysis of repeated measurements data that homogeneous toeplitz covariance matrix pattern was selected as the optimal covariance pattern. The correlations between measurements of different times for the covariance matrix are somewhat highly correlated as 0.64-0.78. Based upon the homogeneous toeplitz covariance pattern model, the time effect was found to be highly significant, but the treatment effect and treatment-time interaction effect were found to be insignificant.

• The Korean Journal of Applied Statistics
• /
• v.22 no.1
• /
• pp.181-188
• /
• 2009

This paper discusses the covariance structures of data collected from an experiment with a nested design structure, where a smaller experimental unit is nested within a larger one. Due to the nonrandomization of repeated measures factors to the nested experimental units, compound symmetry covariance structure is assumed for the analysis of data. Treatments are given as the combinations of the levels of random factors and fixed factors. So, a mixed-effects model is suggested under compound symmetry structure. An example is presented to illustrate the nesting in the experimental units and to show how to get the parameter estimates in the fitted model.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.3
• /
• pp.689-700
• /
• 2016

We study estimation and inference of the joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. For the estimation of marginal models we consider a class of time-varying transformation models and combine the two marginal models using nonparametric empirical copulas. Regression parameters in the transformation model can be obtained as the solution of estimating equations and our models and estimation method can be applied in many situations where the conditional mean-based models are not good enough. Nonparametric copulas combined with time-varying transformation models may allow quite flexible modeling for the joint conditional distributions for bivariate longitudinal data. We apply our method to an epidemiological study of repeatedly measured bivariate cholesterol data.

• The Korean Journal of Food And Nutrition
• /
• v.7 no.3
• /
• pp.213-218
• /
• 1994

본 연구는 식품의 물성을 측정하기 위한 한 가지 방법으로 50 변위를 아주 정밀하게 직선적으로 측정이 가능한 linear proximity sensor(선형 근접 센서)를 활용하여 식빵의 굳기를 측정하였다 선형 근접 센서를 장착한 기구로 몇 가지 응력(0.376, 0.543, 0.769 kPa) 하에서 식빵의 온도와 수분 함량에 따른 변형을 컴퓨터 자동 자료 수집 장치를 통하여 on-line 상태로 매초마다 자료를 수집하여 컴퓨터 자료 분석 program으로 그래프를 얻었다. 식빵에 적용한 응력과 strain의 비율은 응력이 클수록 그 값이 커지는 비 선형 점 탄성체의 성질을 보였다. 이 측정 기구는 좁은 온도범위와 작은 수분함량의 차이에 따른 식빵의 굳기의 정도에 현저한 차이가 있음을 관찰할 수 있었다. 선형 근접 센서를 활용한 이 기구는 간단하면서도 정밀하게 동적으로 식품의 물성을 측정할 수 있었고, 높은 반복성을 나타내었다. 또한 수집된 자료는 점 탄성체의 특성을 설명하는 기계적인 모형으로 나타낼 수 있었다. Inokuchi의 방법을 적용하여 식빵의 물성을 모형화 하면 용수철과 완충 장치의 조합으로 나타내는 Burger's 모형에 잘 일치하였다. 본 측정 장치는 설치와 사용이 간단하여 식빵과 같은 연 식품의 물성을 측정하는데 활용이 용이하였다.

• Science of Emotion and Sensibility
• /
• v.11 no.4
• /
• pp.553-564
• /
• 2008

Generalizability theory was employed to examine how the reliability of polygraph test is affected by the number of relevant questions, the number of repeated tests (the number of of charts), and the number of raters(scorers). The data consisted of the results of the polygraph tests administered to 31 crime suspects. The sample was drawn from the real polygraph tests based on Backster ZCT and archived by the Prosecutor's Office of the Republic of Korea. The numerical scores assigned by thirteen raters to the test charts were analyzed to determine the generalizability of the scores. The largest variance component was accounted for by the examinee factor(43.97%) and the residual variance component was 16.84% of the total variance. The variance component due to the interaction between the examinee and the chart factors was 12.17% and the variance component due to the three way interaction of the examinee, the repeated test, and the relevant question factors was 10.31%. The generalizability coefficient for the current measurement procedure as practiced by the Korean Prosecutor's Office was 0.74 which suggests that the current procedure is acceptable. However, measurement procedures with the combination of more than two relevant questions, more than three repeated tests, and more than two raters were generally found to yield generalizability coefficients larger than 0.80. Therefore, such procedures need to be considered seriously in order to significantly improve the reliability of polygraph test.

• The Korean Journal of Applied Statistics
• /
• v.28 no.2
• /
• pp.201-210
• /
• 2015

Repeated measurements on each variables of interest often arise in bioscience or medical research. We need to account for correlations among repeated measurements to assess the correlation between two variables in the presence of replication. This paper reviews methods to estimate a correlation coefficient between two variables in repeated measurements using the variance-covariance matrix of linear mixed effect models. We analyze acoustic radiation force impulse imaging (ARFI) data to assess correlation between three shear wave velocity (SWV) measurements in liver or spleen and spleen length by ultrasonography. We present how to obtain parameter estimates for the variance-covariance matrix and correlations in mixed effects models using PROC MIXED in SAS.

• Journal of Animal Science and Technology
• /
• v.54 no.2
• /
• pp.71-75
• /
• 2012

The present study data were obtained from 36,894 cows in Korea Animal Improvement Association from 2001 to 2009 which was subjected for ultrasound measurements (eye muscle area, back-fat thickness, marbling score) and descent. Repeated record models were carried out using 7,913 of 36,894 of total animal traits. The ultrasound measured traits and performance test data were used to study the chest girth, body condition score, eye muscle area, back-fat thickness and marbling score with genetic correlation and parameters for the ultrasound measured traits using REMLF90 program. Genetic correlation of eye muscle area with back-fat thickness, marbling score and back-fat thickness with marbling score were noticed in repeated records animal model as 0.69, 0.54, and 0.59, whereas in multiple trait animal model method were 0.07, 0.66, and 0.39, respectively. Repeated records of animal models were used as positive correlation of traits. Multiple trait animal models were used as negative correlation of eye muscle area with marbling score. The analysis on repeat records of animal models using ultrasound measurements about Korean cattle showed positive effects for each traits. In comparison differences between the repeat records of animal models and multiple trait animal models was found with higher traits of her, the heritability and repeatability was found higher in repeat records animal models. In light of these assessments, carcass traits by ultrasound measurements are expected to help and improve an accurate analysis of each trait and if the research analysis using repeat records of animal models continue when we estimate genetic ability of these traits.