• Journal of the Korean Data and Information Science Society
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• 제24권3호
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• pp.651-658
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• 2013

For the marginal model and generalized estimating equations (GEE) method there is important full covariates conditional mean (FCCM) assumption which is pointed out by Pepe and Anderson (1994). With longitudinal data with time-varying stochastic covariates, this assumption may not necessarily hold. If this assumption is violated, the biased estimates of regression coefficients may result. But if a diagonal working correlation matrix is used, irrespective of whether the assumption is violated, the resulting estimates are (nearly) unbiased (Pan et al., 2000).The quadratic inference functions (QIF) method proposed by Qu et al. (2000) is the method based on generalized method of moment (GMM) using GEE. The QIF yields a substantial improvement in efficiency for the estimator of ${\beta}$ when the working correlation is misspecified, and equal efficiency to the GEE when the working correlation is correct (Qu et al., 2000).In this paper, we interest in whether the QIF can improve the results of the GEE method in the case of FCCM is violated. We show that the QIF with exchangeable and AR(1) working correlation matrix cannot be consistent and asymptotically normal in this case. Also it may not be efficient than GEE with independence working correlation. Our simulation studies verify the result.

• Journal of the Korean Data and Information Science Society
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• 제24권4호
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• pp.877-883
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• 2013

The quadratic inference functions (QIF) method proposed by Qu et al. (2000) and the generalized method of moments (GMM) for marginal regression analysis of longitudinal data with time-dependent covariates proposed by Lai and Small (2007) both are the methods based on generalized method of moment (GMM) introduced by Hansen (1982) and both use generalized estimating equations (GEE). Lai and Small (2007) divided time-dependent covariates into three types such as: Type I, Type II and Type III. In this paper, we compared these methods in the case of Type II and Type III in which full covariates conditional mean assumption (FCCM) is violated and interested in whether they can improve the results of GEE with independence working correlation. We show that in the marginal regression model with Type II time-dependent covariates, GMM Type II of Lai and Small (2007) provides more ecient result than QIF and for the Type III time-dependent covariates, QIF with independence working correlation and GMM Type III methods provide the same results. Our simulation study showed the same results.

• Asian Pacific Journal of Cancer Prevention
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• 제13권3호
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• pp.941-944
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• 2012

Objective: The aim of current study was to evaluate the changes of health-related quality of life (HRQoL) and its clinical, demographic and socioeconomic determinants during chemotherapy and 4 months follow-up in women with breast cancer using a repeated measures framework. Methods and Materials: A double blind cohort study was performed in 100 breast cancer patients given fluorouracil, doxorubicin and cyclophosphamide (FAC) or docetaxel, doxorubicin, cyclophosphamide (TAC) in south of Iran. HRQoL was assessed at baseline, end of chemotherapy and four months thereafter using the QLQ-C30 questionnaire from European Organization for Research and Treatment of Cancer (EORTC). Generalized estimating equations (GEE) was applied for statistical analysis. Results: The mean of age at baseline was $48.5{\pm}10.6$. 70% and 14% of patients were married and smokers, respectively, and 20% suffered from another disease besides breast cancer. The results of GEE showed that after control for baseline scores, the HRQoL significantly improved over time. Although, the patients in FAC group had higher scores than the TAC group, the differences also diminished over time. Smoking, marital status and having child affected some scales of HRQoL. None of other variables were significantly related to HRQoL. Conclusion: Although patients in TAC groups had lower level of HRQoL over 8 months follow up, they experienced faster improvement than the FAC group. This implies that in long-term, improvements in TAC group are higher than FAC. Having children was positively correlated with HRQoL. Generally, there were no demographic and socio-economic differences in HRQoL in these patients between the chemotherapeutic regimens.

• Journal of the Korean Statistical Society
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• 제29권2호
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• pp.201-217
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• 2000

The method of generalized estimating equations (GEE) has become very popular for the analysis of longitudinal data. We extend this work to the use of M-estimators; the resultant regression estimates are robust to heavy tailed errors and to outliers. The proposed method does not require correct specification of the dependence structure between observation, and allows for heterogeneity of the error. However, an estimate of the dependence structure may be incorporated, and if it is correct this guarantees a higher efficiency for the regression estimators. A goodness-of-fit test for checking the adequacy of the assumed M-estimation regression model is also provided. Simulation studies are conducted to show the finite-sample performance of the new methods. The proposed methods are applied to a real-life data set.

• 한국경영과학회지
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• 제26권1호
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• pp.109-116
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• 2001

The detection of corporate failures is a subject that has been particularly amenable to cross-sectional financial ratio analysis. In most of firms, however, the financial data are available over past years. Because of this, a model utilizing these longitudinal data could provide useful information on the prediction of bankruptcy. To correctly reflect the longitudinal and firm-specific data, the generalized linear model with assuming the first order AR(autoregressive) process is proposed. The method is motivated by the clinical research that several characteristics are measured repeatedly from individual over the time. The model is compared with several other predictive models to evaluate the performance. By using the financial data from manufacturing corporations in the Korea Stock Exchange (KSE) list, we will discuss some experiences learned from the procedure of sampling scheme, variable transformation, imputation, variable selection, and model evaluation. Finally, implications of the model with repeated measurement and future direction of research will be discussed.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.389-402
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• 2023

Multivariate or clustered failure time data often occur in many medical, epidemiological, and socio-economic studies when survival data are collected from several research centers. If the data are periodically observed as in a longitudinal study, survival times are often subject to various types of interval-censoring, creating multivariate interval-censored data. Then, the event times of interest may be correlated among individuals who come from the same cluster. In this article, we propose a unified linear regression method for analyzing multivariate interval-censored data. We consider a semiparametric multivariate accelerated failure time model as a statistical analysis tool and develop a generalized Buckley-James method to make inferences by imputing interval-censored observations with their conditional mean values. Since the study population consists of several heterogeneous clusters, where the subjects in the same cluster may be related, we propose a generalized estimating equations approach to accommodate potential dependence in clusters. Our simulation results confirm that the proposed estimator is robust to misspecification of working covariance matrix and statistical efficiency can increase when the working covariance structure is close to the truth. The proposed method is applied to the dataset from a diabetic retinopathy study.

• 보건행정학회지
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• 제34권3호
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• pp.282-292
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• 2024

연구배경: 본 연구는 서울의 인구이동 특성을 반영할 수 있는 생활인구와 지역의 건강결과 간 관계를 파악하는 것을 목적으로 한다. 방법: 본 연구에서는 통계청 마이크로데이터 통합서비스의 사망원인통계 원시자료를 사용하였다. 독립변수인 생활인구를 파악하기 위해 KT 통신사(Korean Telecom)에서 제공하고 있는 서울시 25개 자치구의 생활인구 데이터를 활용하였다. 통제변수는 SDoH (social determinants of health)의 네 가지 영역(경제적 안정, 의료접근성 및 품질, 이웃 및 건축환경, 사회 및 커뮤니티 연결)을 기반으로 하였다. 이후 패널 generalized estimating equations (GEE) 분석을 통해 생활인구와 지역의 건강결과 간 관계를 확인하였다. 결과: 패널 GEE 분석결과 모든 사망 관련 건강결과(회피 가능 사망률, 예방 가능 사망률, 치료 가능 사망률)는 생활인구와 통계적으로 유의미한 음(-)의 관계가 있었다. 이는 생활인구의 증가가 사망 관련 건강결과에 긍정적인 영향을 미친다는 것을 시사하는 결과이다. 결론: 지역의 건강결과와 인구밀도 사이에 유의미한 관계가 있음을 확인한 것은 지역의 건강격차 완화를 목표로 하는 정책 개발의 핵심 지표로써 생활인구지표를 사용해야 함을 강조하는 결과이다. 또한 본 연구결과는 생활인구가 적은 지역을 중심으로 지역의 인프라를 전략적으로 확장해야 함을 시사한다.

• 한국환경보건학회:학술대회논문집
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• 한국환경보건학회 2005년도 가을학술대회
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• pp.126-129
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• 2005

본 연구는 서울지역 초등학교 학생 4, 5, 6학년 남 ${\cdot}$ 녀 초등학생들을 대상으로 봄철 대기오염농도와 일별 자각증상 과의 관련성에 대한 패널연구를 수행하였다. 로지회귀분석방법 중 일반화 추정 방정식(generalized estimating equations:GEE)모델을 이용하여 통계분석을 실시한 결과로는 서울지역 초등학교 학생들은 호흡기 증상보다는 피부가려움이나 눈의 따가움 등의 자극증상에 호흡성먼지(PM10)와 아황산가스 그리고 이산화질소 등의 대기오염물질 농도와 관련성이 있는 것으로 추정되었다.

• Journal of Preventive Medicine and Public Health
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• 제37권4호
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• pp.381-389
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• 2004

Objective : To compare the efficacy between SKI306X and Diclofenac by using generalized estimating equations (GEE) methodology in the analysis of correlated bivariate binary outcome data in Osteoarthritis (OA) diseases. Methods : A randomized, double-blind, active comparator-controlled, non-inferiority clinical trial was conducted at 5 institutions in Korea with the random assignment of 248 patients aged 35 to 75 years old with OA of the knee and clinical evidence of OA. Patients were enrolled in this study if they had at least moderate pain in the affected knee joint and a score larger than 35mm as assessed by VAS (Visual Analog Scale). The main exposure variable was treatment (SKI 306X vs. Diclofenac) and other covariates were age, sex, BMI, baseline VAS, center, operation history (Yes/No), NSAIDS (Y/N), acupuncture (Y/N), herbal medicine (Y/N), past history of musculoskeletal disease (Y/N), and previous therapy related with OA (Y/N). The main study outcome was the change of VAS pain scores from baseline to the 2nd and 4th weeks after treatment. Pain scores were obtained as baseline, 2nd and 4th weeks after treatment. We applied GEE approach with empirical covariance matrix and independent(or exchangeable) working correlation matrix to evaluate the relation of several risk factors to the change of VAS pain scores with correlated binary bivariate outcomes. Results : While baseline VAS, age, and acupuncture variables had protective effects for reducing the OA pain, its treatment (Joins/Diclofenac) was not statistically significant through GEE methodology (ITT:aOR=1.37, 95% CI=(0.8200, 2.26), PP:aOR=1.47, 95% CI=(0.73, 2.95)). The goodness-of-fit statistic for GEE (6.55, p=0.68) was computed to assess the adequacy of the fitted final model. Conclusions : Both ANCOVA and GEE methods yielded non statistical significance in the evaluation of non-inferiority of the efficacy between SKI306X and Diclofenac. While VAS outcome for each visit was applied in GEE, only VAS outcome for the fourth visit was applied in ANCOVA. So the GEE methodology is more accurate for the analysis of correlated outcomes.

• 대한간호학회지
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• 제50권4호
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• pp.631-640
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• 2020

Purpose: This study aimed to examine premenstrual symptoms (PMS) of shift nurses and identify the association between PMS, sleep, and occupational stress. Methods: This study was conducted with a secondary data analysis that used data from the Shift Work Nurse's Health and Turnover study. The participants were 258 nurses who were working in shifts including night shifts. PMS, sleep patterns (sleep time and sleep time variability), sleep quality, and the occupational stress of each participant were measured using the Moos Menstrual Distress Questionnaire, a sleep diary, an actigraph, the Insomnia Severity Index, and the Korean Occupational Stress Scale, respectively. Data were analyzed using SPSS 23 and STATA 15.1 to obtain descriptive statistics, Pearson's correlation coefficients, multiple linear regression with generalized estimating equations (GEE) and Baron and Kenny's mediating analysis. Results: The average PMS score, average sleep time, average sleep time variability, average sleep quality score, and average occupational stress score of the participants was 53.95 ± 40.45, 7.52 ± 0.89 hours, 32.84 ± 8.43%, 12.34 ± 5.95, and 49.89 ± 8.98, respectively. A multiple linear regression analysis with GEE indicated that sleep time variability (B = 0.86, p = .001), and sleep quality (B = 2.36, p < .001) had negative effects on nurses' PMS. We also found that sleep quality had a complete mediating effect in the relationship between occupational stress and PMS. Conclusion: These findings indicate that both sleep time variability and sleep quality are important factors associated with PMS among shift work nurses. To improve shift nurses' PMS status, strategies are urgently needed to decrease sleep time variability and increase sleep quality.