• Journal of the Korean Statistical Society
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• v.29 no.2
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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.

• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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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.

• Korean Journal of Adult Nursing
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• v.26 no.2
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• pp.149-158
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• 2014

Purpose: The purpose of this study was to determine whether Selection, Optimization and Compensation (SOC) Strategy mediated the relationship between job stress and health promoting behaviors among nurses. Methods: A descriptive causal relationship research design was used. 245 subjects recruited from the five general hospitals, which have over 500 beds in Seoul and Kyunggi-do, participated in the study by completing a survey which included questions about SOC strategy, job stress and health promoting behaviors. t-test, ANOVA, Pearson's correlation coefficient and multiple regression were used to analyze the data. SPSS/WIN 20.0 was used for all analysis. Results: The mean job stress score was 47.89; mean SOC strategy score was .71. 'Spiritual development' was the highest reported health promoting behavior with a mean of 3.57. Job stress was significantly and negatively related to health promoting behaviors. The result showed that all the mediating paths of SOC strategy were significant. The partial mediating model showed high goodness of fit demonstrating that the model was outstanding. Conclusion: SOC strategy mediated the relationship between job stress and health promoting behaviors. Applying better SOC strategies among nurses will increase flexibility in responding to job stress and will also better perform health promoting behaviors.