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JCR 2016
جستجوی مقالات
چهارشنبه 26 آذر 1404
Journal of Research in Medical Sciences
، جلد ۱۶، شماره ۳، صفحات ۰-۰
عنوان فارسی
چکیده فارسی مقاله
کلیدواژههای فارسی مقاله
عنوان انگلیسی
Comparison of Generalized Estimating Equations and Quadratic Inference Functions in superior versus inferior Ahmed Glaucoma Valve implantation
چکیده انگلیسی مقاله
BACKGROUND: The celebrated generalized estimating equations (GEE) approach is often used in longitudinal data analysis. While this method behaves robustly against misspecification of the working correlation structure, it has some limitations on efficacy of estimators, goodness-of-fit tests and model selection criteria. The quadratic inference functions (QIF) is a new statistical methodology that overcomes these limitations. METHODS: We administered the use of QIF and GEE in comparing the superior and inferior Ahmed glaucoma valve (AGV) implantation, while our focus was on the efficiency of estimation and using model selection criteria; we compared the effect of implant location on intraocular pressure (IOP) in refractory glaucoma patients. We modeled the relationship between IOP and implant location, patient's sex and age, best corrected visual acuity, history of cataract surgery, preoperative IOP and months after surgery with assuming unstructured working correlation. RESULTS: 63 eyes of 63 patients were included in this study; 28 eyes in inferior group and 35 eyes in superior group. The GEE analysis revealed that preoperative IOP has a significant effect on IOP (p = 0.011). However, QIF showed that preoperative IOP, months after surgery and squared months are significantly associated with IOP after surgery (p < 0.05). Overall, estimates from QIF are more efficient than GEE (RE = 1.272). CONCLUSIONS: In the case of unstructured working correlation, the QIF is more efficient than GEE. There were no considerable difference between these locations; our results confirmed previously published works which mentioned it is better that glaucoma patients undergo superior AGV implantation. KEYWORDS: Longitudinal Data, Generalized Estimating Equation, Quadratic Inference Function, Ahmed Glaucoma Valve Implantation. Abstract BACKGROUND: The celebrated generalized estimating equations (GEE) approach is often used in longitudinal data analysis. While this method behaves robustly against misspecification of the working correlation structure, it has some limitations on efficacy of estimators, goodness-of-fit tests and model selection criteria. The quadratic inference functions (QIF) is a new statistical methodology that overcomes these limitations. METHODS: We administered the use of QIF and GEE in comparing the superior and inferior Ahmed glaucoma valve (AGV) implantation, while our focus was on the efficiency of estimation and using model selection criteria; we compared the effect of implant location on intraocular pressure (IOP) in refractory glaucoma patients. We modeled the relationship between IOP and implant location, patient's sex and age, best corrected visual acuity, history of cataract surgery, preoperative IOP and months after surgery with assuming unstructured working correlation. RESULTS: 63 eyes of 63 patients were included in this study; 28 eyes in inferior group and 35 eyes in superior group. The GEE analysis revealed that preoperative IOP has a significant effect on IOP (p = 0.011). However, QIF showed that preoperative IOP, months after surgery and squared months are significantly associated with IOP after surgery (p < 0.05). Overall, estimates from QIF are more efficient than GEE (RE = 1.272). CONCLUSIONS: In the case of unstructured working correlation, the QIF is more efficient than GEE. There were no considerable difference between these locations; our results confirmed previously published works which mentioned it is better that glaucoma patients undergo superior AGV implantation. KEYWORDS: Longitudinal Data, Generalized Estimating Equation, Quadratic Inference Function, Ahmed Glaucoma Valve Implantation.
کلیدواژههای انگلیسی مقاله
نویسندگان مقاله
راضیه خواجه کاظمی | razieh khajeh kazemi
msc student of biostatistics, department of epidemiology and biostatistics, tehran university of medical sciences, tehran, iran.
سازمان اصلی تایید شده
: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)
بنفشه گلستان | banafsheh golestan
department of epidemiology and biostatistics, tehran university of medical sciences, tehran, iran.
سازمان اصلی تایید شده
: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)
کاظم محمد | kazem mohammad
department of epidemiology and biostatistics, tehran university of medical sciences, tehran, iran.
سازمان اصلی تایید شده
: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)
محمودی | mahmoud mahmoudi
department of epidemiology and biostatistics, tehran university of medical sciences, tehran, iran.
سازمان اصلی تایید شده
: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)
سحرناز نجات | saharnaz nedjat
department of epidemiology and biostatistics, tehran university of medical sciences, tehran, iran.
سازمان اصلی تایید شده
: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)
محمد پاکروان | mohammad pakravan
ophthalmic research center, shaheed beheshti university of medical sciences, tehran, iran.
سازمان اصلی تایید شده
: دانشگاه علوم پزشکی شهید بهشتی (Shahid beheshti university of medical sciences)
نشانی اینترنتی
http://jrms.mui.ac.ir/index.php/jrms/article/view/5816
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