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A Non-Random Dropout Model for Analyzing Longitudinal Skew-Normal Response
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نویسنده
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Baghfalaki T. ,Ganjali M. ,Khounsiavash M.
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منبع
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journal of the iranian statistical society - 2012 - دوره : 11 - شماره : 2 - صفحه:101 -129
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چکیده
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In this paper, multivariate skew-normal distribution is em- ployed for analyzing an outcome based dropout model for repeated mea- surements with non-random dropout in skew regression data sets. a probit regression is considered as the conditional probability of an ob- servation to be missing given outcomes. a simulation study of using the proposed methodology and comparing it with a semi-parametric method, gee, is provided. the standardized bias is used for compari- son of different approaches. furthermore, for investigation of efficiency of the methodology two applications are analyzed where observed infor- mation matrix is used to find the variances of the parameter estimates. in one of the applications a sensitivity analysis is also performed to in- vestigate the change on the response model’s parameter estimates due to perturbation of drop-out model’s parameter of interest
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کلیدواژه
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Dropout ,generalized estimating equations (GEE) ,longitu- dinal data ,observed information matrix ,selection model ,Skew-Normal distribution
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آدرس
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shahid beheshti university, Department of Statistics, ایران, shahid beheshti university, Department of Statistics, ایران, islamic azad university, ایران
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پست الکترونیکی
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mfsiavash@gmail.com
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Authors
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