Zero-inflated count models for longitudinal measurements with heterogeneous random effects
نویسندگان
چکیده
منابع مشابه
Consistent estimation of zero-inflated count models.
Applications of zero-inflated count data models have proliferated in health economics. However, zero-inflated Poisson or zero-inflated negative binomial maximum likelihood estimators are not robust to misspecification. This article proposes Poisson quasi-likelihood estimators as an alternative. These estimators are consistent in the presence of excess zeros without having to specify the full di...
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We describe a mixed-effects hurdle model for zero-inflated longitudinal count data, where a baseline variable is included in the model specification. Association between the count data process and the endogenous baseline variable is modeled through a latent structure, assumed to be dependent across equations. We show how model parameters can be estimated in a finite mixture context, allowing fo...
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هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...
15 صفحه اولSemiparametric analysis of longitudinal zero-inflated count data
Background: The instrumental activities of daily living (IADLs) are important index of physical functioning in older adult studies. These count outcomes with a large proportion of zeros are often collected in longitudinal studies. Data were from the Hispanic Established Population for Epidemiological Study of the Elderly (HEPESE), a four wave (seven years) longitudinal study of community-dwelli...
متن کاملModeling zero-inflated count data with glmmTMB
Ecological phenomena are often measured in the form of count data. These data can be analyzed using generalized linear mixed models (GLMMs) when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the standard error distributions used in GLMMs, e.g., parasite counts may be exactly zero fo...
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ژورنال
عنوان ژورنال: Statistical Methods in Medical Research
سال: 2015
ISSN: 0962-2802,1477-0334
DOI: 10.1177/0962280215588224