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使用零膨胀模型分析具有大量零值的龋齿情况。

Using zero inflated models to analyze dental caries with many zeroes.

作者信息

Javali Shivalingappa B, Pandit Parameshwar V

机构信息

Department of Public Health Dentistry, SDM College of Dental Sciences & Hospital, Dharwad, Karnataka, India.

出版信息

Indian J Dent Res. 2010 Oct-Dec;21(4):480-5. doi: 10.4103/0970-9290.74210.

Abstract

AIM

The study aimed to analyze and determine the factors associated with dental caries experience contains many zeros by zero inflated models.

DESIGN

A cross sectional design was employed using clinical examination and questionnaire with interview method.

MATERIALS AND METHODS

A study was conducted during March-August 2007 in Dharwad, Karnataka, India, involved a systematic random samples of 1760 individuals aged 18-40 years. The dental caries examination was carried out by using DMFT index (i.e. Decayed (D), Missing (M), Filled (F)). The DMFT index data contains many zeros were analyzed with Zero Inflated Poisson (ZIP) and Zero Inflated Negative Binomial (ZINB) models.

RESULTS

The study findings indicated, the variables such as family size, frequency of brushing and duration of change of toothbrush were positively associated with dental caries. But the variable the frequency of sweet consumption is negatively associated with dental caries experience in Zero Inflated Poisson (ZIP) and Zero Inflated Negative Binomial (ZINB) models.

CONCLUSIONS

The ZIP model is a very good fit over the standard Poisson model and the ZINB is the better statistical fit compared to the Negative Binomial model. The Zero Inflated Negative Binomial model is better fit over the Zero Inflated Poisson model for modeling the DMF count data.

摘要

目的

本研究旨在通过零膨胀模型分析并确定与龋齿经历中存在大量零值相关的因素。

设计

采用横断面设计,运用临床检查和问卷调查及访谈方法。

材料与方法

2007年3月至8月在印度卡纳塔克邦达尔瓦德进行了一项研究,纳入了1760名年龄在18 - 40岁的系统随机样本。使用DMFT指数(即龋坏(D)、缺失(M)、充填(F))进行龋齿检查。对包含大量零值的DMFT指数数据采用零膨胀泊松(ZIP)模型和零膨胀负二项式(ZINB)模型进行分析。

结果

研究结果表明,家庭规模、刷牙频率和牙刷更换时长等变量与龋齿呈正相关。但在零膨胀泊松(ZIP)模型和零膨胀负二项式(ZINB)模型中,甜食消费频率这一变量与龋齿经历呈负相关。

结论

ZIP模型比标准泊松模型拟合效果好,ZINB模型比负二项式模型统计拟合效果更佳。对于DMF计数数据建模,零膨胀负二项式模型比零膨胀泊松模型拟合效果更好。

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