Semiparametric analysis of zero-inflated count data
文献类型：期刊论文
| 作者 | Lam, K. F.; Xue, Hongqi; Cheung, Yin Bun |
| 刊名 | Biometrics
 |
| 出版日期 | 2006-12-01 |
| 卷号 | 62期号:4页码:996-1003 |
| ISSN号 | 0006-341X |
| 关键词 | Asymptotically efficient Generalized partly linear model Sieve maximum likelihood estimator Zero-inflated poisson regression model |
| DOI | 10.1111/j.1541-0420.2006.00575.x |
| 通讯作者 | Lam, k. f.(hrntlkf@hku.hk) |
| 英文摘要 | Medical and public health research often involve the analysis of count data that exhibit a substantially large proportion of zeros, such as the number of heart attacks and the number of days of missed primary activities in a given period. a zero-inflated poisson regression model, which hypothesizes a two-point heterogeneity in the population characterized by a binary random effect, is generally used to model such data. subjects are broadly categorized into the low-risk group leading to structural zero counts and high-risk (or normal) group so that the counts can be modeled by a poisson regression model. the main aim is to identify the explanatory variables that have significant effects on (i) the probability that the subject is from the low-risk group by means of a logistic regression formulation; and (ii) the magnitude of the counts, given that the subject is from the high-risk group by means of a poisson regression where the effects of the covariates are assumed to be linearly related to the natural logarithm of the mean of the counts. in this article we consider a semiparametric zero-inflated poisson regression model that postulates a possibly nonlinear relationship between the natural logarithm of the mean of the counts and a particular covariate. a sieve maximum likelihood estimation method is proposed. asymptotic properties of the proposed sieve maximum likelihood estimators are discussed. under some mild conditions, the estimators are shown to be asymptotically efficient and normally distributed. simulation studies were carried out to investigate the performance of the proposed method. for illustration purpose, the method is applied to a data set from a public health survey conducted in indonesia where the variable of interest is the number of days of missed primary activities due to illness in a 4-week period. |
| WOS关键词 | MODELS ; AGE ; REGRESSION |
| WOS研究方向 | Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology ; Mathematics |
| WOS类目 | Biology ; Mathematical & Computational Biology ; Statistics & Probability |
| 语种 | 英语 |
| 出版者 | BLACKWELL PUBLISHING |
| WOS记录号 | WOS:000242771800005 |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2379256 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Lam, K. F. |
| 作者单位 | 1.Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China 2.Chinese Acad Sci, Grad Univ, Dept Math, Beijing, Peoples R China 3.Univ London London Sch Hyg & Trop Med, MRC, Trop Epidemiol Grp, London WC1E 7HT, England |
| 推荐引用方式 GB/T 7714 | Lam, K. F.,Xue, Hongqi,Cheung, Yin Bun. Semiparametric analysis of zero-inflated count data[J]. Biometrics,2006,62(4):996-1003. |
| APA | Lam, K. F.,Xue, Hongqi,&Cheung, Yin Bun.(2006).Semiparametric analysis of zero-inflated count data.Biometrics,62(4),996-1003. |
| MLA | Lam, K. F.,et al."Semiparametric analysis of zero-inflated count data".Biometrics 62.4(2006):996-1003. |
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来源：中国科学院大学
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