Statistical estimation in the proportional hazards model with risk set sampling

Thomas' partial likelihood estimator of regression parameters is widely used in the analysis of nested case-control data with Cox's model. This paper proposes a new estimator of the regression parameters, which is consistent and asymptotically normal. Its asymptotic variance is smaller than that of Thomas' estimator away from the null. Unlike some other existing estimators, the proposed estimator does not rely on any more data than strictly necessary for Thomas' estimator and is easily computable from a closed form estimating equation with a unique solution. The variance estimation is obtained as minus the inverse of the derivative of the estimating function and therefore the inference is easily available. A numerical example is provided in support of the theory.Comment: Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Statistics (http://www.imstat.org/aos/) at http://dx.doi.org/10.1214/00905360400000051

Estimation of Dynamic Mixed Double Factors Model in High Dimensional Panel Data

The purpose of this article is to develop the dimension reduction techniques in panel data analysis when the number of individuals and indicators is large. We use Principal Component Analysis (PCA) method to represent large number of indicators by minority common factors in the factor models. We propose the Dynamic Mixed Double Factor Model (DMDFM for short) to re ect cross section and time series correlation with interactive factor structure. DMDFM not only reduce the dimension of indicators but also consider the time series and cross section mixed effect. Different from other models, mixed factor model have two styles of common factors. The regressors factors re flect common trend and reduce the dimension, error components factors re ect difference and weak correlation of individuals. The results of Monte Carlo simulation show that Generalized Method of Moments (GMM) estimators have good unbiasedness and consistency. Simulation also shows that the DMDFM can improve prediction power of the models effectively.Comment: 38 pages, 2 figure

Digital libraries: What do users want?

This is the post-print version of the Article of the Article. The official published version can be accessed from the link below - Copyright @ 2006 EmeraldPurpose – The purpose of this study is to determine user suggestions for digital libraries' functionality and features. Design/methodology/approach – A survey was conducted as part of this study, in which users' suggestions for digital libraries were solicited, as well as their ranking opinions on a range of suggested digital library features. Findings – The study revealed that, regardless of users' information technology (IT) backgrounds, their expectations of digital libraries' functionality are the same. However, based on users' previous experiences with digital libraries, their requirements with respect to specific features may change. Practical implications – Involving users in digital library design should be an integral step in the process of building a digital library – in addition to the classic roles of evaluation and testing. Originality/value – In previous digital library user studies, users were involved implicitly (e.g. observed) or explicitly (e.g. diary notes). However, they were never asked to suggest digital library features or functionalities, as this was left to usability and domain experts. This study approached digital library design from a new perspective, giving users an opportunity to express their suggestions on future functionality and features of digital libraries. Moreover, in contrast to previous work, this study has explicitly taken into account the IT abilities of those interacting with a digital library