Dealing with non-ignorable non-response by using an 'enthusiasm-to-respond' variable

In the National Survey of Sexual Attitudes and Lifestyles (NATSSAL), it is recognized that non-response is unlikely to be ignorable. In some surveys, in addition to the response variables of interest, there may also be an 'enthusiasm-to-respond' variable which is expected to be related to the probabilities of item and unit response. Inference techniques to deal with non-ignorable non-response, based on a propensity-to-respond score, can be developed when there are both item and unit non-responders. For the NATSSAL data, an interviewer-measured interviewee embarrassment variable is combined with demographics to produce a score for the propensity to respond. The necessary likelihood development is outlined and alternative approaches to interval estimation are compared. The methodology is illustrated through an estimation of virginity from NATSSAL data.     

Homogeneity testing in a Weibull mixture model

The mixed Weibull distribution provides a flexible model to analyze random durations in a possibly heterogeneous population. To test for homogeneity against unobserved heterogeneity in a Weibull mixture model, a dispersion score test and a goodness-of-fit test are investigated. The empirical power of these tests is assessed and compared on a broad range of alternatives. It comes out that the dispersion score test, as it is based on a Weibull-to-exponential transformation, often breaks down. A simple new procedure is introduced for Weibull mixtures in scale, which combines the dispersion score test and the goodness-of-fit test. The new test is compared with several known procedures and shown to have a good overall power. To detect mixtures in shape and scale, a goodness-of-fit test is recommended. This research has been partially sponsored by a grant of the Deutsche Forschungsgemeinschaft. We thank Lars Haferkamp for computational assistance and Wilfried Seidel and a referee for their remarks on alternative test procedures.     

Analysis of longitudinal binary data from multiphase sampling

The efficient use of surrogate or auxiliary information has been investigated within both model-based and design-based approaches to data analysis, particularly in the context of missing data. Here we consider the use of such data in epidemiological studies of disease incidence in which surrogate measures of disease status are available for all subjects at two time points, but definitive diagnoses are available only in stratified subsamples. We briefly review methods for the analysis of two-phase studies of disease prevalence at a single time point, and we discuss the extension of four of these methods to the analysis of incidence studies. Their performance is compared with special reference to a study of the incidence of senile dementia.     

Discretely Observed Diffusions: Approximation of the Continuous-time Score Function

We discuss parameter estimation for discretely observed, ergodic diffusion processes where the diffusion coefficient does not depend on the parameter. We propose using an approximation of the continuous-time score function as an estimating function. The estimating function can be expressed in simple terms through the drift and the diffusion coefficient and is thus easy to calculate. Simulation studies show that the method performs well.     

On the inefficiency of propensity score matching

Propensity score matching is now widely used in empirical applications for estimating treatment effects. Propensity score matching (PSM) is preferred to matching on X because of the lower dimension of the estimation problem. In this note, however, it is shown that PSM is inefficient compared to matching on X. Hence, matching on X should be considered as a serious alternative.     

Non‐parametric Maximum Likelihood Estimation for Cox Regression with Subject‐Specific Measurement Error

Abstract. Many epidemiological studies have been conducted to identify an association between nutrient consumption and chronic disease risk. To this problem, Cox regression with additive covariate measurement error has been well developed in the literature. However, researchers are concerned with the validity of the additive measurement error assumption for self‐report nutrient data. Recently, some study designs using more reliable biomarker data have been considered, in which the additive measurement error assumption is more likely to hold. Biomarker data are often available in a subcohort. Self‐report data often encounter with a variety of serious biases. Complications arise primarily because the magnitude of measurement errors is often associated with some characteristics of a study subject. A more general measurement error model has been developed for self‐report data. In this paper, a non‐parametric maximum likelihood (NPML) estimator using an EM algorithm is proposed to simultaneously adjust for the general measurement errors.     

Longitudinal profiles of bounded outcome scores as predictors for disease activity in rheumatoid arthritis patients: a joint modeling approach

A variety of statistical approaches have been suggested in the literature for the analysis of bounded outcome scores (BOS). In this paper, we suggest a statistical approach when BOSs are repeatedly measured over time and used as predictors in a regression model. Instead of directly using the BOS as a predictor, we propose to extend the approaches suggested in [16 E. Lesaffre, D. Rizopoulos, and R. Tsonaka, The logistics-transform for bounded outcome scores, Biostatistics 8 (2007), pp. 72–85. doi: 10.1093/biostatistics/kxj034[Crossref], [PubMed], [Web of Science ®] , [Google Scholar],21 M. Molas and E. Lesaffre, A comparison of the three random effects approaches to analyse repeated bounded outcome scores with an application in a stroke revalidation study, Stat. Med. 27 (2008), pp. 6612–6633. doi: 10.1002/sim.3432[Crossref], [PubMed], [Web of Science ®] , [Google Scholar],28 R. Tsonaka, D. Rizopoulos, and E. Lesaffre, Power and sample size calculations for discrete bounded outcome scores, Stat. Med. 25 (2006), pp. 4241–4252. doi: 10.1002/sim.2679[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]] to a joint modeling setting. Our approach is illustrated on longitudinal profiles of multiple patients’ reported outcomes to predict the current clinical status of rheumatoid arthritis patients by a disease activities score of 28 joints (DAS28). Both a maximum likelihood as well as a Bayesian approach is developed.     

Semi-parametric Efficient Inference for Heteroscedastic Semivarying-coefficient Models

Semivarying-coefficient models with heteroscedastic errors are frequently used in statistical modeling. When the error is conditional heteroskedastic, Ahmad, et al. (2005 Ahmad, I., Leelahanon, S., Li, Q. (2005). Efficient estimation of a semiparametric partially linear varying coefficient model. Ann. Statist. 33(1):258–283.[Crossref], [Web of Science ®] , [Google Scholar]) proposed a general series method to obtain an efficient estimation. In this article we study the heteroscedastic semi-varying coefficient models with a nonparametric variance function, not only use the semi-parametric efficient normal approximation method to derive a family of semi-parametric efficient estimator, but also use the semi-parametric efficient empirical likelihood method to construct the efficient empirical likelihood confidence regions. The proposed estimators retain the double robustness feature of semi-parametric efficient estimator.     

中国高学历劳动者的教育匹配与收入回报

近十多年来,鉴于中国高等教育扩张对劳动力市场的影响,一些学者开始用经验数据研究劳动者与工作之间的教育匹配(尤其是过度教育)对收入回报的影响。但是,已有文献较少考虑过度教育的选择性问题,也很少对高学历劳动者进行专门研究。本文使用倾向值匹配的方法分析高学历劳动者的教育匹配与收入回报。研究发现,即使是在考虑了选择性之后,过度教育者的收入仍然显著低于适度教育者。同时,对家庭背景、学校出身、人力资本和劳动力市场四大影响因素的考察还发现,过度教育确实具有负向选择的特点,那些拥有较低人力资本和较差出身背景的人更容易发生过度教育。     

中国网民的政治价值观与网络抗争行为的限度

中国的市场化转型带来了政治价值观的变化,进而重塑着个体的政治参与行为,其中包括网络抗争行为。由于种种限制,互联网并不必然带来网络抗争,个人的政治价值观是重要的影响因素。基于全国性的概率抽样调查数据,本文首先构造了个人的政治价值观倾向得分,然后用广义倾向值匹配估算了政治价值观对批评政府官员或政策和讨论集体行动这两种网络抗争行为的响应函数和干预效应。结果显示,越趋向自由民主价值观,个人拥有这两种网络抗争经历的概率越高,且呈现强化趋势。但是,这种作用具有阈值效应,即自由民主价值观达到较高水平后,更高的自由民主价值观带来的网络抗争行为的发生概率反而更低。因此,除了来自政府和体制的外在限制,网络抗争还存在着内生于行动者本身的限制。本文通过实证研究证实了政治价值观对网络抗争行为产生的内在限制。