Variable selection for survival data with a class of adaptive elastic net techniques

The accelerated failure time (AFT) models have proved useful in many contexts, though heavy censoring (as for example in cancer survival) and high dimensionality (as for example in microarray data) cause difficulties for model fitting and model selection. We propose new approaches to variable selection for censored data, based on AFT models optimized using regularized weighted least squares. The regularized technique uses a mixture of \(\ell _1\) and \(\ell _2\) norm penalties under two proposed elastic net type approaches. One is the adaptive elastic net and the other is weighted elastic net. The approaches extend the original approaches proposed by Ghosh (Adaptive elastic net: an improvement of elastic net to achieve oracle properties, Technical Reports 2007) and Hong and Zhang (Math Model Nat Phenom 5(3):115–133 2010), respectively. We also extend the two proposed approaches by adding censoring observations as constraints into their model optimization frameworks. The approaches are evaluated on microarray and by simulation. We compare the performance of these approaches with six other variable selection techniques-three are generally used for censored data and the other three are correlation-based greedy methods used for high-dimensional data.     

A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data

With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution and the covariates are independent. Covariate‐dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate‐dependent censoring. We consider a covariate‐adjusted weight function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate‐adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate‐adjusted weight approach works well for the variance estimator as well. We illustrate our methods with bone marrow transplant data from the Center for International Blood and Marrow Transplant Research. Here, cancer relapse and death in complete remission are two competing risks.     

Predictive Inference for Big,Spatial, Non‐Gaussian Data: MODIS Cloud Data and its Change‐of‐Support

Remote sensing of the earth with satellites yields datasets that can be massive in size, nonstationary in space, and non‐Gaussian in distribution. To overcome computational challenges, we use the reduced‐rank spatial random effects (SRE) model in a statistical analysis of cloud‐mask data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on board NASA's Terra satellite. Parameterisations of cloud processes are the biggest source of uncertainty and sensitivity in different climate models’ future projections of Earth's climate. An accurate quantification of the spatial distribution of clouds, as well as a rigorously estimated pixel‐scale clear‐sky‐probability process, is needed to establish reliable estimates of cloud‐distributional changes and trends caused by climate change. Here we give a hierarchical spatial‐statistical modelling approach for a very large spatial dataset of 2.75 million pixels, corresponding to a granule of MODIS cloud‐mask data, and we use spatial change‐of‐Support relationships to estimate cloud fraction at coarser resolutions. Our model is non‐Gaussian; it postulates a hidden process for the clear‐sky probability that makes use of the SRE model, EM‐estimation, and optimal (empirical Bayes) spatial prediction of the clear‐sky‐probability process. Measures of prediction uncertainty are also given.     

高校毕业生就业区域流向探析——以合肥工业大学为例

本文以合肥工业大学为例,通过对该校近三届毕业生就业的地域流向进行调查,分析了理工科高校毕业生地域流向的三个特点及成因,并就如何做好毕业生就业工作提出有关对策.     

Obesity and hospitalization over the adult life course: does duration of exposure increase use?

Consistent with a new genre of research on life-course analyses of health-service use, this study explores the consequences of long-term exposure to a risk factor. Drawing from cumulative-disadvantage theory, the study examines whether obesity, especially chronic obesity, increases hospitalization admission and length of stay. Analyses make use of hospital records abstracted over 20 years from a national survey of adults 41 to 77 years of age at baseline (n = 4,574). Multiple measures of body weight are used to calculate adult obesity duration. Results reveal that obesity increased hospital admissions and length of stay over the 20 years studied. Among persons obese at any time during the study, years of obesity also led to longer stays. The findings highlight the utility of measures of the duration of risk exposure for both life-course studies of health and tests of cumulative-disadvantage theory.     

Intergenerational class mobility in contemporary Britain: political concerns and empirical findings

In Britain in recent years social mobility has become a topic of central political concern, primarily as a result of the effort made by New Labour to make equality of opportunity rather than equality of condition a focus of policy. Questions of the level, pattern and trend of mobility thus bear directly on the relevance of New Labour's policy analysis, and in turn are likely be crucial to the evaluation of its performance in government. However, politically motivated discussion of social mobility often reveals an inadequate grasp of both empirical and analytical issues. We provide new evidence relevant to the assessment of social mobility - in particular, intergenerational class mobility - in contemporary Britain through cross-cohort analyses based on the NCDS and BCS datasets which we can relate to earlier cross-sectional analyses based on the GHS. We find that, contrary to what seems now widely supposed, there is no evidence that absolute mobility rates are falling; but, for men, the balance of upward and downward movement is becoming less favourable. This is overwhelmingly the result of class structural change. Relative mobility rates, for both men and women, remain essentially constant, although there are possible indications of a declining propensity for long-range mobility. We conclude that under present day structural conditions there can be no return to the generally rising rates of upward mobility that characterized the middle decades of the twentieth century - unless this is achieved through changing relative rates in the direction of greater equality or, that is, of greater fluidity. But this would then produce rising rates of downward mobility to exactly the same extent - an outcome apparently unappreciated by, and unlikely to be congenial to, politicians preoccupied with winning the electoral 'middle ground'.     

Do hostile sexual beliefs affect men's perceptions of sexual-interest messages?

This study tested the distorted cognitions component of Hall and Hirschman's (1991) quadripartite model of sexual aggression. Men (N = 107) with and without hostile sexual beliefs viewed erotic slides with a female partner who provided one of four patterns of feedback: clear disinterest, token disinterest, compliant interest, and clear interest. Hostile men reported fewer differences between women, were unresponsive to their partner's perceived embarrassment, and reported a consistent positive mood regardless of her feedback. Conversely, nonhostile men were more responsive to feedback, mirrored the partner's embarrassment, and experienced a less positive mood when she communicated clear disinterest in the erotica. These findings support the distorted cognitions component of the quadripartite model of sexual aggression. The authors also discuss the strengths and limitations of this study's methodology.     

College and university compliance with a required meningococcal vaccination law

OBJECTIVE: Maryland became the first state to pass a vaccination law requiring college and university students living on campus to obtain a meningococcal vaccination or to sign a waiver refusing vaccination because college students are at increased risk for disease. The authors sought to identify how Maryland colleges addressed the law and determine whether schools were in full compliance. PARTICIPANTS: The authors surveyed 32 college/university administrators via a self-administered questionnaire. METHODS: The authors calculated vaccination and waiver rates and assessed compliance with the law overall and with specific law components. RESULTS: Among 28 participating schools, annual vaccination rates and waiver rates among students during 2000-2004 ranged from 66%-76% and 12%-17%, respectively. Two (7%) schools were compliant with all components of the law. CONCLUSIONS: Mandatory vaccination laws do not ensure compliance at the college and university level. Mandatory reporting, increased education, and collaboration between colleges and universities and public health agencies are needed.