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.     

Randomization tests in recursive response-adaptive randomization procedures

In a randomized clinical trial, response-adaptive randomization procedures use the information gathered, including the previous patients' responses, to allocate the next patient. In this setting, we consider randomization-based inference. We provide an algorithm to obtain exact p-values for statistical tests that compare two treatments with dichotomous responses. This algorithm can be applied to a family of response adaptive randomization procedures which share the following property: the distribution of the allocation rule depends only on the imbalance between treatments and on the imbalance between successes for treatments 1 and 2 in the previous step. This family includes some outstanding response adaptive randomization procedures. We study a randomization test to contrast the null hypothesis of equivalence of treatments and we show that this test has a similar performance to that of its parametric counterpart. Besides, we study the effect of a covariate in the inferential process. First, we obtain a parametric test, constructed assuming a logit model which relates responses to treatments and covariate levels, and we give conditions that guarantee its asymptotic normality. Finally, we show that the randomization test, which is free of model specification, performs as well as the parametric test that takes the covariate into account.     

Power analysis for clustered non-continuous responses in multicenter trials

Power analysis for multi-center randomized control trials is quite difficult to perform for non-continuous responses when site differences are modeled by random effects using the generalized linear mixed-effects model (GLMM). First, it is not possible to construct power functions analytically, because of the extreme complexity of the sampling distribution of parameter estimates. Second, Monte Carlo (MC) simulation, a popular option for estimating power for complex models, does not work within the current context because of a lack of methods and software packages that would provide reliable estimates for fitting such GLMMs. For example, even statistical packages from software giants like SAS do not provide reliable estimates at the time of writing. Another major limitation of MC simulation is the lengthy running time, especially for complex models such as GLMM, especially when estimating power for multiple scenarios of interest. We present a new approach to address such limitations. The proposed approach defines a marginal model to approximate the GLMM and estimates power without relying on MC simulation. The approach is illustrated with both real and simulated data, with the simulation study demonstrating good performance of the method.     

Methods to assess measurement error in questionnaires of sedentary behavior

Sedentary behavior has already been associated with mortality, cardiovascular disease, and cancer. Questionnaires are an affordable tool for measuring sedentary behavior in large epidemiological studies. Here, we introduce and evaluate two statistical methods for quantifying measurement error in questionnaires. Accurate estimates are needed for assessing questionnaire quality. The two methods would be applied to validation studies that measure a sedentary behavior by both questionnaire and accelerometer on multiple days. The first method fits a reduced model by assuming the accelerometer is without error, while the second method fits a more complete model that allows both measures to have error. Because accelerometers tend to be highly accurate, we show that ignoring the accelerometer's measurement error, can result in more accurate estimates of measurement error in some scenarios. In this article, we derive asymptotic approximations for the mean-squared error of the estimated parameters from both methods, evaluate their dependence on study design and behavior characteristics, and offer an R package so investigators can make an informed choice between the two methods. We demonstrate the difference between the two methods in a recent validation study comparing previous day recalls to an accelerometer-based ActivPal.     

Eminent Social Scientists’ Views on Immigration Issues: 1985 and 2006

Following up on a research note by Stephen Moore published in 1985, this article compares the results of the survey conducted in 1985 against one carried out in 2006 on the views of eminent social scientists (economists, political scientists, psychologists, sociologists, historians and anthropologists) on immigration issues. Specifically, the surveys report on whether the respondents are likely to favor an increase in the number of immigrants who are allowed into the United States and other issues such as whether immigrants improve the economy.

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现代管理科学中的直觉主义

随着信息技术发展迅猛,管理科学移植了许多自然科学的基础理论和研究方法,取得极大进步.然而,在管理实践工作中却经常受到自然科学理论和方法的局限.探索这种局限性的根源,指出直觉以及直觉主义在管理中的哲学意义;提出在管理科学中把握直觉的本质,将直觉主义引入管理科学,从而有效地选择战略和决策.     

Are mating strategies and mating tactics independent constructs?

This study explored the constructs of mating tactics and mating strategy. These constructs are conceptually related but distinct. In current research, the measurement of one of these constructs is often viewed as being indicative of the other. Therefore, an exploration of these constructs will enhance understanding of study outcomes in this research area. Self-report measures of mating tactics and strategies were administered to 183 female participants, aged 18-45 years. The Escalating Sexual Encounters Questionnaire (ESEQ, Greer & Buss, 1994), the Derogatis' Sexual Experience Scale (Derogatis & Melisaratos, 1979), the Sexual Strategies Measure (SSM, Schmitt, 1996), the Sociosexual Orientation Inventory (Simpson & Gangestad, 1991), and two questions assessing age at menarche and total number of sexual partners were administered. Exploratory factor analysis with oblique rotation produced two distinct factors reflecting a "tactic"-based factor and a "strategy"-based factor. This finding is consistent with viewing mating tactics and mating strategies as distinct and varying independently. An important implication of this study is that measurement of mating tactics is not indicative of underlying mating strategies in women. Further, four patterns of female mating style emerged upon review of participant factor scores and are discussed within an evolutionary context.     

Association of sexual abstinence in adolescence with mental health in adulthood

We examined whether adolescent sexual abstinence predicts better adult mental health. 1,917 adolescents, recruited from middle schools at age 13, were surveyed at ages 13, 18, 23, and 29. In bivariate analyses, adolescent sexual abstinence was associated with better mental health at age 29 for females, but not males; three adolescent factors, educational prospects, family bonding, and unconventionality were investigated as explanatory variables of this relationship. The abstinence-mental health relationship was nonsignificant when educational prospects was included in multivariate models, and marginally significant when family bonding and unconventionality were included; all three explanatory factors accounted for significant proportions of the variance in adult mental health. Girls who are uninvolved in school, have weak family backgrounds, and exhibit unconventionality may have poor adult mental health, whether or not they abstain from sex in adolescence. Interventions that strengthen adolescents' connections to families and schools may reduce risk for long-term mental health problems.