Two-Step Residual-Based Estimation of Error Variances for Generalized Least Squares in Split-Plot Experiments

In split-plot experiments, estimation of unknown parameters by generalized least squares (GLS), as opposed to ordinary least squares (OLS), is required, owing to the existence of whole- and subplot errors. However, estimating the error variances is often necessary for GLS. Restricted maximum likelihood (REML) is an established method for estimating the error variances, and its benefits have been highlighted in many previous studies. This article proposes a new two-step residual-based approach for estimating error variances. Results of numerical simulations indicate that the proposed method performs sufficiently well to be considered as a suitable alternative to REML.     

Conceptualizing maternal and paternal autonomy support and control among adolescents in Hong Kong

This study examined how parental autonomy support and control are conceptualized by adolescents in Hong Kong (Grades 7–11) using the Perceived Parental Autonomy Support Scale. Competitive models were evaluated using confirmatory factor analyses. Although the 6-factor model demonstrated the best fit, further analyses indicated that a second-order structure was more appropriate. Provision of choice, acknowledgment of child's feelings, rationale for rules, and demands subsumed under autonomy support. Guilt-inducing criticisms and the use of threats subsumed under control. Performance pressure emerged as a first-order construct on its own. Measurement invariance was evident across adolescent gender and age. All subscales had adequate to strong reliability. Discriminate validity was evident. Findings offer insights into the conceptualization of autonomy support and control in Hong Kong.     

Nonlinear regression modeling via the lasso-type regularization

We consider the problem of constructing nonlinear regression models with Gaussian basis functions, using lasso regularization. Regularization with a lasso penalty is an advantageous in that it estimates some coefficients in linear regression models to be exactly zero. We propose imposing a weighted lasso penalty on a nonlinear regression model and thereby selecting the number of basis functions effectively. In order to select tuning parameters in the regularization method, we use a deviance information criterion proposed by Spiegelhalter et al. (2002), calculating the effective number of parameters by Gibbs sampling. Simulation results demonstrate that our methodology performs well in various situations.     

On Small Sample Properties of the Wald,LR and LM Tests in a Linear Model with AR(1) Errors

When the error terms are autocorrelated, the conventional t-tests for individual regression coefficients mislead us to over-rejection of the null hypothesis. We examine, by Monte Carlo experiments, the small sample properties of the unrestricted estimator of ρ and of the estimator of ρ restricted by the null hypothesis. We compare the small sample properties of the Wald, likelihood ratio and Lagrange multiplier test statistics for individual regression coefficients. It is shown that when the null hypothesis is true, the unrestricted estimator of ρ is biased. It is also shown that the Lagrange multiplier test using the maximum likelihood estimator of ρ performs better than the Wald and likelihood ratio tests.     

Nonlinear regression modeling via regularized radial basis function networks

The problem of constructing nonlinear regression models is investigated to analyze data with complex structure. We introduce radial basis functions with hyperparameter that adjusts the amount of overlapping basis functions and adopts the information of the input and response variables. By using the radial basis functions, we construct nonlinear regression models with help of the technique of regularization. Crucial issues in the model building process are the choices of a hyperparameter, the number of basis functions and a smoothing parameter. We present information-theoretic criteria for evaluating statistical models under model misspecification both for distributional and structural assumptions. We use real data examples and Monte Carlo simulations to investigate the properties of the proposed nonlinear regression modeling techniques. The simulation results show that our nonlinear modeling performs well in various situations, and clear improvements are obtained for the use of the hyperparameter in the basis functions.     

Obesity over the life course

Obesity in middle-aged humans is a risk factor for many age-related diseases and decreases life expectancy by about 7 years, which is roughly comparable to the combined effect of all cardiovascular disease and cancer on life span. The prevalence of obesity increases up until late middle age and decreases thereafter. Mechanisms that lead to increased obesity with age are not yet well understood, but current evidence implicates impairments in hypothalamic function, especially impairments in the ability of hypothalamic pro-opiomelanocortin neurons to sense nutritional signals. The rapid increase in the prevalence of obesity at all ages in the past decade suggests that, in the next two or three decades, diseases associated with obesity, especially diabetes, will begin to rise rapidly. Indeed, these trends suggest that for the first time in modern history, the life expectancy of people in developed societies will begin to decrease, unless the rapid increase in the prevalence of obesity can be reversed.     

宇野理论与广松涉的价值概念

价值本身的阐明,在马克思那里是以与价值实体论相混合的形式而展开的,后来的多数马克思学派也继承了这一缺陷。与此相对,作为有别于眼下价值实体论而阐明价值本身的性质的尝试,是日本的两位研究者即宇野弘藏和广松涉的研究。宇野认为:论证劳动价值说(及剩余价值论)即,《资本论》应该不是开头,而是第三篇绝对剩余价值的生产之后才展开价值实体论,第一篇、第二篇则是与作为流通形式论(商品、货币、资本这种价值本身的存在方式的分析)。而广松认为:价值不是单以物理的存在为出发点,而是主体间性地形成的既不是主观的判断也不是客观的实在的东西。     

Lifetime Assessment by Intermittent Inspection under the Mixture Weibull Power Law Model with Application to XLPE Cables

This paper proposes a new treatment for electrical insulation degradation. Some types of insulation which have been used under various circumstances are considered to degrade at various rates in accordance with their stress circumstances. The cross-linked polyethylene (XLPE) insulated cables inspected by major Japanese electric companies clearly indicate such phenomena. By assuming that the inspected specimen is sampled from one of the clustered groups, a mixed degradation model can be constructed. Since the degradation of the insulation under common circumstances is considered to follow a Weibull distribution, a mixture model and a Weibull power law can be combined. This is called The mixture Weibull power law model. By using the maximum likelihood estimation for the newly proposed model to Japanese 22 and 33kV insulation class cables, they are clustered into a certain number of groups by using the AIC and the generalized likelihood ratio test method. The reliability of the cables at specified years are assessed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Games of Capacity Manipulation in Hospital-intern Markets

In this paper, we analyze capacity manipulation games in hospital-intern markets inspired by the real-life entry-level labor markets for young physicians who seek residencies at hospitals. In a hospital-intern market, the matching is determined by a centralized clearinghouse using the preferences revealed by interns and hospitals and the number of vacant positions revealed by hospitals. We consider a model in which preferences of hospitals and interns are common knowledge. Hospitals play a capacity-reporting game. We analyze the equilibria of the game-form under the two most widely used matching rules: hospital-optimal and intern-optimal stable rules. We show that (i) there may not be a pure strategy equilibrium in general; and (ii) when a pure strategy equilibrium exists, every hospital weakly prefers this equilibrium outcome to the outcome of any larger capacity profile. Finally, we present conditions on preferences to guarantee the existence of pure strategy equilibria.