Sequential Hypothesis Tests for Identifying the Minimum Dose with a Threshold Effect

We propose a procedure to identify a lowest dose having greater effect than a threshold dose under the assumption of monotonicity of dose mean response in dose response test. So, we use statistics based on contrasts among sample means and apply a group sequential procedure to our procedure to identify effectively the dose. If we can identify the dose at an early step in the sequential test, since we can terminate the procedure with a few observations, the procedure is useful from an economical point of view. In a simulation studies, we compare the superiority among these procedures based on three contrasts.     

Selecting the regularization parameters in high-dimensional panel data models: Consistency and efficiency

This article considers panel data models in the presence of a large number of potential predictors and unobservable common factors. The model is estimated by the regularization method together with the principal components procedure. We propose a panel information criterion for selecting the regularization parameter and the number of common factors under a diverging number of predictors. Under the correct model specification, we show that the proposed criterion consistently identifies the true model. If the model is instead misspecified, the proposed criterion achieves asymptotically efficient model selection. Simulation results confirm these theoretical arguments.     

Age related variation of salivary testosterone values in healthy Japanese males

Objective. We examined age associated variation in salivary testosterone values among Japanese males as well as anthropometric measurements.

Methods. Salivary samples were collected in pretreated sodium azide treated tubes. The first series: 15–79-year-old males (n = 99); two morning and two evening samples were collected at home for two days. The second series: 90-year-old males (n = 29); one morning sample was collected. Testosterone values were determined using an iodine125-based radioimmunoassay kit modified for saliva.

Results. Results show 1) a significant decrease in salivary testosterone values from 20s to 40s and older, 2) no significant decline after 40 through 90 years old, 3) no significant age-related differences in the degree of intraindividual diurnal fluctuation across age groups of 40–70s, and 4) higher BMI is associated with the lower salivary testosterone among 40–70s.

Conclusions. These results suggest that neither a constant decrease of salivary testosterone values or markedly reduced intraindividual fluctations are universal aspects of aging. Older males may maintain relatively high testosterone levels compared to younger men and a relatively ‘robust’ neuroendocrinological system.     

Classification and similarity analysis of fundamental frequency patterns in infant spoken language acquisition

Fundamental frequency (F0) patterns, which indicate the vibration frequency of vocal cords, reflect the developmental changes in infant spoken language. In previous studies of developmental psychology, however, F0 patterns were manually classified into subjectively specified categories. Furthermore, since F0 has sequential missing and indicates a mean nonstationarity, classification that employs subsequent partition and conventional discriminant analysis based on stationary and local stationary processes is considered inadequate. Consequently, we propose a classification method based on discriminant analysis of time series data with mean nonstationarity and sequential missing, and a measurement technique for investigating the configuration similarities for classification. Using our proposed procedures, we analyse a longitudinal database of recorded conversations between infants and parents over a five-year period. Various F0 patterns were automatically classified into appropriate pattern groups, and the classification similarities calculated. These similarities gradually decreased with infant’s monthly age until a large change occurred around 20 months. The results suggest that our proposed methods are useful for analysing large-scale data and can contribute to studies of infant spoken language acquisition.     

日本冲绳本岛临海民居风景防护林的构建及对中国新民居建设的启示

为加快推进中国农村新民居建设,完善相关配套建设措施,笔者借鉴日本在防灾减灾理论和方法方面处于世界前列,以法律的形式保证规划先行的经验,通过对冲绳本岛相关历史资料分析、民意调查和实地调查,以及福木起源的追溯,福木数量和防护林密度的测算等,论证了福木风景防护林映衬红瓦木造建筑为冲绳典型集落(即村庄、村落)特征.风景防护林的构建源自于村民抵御自然灾害的本能和政府保一方平安的责任意识,最后发展为保护村民生活环境、保障社会安定的基础.同时防护林使冲绳自然环境更显生态美观,促进了旅游业的兴旺,旅游已成为冲绳的支柱产业.     

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.     

The Finite-Sample Performance of White's Test for Heteroskedasticity Under Stochastic Regressors

We study the finite-sample properties of White's test for heteroskedasticity in stochastic regression models where explanatory variables are random and not given. We investigate by simulation the effect of non independence of explanatory variables and error term and heteroskedasticity on White's test. A standard bootstrap method in the computationally convenient form is found to work well with respect to the size and power.     

Matrix decomposition in meta-analysis for extraction of adverse event pattern and patient-level safety profile

The purpose of assessing adverse events (AEs) in clinical studies is to evaluate what AE patterns are likely to occur during treatment. In contrast, it is difficult to specify which of these patterns occurs in each patient. To tackle this challenging issue, we constructed a new statistical model including nonnegative matrix factorization by incorporating background knowledge of AE-specific structures such as severity and drug mechanism of action. The model uses a meta-analysis framework for integrating data from multiple clinical studies because insufficient information is derived from a single trial. We demonstrated the proposed method by applying it to real data consisting of three Phase III studies, two mechanisms of action, five anticancer treatments, 3317 patients, 848 AE types, and 99,546 AEs. The extracted typical treatment-specific AE patterns coincided with medical knowledge. We also demonstrated patient-level safety profiles using the data of AEs that were observed by the end of the second cycle.     

A Simulation Study of White's Test for Heteroskedasticity in Fixed and Stochastic Regression Models

We study the finite-sample properties of White's test for heteroskedasticity in fixed and stochastic regression models. We compare by simulation White and bootstrap methods when the underlying distribution is symmetric as well as asymmetric. The superior performance of the bootstrap method in small samples does not hold when the underlying distribution is asymmetric.