Alternative Time Scales and Failure Time Models

In many reliability applications, there may not be a unique plausible scale in which to measure time to failure or assess performance. This is especially the case when several measures of usage are available on each unit. For example, the age, the total number of flight hours, and the number of landings are usage measures that are often considered important in aircraft reliability. Similarly, in medical or biological applications of survival analysis there are often alternative scales (e.g., Oakes, 1995). This paper considers the definition of a "good" time scale, along with methods of determining a time scale.     

The two-sample problem with multivariate censored data: a new rank test family

A new rank test family is proposed to test the equality of two multivariate failure times distributions with censored observations. The tests are very simple: they are based on a transformation of the multivariate rank vectors to a univariate rank score and the resulting statistics belong to the familiar class of the weighted logrank test statistics. The new procedure is also applicable to multivariate observations in general, such as repeated measures, some of which may be missing. To investigate the performance of the proposed tests, a simulation study was conducted with bivariate exponential models for various censoring rates. The size and power of these tests against Lehmann alternatives were compared to the size and power of two other tests (Wei and Lachin, 1984 and Wei and Knuiman, 1987). In all simulations the new procedures provide a relatively good power and an accurate control over the size of the test. A real example from the National Cooperative Gallstone Study is given     

晚明中国的文艺复兴教育——关于耶稣会士高一志《童幼教育》的初步研究

1588年,范礼安在澳门出版了玻尼法爵的《基督教育》,这是在中国用西方技术印刷的第一本书。40余年后,意大利传教士高一志在山西出版了《童幼教育》。本文试图研究这两本书的关系,证明《童幼教育》受到了文艺复兴教育思想的影响,通过对此书来源的分析来阐明它的结构,并且在西方与中国文化相遇的背景之下研究《童幼教育》的意图。     

Linear Regression Models under Conditional Independence Restrictions

Maximum likelihood estimation is investigated in the context of linear regression models under partial independence restrictions. These restrictions aim to assume a kind of completeness of a set of predictors Z in the sense that they are sufficient to explain the dependencies between an outcome Y and predictors X: ?(Y|Z, X) = ?(Y|Z), where ?(·|·) stands for the conditional distribution. From a practical point of view, the former model is particularly interesting in a double sampling scheme where Y and Z are measured together on a first sample and Z and X on a second separate sample. In that case, estimation procedures are close to those developed in the study of double‐regression by Engel & Walstra (1991) and Causeur & Dhorne (1998) . Properties of the estimators are derived in a small sample framework and in an asymptotic one, and the procedure is illustrated by an example from the food industry context.     

Emergence of a consonant bias during the first year of life: New evidence from own‐name recognition

Recent evidence suggests that during the first year of life, a preference for consonant information during lexical processing (consonant bias) emerges, at least for some languages like French. Our study investigated the factors involved in this emergence as well as the developmental consequences for variation in consonant bias emergence. In a series of experiments, we measured 5‐, 8‐, and 11‐month‐old French‐learning infants orientation times to a consonant or vowel mispronunciation of their own name, which is one of the few word forms familiar to infants at this young age. Both 5‐ and 8‐month‐olds oriented longer to vowel mispronunciations, but 11‐month‐olds showed a different pattern, initially orienting longer to consonant mispronunciations. We interpret these results as further evidence of an initial vowel bias, with consonant bias emergence by 11 months. Neither acoustic‐phonetic nor lexical factors predicted preferences in 8‐ and 11‐month‐olds. Finally, counter to our predictions, a vowel bias at the time of test for 11‐month‐olds was related to later productive vocabulary outcomes.     

Social Network and Wage: Evidence from Cameroon

Using Cameroonian data, this paper investigates the effects of social network on wage. Social network is measured in terms of using friends and relatives while looking for a job. In order to evaluate the effectiveness of social network with regard to wage, we make use of Heckman selection model. Our findings contrast with previous studies. After factoring the endogeneity and sample selection, we find that Job seekers who make use of social network exhibit a wage premium of 1.53 per cent of average wage. We also find that social network contributes to explain wage differential according to gender and institutional sectors (formal versus informal).     

ERRATA CORRIGE: “ARE MUSLIM IMMIGRANTS DIFFERENT IN TERMS OF CULTURAL INTEGRATION?”

We are thankful to Michael Lundholm and Mahmood Arai for pointing us towards a coding error which invalidates the regressions in our paper. Correcting the code leads to a decrease in sample sizes, though much smaller than Arai et al. (2011) claim based on their “replication”. An appropriate redefinition of the variables and of the model specification allows us to reproduce the substance of the empirical analysis in our original published paper. Although the results are now less clear‐cut, our analysis remains essentially unchanged.     

Local likelihood density estimation for interval censored data

The authors propose a class of procedures for local likelihood estimation from data that are either interval‐censored or that have been aggregated into bins. One such procedure relies on an algorithm that generalizes existing self‐consistency algorithms by introducing kernel smoothing at each step of the iteration. The entire class of procedures yields estimates that are obtained as solutions of fixed point equations. By discretizing and applying numerical integration, the authors use fixed point theory to study convergence of algorithms for the class. Rapid convergence is effected by the implementation of a local EM algorithm as a global Newton iteration. The latter requires an explicit solution of the local likelihood equations which can be found by using the symbolic Newton‐Raphson algorithm, if necessary.     

Estimation of the Sobol indices in a linear functional multidimensional model

We consider a functional linear model where the explicative variables are known stochastic processes taking values in a Hilbert space, the main example is given by Gaussian processes in L²([0,1])${\mathbb{L}}^2([0,1])$. We propose estimators of the Sobol indices in this functional linear model. Our estimators are based on U-statistics. We prove the asymptotic normality and the efficiency of our estimators and we compare them from a theoretical and practical point of view with classical estimators of Sobol indices.