Analysis of survival data by a Weibull-generalized Poisson distribution

In life-testing and survival analysis, sometimes the components are arranged in series or parallel system and the number of components is initially unknown. Thus, the number of components, say Z, is considered as random with an appropriate probability mass function. In this paper, we model the survival data with baseline distribution as Weibull and the distribution of Z as generalized Poisson, giving rise to four parameters in the model: increasing, decreasing, bathtub and upside bathtub failure rates. Two examples are provided and the maximum-likelihood estimation of the parameters is studied. Rao's score test is developed to compare the results with the exponential Poisson model studied by Kus [17] and the exponential-generalized Poisson distribution with baseline distribution as exponential and the distribution of Z as generalized Poisson. Simulation studies are carried out to examine the performance of the estimates.     

浅谈学分制条件下的成绩管理

学习成绩的管理对学生在校期间的各项管理都有着重要的影响,通过统计、分析、预测等工作,可以为学分制改革和学校其他各项改革或决策提供有参考价值的数据信息。     

Testing for normality in linear regression models

The importance of the normal distribution for fitting continuous data is well known. However, in many practical situations data distribution departs from normality. For example, the sample skewness and the sample kurtosis are far away from 0 and 3, respectively, which are nice properties of normal distributions. So, it is important to have formal tests of normality against any alternative. D'Agostino et al. [A suggestion for using powerful and informative tests of normality, Am. Statist. 44 (1990), pp. 316–321] review four procedures Z ²(g ₁), Z ²(g ₂), D and K ² for testing departure from normality. The first two of these procedures are tests of normality against departure due to skewness and kurtosis, respectively. The other two tests are omnibus tests. An alternative to the normal distribution is a class of skew-normal distributions (see [A. Azzalini, A class of distributions which includes the normal ones, Scand. J. Statist. 12 (1985), pp. 171–178]). In this paper, we obtain a score test (W) and a likelihood ratio test (LR) of goodness of fit of the normal regression model against the skew-normal family of regression models. It turns out that the score test is based on the sample skewness and is of very simple form. The performance of these six procedures, in terms of size and power, are compared using simulations. The level properties of the three statistics LR, W and Z ²(g ₁) are similar and close to the nominal level for moderate to large sample sizes. Also, their power properties are similar for small departure from normality due to skewness (γ₁≤0.4). Of these, the score test statistic has a very simple form and computationally much simpler than the other two statistics. The LR statistic, in general, has highest power, although it is computationally much complex as it requires estimates of the parameters under the normal model as well as those under the skew-normal model. So, the score test may be used to test for normality against small departure from normality due to skewness. Otherwise, the likelihood ratio statistic LR should be used as it detects general departure from normality (due to both skewness and kurtosis) with, in general, largest power.     

Statistical diagnostics for nonlinear regression models based on scale mixtures of skew-normal distributions

The purpose of this paper is to develop diagnostics analysis for nonlinear regression models (NLMs) under scale mixtures of skew-normal (SMSN) distributions introduced by Garay et al. [Nonlinear regression models based on SMSN distributions. J. Korean Statist. Soc. 2011;40:115–124]. This novel class of models provides a useful generalization of the symmetrical NLM [Vanegas LH, Cysneiros FJA. Assessment of diagnostic procedures in symmetrical nonlinear regression models. Comput. Statist. Data Anal. 2010;54:1002–1016] since the random terms distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as the skew-t, skew-slash, skew-contaminated normal distributions, among others. Motivated by the results given in Garay et al. [Nonlinear regression models based on SMSN distributions. J. Korean Statist. Soc. 2011;40:115–124], we presented a score test for testing the homogeneity of the scale parameter and its properties are investigated through Monte Carlo simulations studies. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. The newly developed procedures are illustrated considering a real data set.     

Efficiency Bounds for Missing Data Models With Semiparametric Restrictions

This paper shows that the semiparametric efficiency bound for a parameter identified by an unconditional moment restriction with data missing at random (MAR) coincides with that of a particular augmented moment condition problem. The augmented system consists of the inverse probability weighted (IPW) original moment restriction and an additional conditional moment restriction which exhausts all other implications of the MAR assumption. The paper also investigates the value of additional semiparametric restrictions on the conditional expectation function (CEF) of the original moment function given always observed covariates. In the program evaluation context, for example, such restrictions are implied by semiparametric models for the potential outcome CEFs given baseline covariates. The efficiency bound associated with this model is shown to also coincide with that of a particular moment condition problem. Some implications of these results for estimation are briefly discussed.     

谈钢琴教学中读谱、演奏技巧与乐感的综合培养——以肖邦夜曲op.9-no.1作品教学为例

钢琴演奏是一个综合的整体艺术,在钢琴教学中,需运用辩证统一的教学模式——即将读谱、演奏技法以及乐感的培养三者相互协调、促进。并通过钢琴教学中的演奏及乐感的培养来促进学生的循环认知、模式信息认知与演奏技巧创新认知等能力的培养。肖邦夜曲op.9-no.1音乐语言丰富多彩,通过肖邦的这部夜曲作品教学的分析可以帮助我们研究和了解肖邦的创作追求,帮助学生增加抒情性乐曲的乐感与演奏技巧。     

Bayesian misclassification and propensity score methods for clustered observational studies

Bayesian propensity score regression analysis with misclassified binary responses is proposed to analyse clustered observational data. This approach utilizes multilevel models and corrects for misclassification in the responses. Using the deviance information criterion (DIC), the performance of the approach is compared with approaches without correcting for misclassification, multilevel structure specification, or both in the study of the impact of female employment on the likelihood of physical violence. The smallest DIC confirms that our proposed model best fits the data. We conclude that female employment has an insignificant impact on the likelihood of physical spousal violence towards women. In addition, a simulation study confirms that the proposed approach performed best in terms of bias and coverage rate. Ignoring misclassification in response or multilevel structure of data would yield biased estimation of the exposure effect.     

School factors helping disadvantaged students to succeed: empirical evidence from four Italian cities

This research investigates a particular category of disadvantaged students, namely those who are able to overcome a situation of socio-economical disadvantage and obtain good academic results (here named ‘resilient students’). We have used micro-data provided by the Italian National Evaluation Committee for Education and focused on class and school-level characteristics that help disadvantaged students to become resilient students when they move from primary (grade 5) to lower secondary school (grade 6), concentrating our analysis on four major cities. We employed a probit regression and a propensity score matching model, finding that class and school factors do matter. In particular, we looked at whether the performance of their peers has a positive impact on that of disadvantaged students, estimating the increased probability of these students becoming resilient.     

同乡的力量：同乡聚集对农民工工资收入的影响

中国的城乡流动中存在同一籍贯或同一来源地的农村流动人口的就业聚集现象--“同乡聚集”。本研究使用2010年珠三角和长三角外来务工者调查的数据,采用倾向分数匹配和异质性干预模型等方法,考察了以籍贯为族群基础的同乡聚集对城市农民工经济收入的影响。研究发现,尽管同乡聚集者的收入优势受到异质性和自我选择机制的影响,但同乡聚集仍有助于提高农民工的工资收入。越倾向于同乡聚集的农民工,从同乡聚集中获得的收入回报越高。     

The Model Development Dissertation

ABSTRACT

Asset-building programs, such as Individual Development Account (IDA) programs within social service agencies, assist low-income employed clients in building credit, purchasing affordable assets, and gaining wealth. This longitudinal exploratory study examines the credit outcomes of IDA programs to add to the knowledge concerning the effects of IDAs as an asset-building tool. Data were analyzed using a convenience sample of IDA participants and nonparticipants (N = 164), and the results indicated that initial credit score and history are associated with program participation. However, results also suggested that initial credit score is not a meaningful indicator of program completion, time to completion, or type of asset purchased for participants. Those who completed the IDA program within 2 years experienced the highest credit gains. Future research with larger samples is needed to further assess the impact of credit on program participation and completion and on whether credit gains are sustained.