全球城市：我们还能视而不见吗-

本文呼吁在世界事务研究中对全球城市给予更多的关注,以便更全面地解读全球治理这一由相互重叠的管辖权力范围组成的多层次的进程。文章指出,国际研究对全球城市的战略角色非常不敏感,同时展现了全球城市如何通过发挥其联网能力在世界舞台上演绎纵横,从城市的角度为厘清全球治理多层次的治理性提供了线索。笔者认为,通过全球城市的视角,能够使理论学者将被治理方式与政治团体相隔开的宏观进程与微观动态联系起来。     

Differences between matched heterosexual and non-heterosexual college students on defense mechanisms and psychopathological symptoms

Differences between heterosexual and non-heterosexual college students on measures of defense mechanisms and psychopathological symptoms were examined. Fifty-six (28 heterosexual, 28 non-heterosexual) subjects were drawn from a larger study of college student adjustment. Non-heterosexual subjects were matched to a heterosexual peer on several demographic variables as well as on attachment security/insecurity. Differences between the two groups on the Defense Mechanism Inventory and the Brief Symptom Inventory were tested. Contrary to traditional psychoanalytic conceptions of homosexuality, no differences were found between the two groups on any subscale of the Defense Mechanism Inventory, thereby repudiating one important aspect of traditional psychoanalytic theories on the development of homosexuality. Non-heterosexual students reported significantly higher levels of anxiety, depression, somaticization, paranoid ideation, general symptom severity, and suicidal ideation. These students appear to be at increased risk for psychopathology and suicidal ideation, despite similar defense profiles, when compared to matched heterosexual peers. Additional research is needed to determine the origins of this increased risk, and comprehensive and targeted prevention and intervention programs must be established to ameliorate such risks.     

The determinants of breast-feeding in sri lanka

Breast-feeding is the focus of rapidly growing interest. Research on the determinants of breast-feeding is only beginning. The research in this paper is based on World Fertility Survey data for Sri Lanka. We develop what we believe to be an appropriate probit model and find that there are significant socioeconomic factors that influence breast-feeding, in addition to the demographic factors focused upon in the literature. Moreover, some of them have clear policy implications, which are elaborated herein with respect to labor force, education, family planning and internal migration policies. In the course of the paper we also address a number of generally neglected statistical issues that should be considered in analyzing the determinants of breastfeeding, including problems resulting from digit preference or age heaping, the need to use dichotomous dependent variables, unavoidable truncation biases in the basic data, and structural shifts in the determinants of breastfeeding at different durations.     

CLASS SIZE AND CLASS HETEROGENEITY

We study how class size and class composition affect the academic and labor market performance of college students, two crucial policy questions given the secular increase in college enrollment. Our identification strategy relies on the random assignment of students to teaching classes. We find that a one standard deviation increase in class‐size results in a 0.1 standard deviation deterioration of the average grade. Further, the effect is heterogeneous as it is stronger for males and lower income students. Also, the effects of class composition in terms of gender and ability appear to be inverse U‐shaped. Finally, a reduction of 20 students (one standard deviation) in one’s class size has a positive effect on monthly wages of about €80 ($115) or 6% over the average.     

A Two-Latent-Class Model for Smoking Cessation Data with Informative Dropouts

Non ignorable missing data is a common problem in longitudinal studies. Latent class models are attractive for simplifying the modeling of missing data when the data are subject to either a monotone or intermittent missing data pattern. In our study, we propose a new two-latent-class model for categorical data with informative dropouts, dividing the observed data into two latent classes; one class in which the outcomes are deterministic and a second one in which the outcomes can be modeled using logistic regression. In the model, the latent classes connect the longitudinal responses and the missingness process under the assumption of conditional independence. Parameters are estimated by the method of maximum likelihood estimation based on the above assumptions and the tetrachoric correlation between responses within the same subject. We compare the proposed method with the shared parameter model and the weighted GEE model using the areas under the ROC curves in the simulations and the application to the smoking cessation data set. The simulation results indicate that the proposed two-latent-class model performs well under different missing procedures. The application results show that our proposed method is better than the shared parameter model and the weighted GEE model.     

A Dynamic Latent Model for Poverty Measurement

The main purpose of this paper is the longitudinal analysis of the poverty phenomenon. By interpreting poverty as a latent variable, we are able to resort to the statistical methodology developed for latent structure analysis. In particular, we propose to use the mixture latent Markov model which allows us to achieve two goals: (i) a time-invariant classification of households into homogenous groups, representing different levels of poverty; (ii) the dynamic analysis of the poverty phenomenon which highlights the distinction between transitory and permanent poverty situations. Furthermore, we exploit the flexibility provided by the model in order to achieve the measurement of poverty in a multidisciplinary framework, using several socio-economic indicators as covariates and identifying the main relevant factors which influence permanent and transitory poverty. The analysis of the longitudinal data of the Survey on Households Income and Wealth of the Bank of Italy provides the identification of two groups of households which are characterized by different dynamic features. Moreover, the inclusion of socio-economic covariates such as level of education, employment status, geographical area and residence size of the household head shows a direct association with permanent poverty.     

Re-randomization tests as sensitivity analyses to confirm immunological noninferiority of an investigational vaccine: Case study

Here we present as case study how re-randomization tests were performed in two randomized, controlled clinical trials as sensitivity analyses, as recommended by the United States Food and Drug Administration in the context of adaptive randomization. This was done to confirm primary conclusions on immunological noninferiority of an investigational new fully liquid presentation of a quadrivalent cross-reacting material conjugate meningococcal vaccine (MenACWY-CRM), over its licensed lyophilized/liquid presentation. In two phase 2b studies (Study #1: NCT03652610; Study #2: NCT03433482), noninferiority of the fully liquid presentation of MenACWY-CRM to the licensed presentation was assessed and demonstrated for immune responses against meningococcal serogroup A (MenA), the only vaccine component modified from lyophilized to liquid in the new presentation. The original vaccine assignment algorithm, with a minimization procedure accounting for center or center within age strata, was used to re-randomize participants belonging to the fully liquid and licensed vaccine groups while keeping antibody responses, covariates and entry order as observed. Test statistics under re-randomization were generated according to the ANCOVA model used in the primary analysis. To confirm immunological noninferiority following re-randomization, the corresponding p-values had to be <0.025. For both studies and all primary objective evaluations, the re-randomization p-values were well below 0.025 (0.0004 for Study #1; 0.0001 for the two co-primary endpoints in Study #2). Re-randomization tests performed to comply with a regulatory request confirmed the primary conclusions of immunological noninferiority for the MenA of the fully liquid compared to the licensed vaccine presentation.     

Modelling Incomplete Spells of Unemployment and Employment

ABSTRACT: The procedure used to analyse a data set which includes only censored or incomplete spells is examined in this paper. First of all, the distributions of incomplete spell durations are analysed without explanatory variables (such as age, gender, and so on), assuming that unobserved completed spells have a Weibull distribution. The relationships between the mean of the incomplete spells and the mean of the completed spells are reported for first-job seekers, unemployed, employed and self-employed workers. Given that the unobserved completed spells are Weibull-distributed, the unobserved heterogeneity is introduced on the scale parameter of the Weibull. The heterogeneity, considered as a variable, is analysed for a binomial or Weibull distribution. As the beginning of a spell is a retrospective datum, the recall errors are modelled including the heaping effect. Using some proportional hazards models, the methodology to study the influences of explanatory variables on spell distributions is then described, once again including both the heterogeneity and the heaping effect. On this basis, the lengths of on-going spells of unemployment for first-job seekers and unemployed workers are modelled, as well as the current job tenures of employed and self-employed workers.