Robust regression: an inferential method for determining which independent variables are most important

Consider the usual linear regression model consisting of two or more explanatory variables. There are many methods aimed at indicating the relative importance of the explanatory variables. But in general these methods do not address a fundamental issue: when all of the explanatory variables are included in the model, how strong is the empirical evidence that the first explanatory variable is more or less important than the second explanatory variable? How strong is the empirical evidence that the first two explanatory variables are more important than the third explanatory variable? The paper suggests a robust method for dealing with these issues. The proposed technique is based on a particular version of explanatory power used in conjunction with a modification of the basic percentile method.     

Sample size determination for testing equality in frequency data under an incomplete block crossover design

When there are more than two treatments under comparison, we may consider the use of the incomplete block crossover design (IBCD) to save the number of patients needed for a parallel groups design and reduce the duration of a crossover trial. We develop an asymptotic procedure for simultaneously testing equality of two treatments versus a control treatment (or placebo) in frequency data under the IBCD with two periods. We derive a sample size calculation procedure for the desired power of detecting the given treatment effects at a nominal-level and suggest a simple ad hoc adjustment procedure to improve the accuracy of the sample size determination when the resulting minimum required number of patients is not large. We employ Monte Carlo simulation to evaluate the finite-sample performance of the proposed test, the accuracy of the sample size calculation procedure, and that with the simple ad hoc adjustment suggested here. We use the data taken as a part of a crossover trial comparing the number of exacerbations between using salbutamol or salmeterol and a placebo in asthma patients to illustrate the sample size calculation procedure.     

The conditional maximum of Poisson random variables

The conditional maxima of independent Poisson random variables are studied. A triangular array of row-wise independent Poisson random variables is considered. If condition is given for the row-wise sums, then the limiting distribution of the row-wise maxima is concentrated onto two points. The result is in accordance with the classical result of Anderson. The case of general power series distributions is also covered. The model studied in Theorems 2.1 and 2.2 is an analogue of the generalized allocation scheme. It can be considered as a non homogeneous generalized scheme of allocations of at most n balls into N boxes. Then the maximal value of the contents of the boxes is studied.     

On the Use of GLS Demeaning in Panel Unit Root Testing

One of the most well-known facts about unit root testing in time series is that the Dickey–Fuller (DF) test based on ordinary least squares (OLS) demeaned data suffers from low power, and that the use of generalized least squares (GLS) demeaning can lead to substantial power gains. Of course, this development has not gone unnoticed in the panel unit root literature. However, while the potential of using GLS demeaning is widely recognized, oddly enough, there are still no theoretical results available to facilitate a formal analysis of such demeaning in the panel data context. The present article can be seen as a reaction to this. The purpose is to evaluate the effect of GLS demeaning when used in conjuncture with the pooled OLS t-test for a unit root, resulting in a panel analog of the time series DF–GLS test. A key finding is that the success of GLS depend critically on the order in which the dependent variable is demeaned and first-differenced. If the variable is demeaned prior to taking first-differences, power is maximized by using GLS demeaning, whereas if the differencing is done first, then OLS demeaning is preferred. Furthermore, even if the former demeaning approach is used, such that GLS is preferred, the asymptotic distribution of the resulting test is independent of the tuning parameters that characterize the local alternative under which the demeaning performed. Hence, the demeaning can just as well be performed under the unit root null hypothesis. In this sense, GLS demeaning under the local alternative is redundant.     

Bootstrap tests for time varying cointegration

This article proposes wild and the independent and identically distibuted (i.i.d.) parametric bootstrap implementations of the time-varying cointegration test of Bierens and Martins (2010 Bierens, H. J., Martins, L. F. (2010). Time varying cointegration. Econometric Theory 26:1453–1490.[Crossref], [Web of Science ®] , [Google Scholar]). The bootstrap statistics and the original likelihood ratio test share the same first-order asymptotic null distribution. Monte Carlo results suggest that the bootstrap approximation to the finite-sample distribution is very accurate, in particular for the wild bootstrap case. The tests are applied to study the purchasing power parity hypothesis for twelve Organisation for Economic Cooperation and Development (OECD) countries and we only find evidence of a constant long-term equilibrium for the U.S.–U.K. relationship.     

Use of a historical control group in a noninferiority trial assessing a new antibacterial treatment: A case study and discussion of practical implementation aspects

When recruitment into a clinical trial is limited due to rarity of the disease of interest, or when recruitment to the control arm is limited due to ethical reasons (eg, pediatric studies or important unmet medical need), exploiting historical controls to augment the prospectively collected database can be an attractive option. Statistical methods for combining historical data with randomized data, while accounting for the incompatibility between the two, have been recently proposed and remain an active field of research. The current literature is lacking a rigorous comparison between methods but also guidelines about their use in practice. In this paper, we compare the existing methods based on a confirmatory phase III study design exercise done for a new antibacterial therapy with a binary endpoint and a single historical dataset. A procedure to assess the relative performance of the different methods for borrowing information from historical control data is proposed, and practical questions related to the selection and implementation of methods are discussed. Based on our examination, we found that the methods have a comparable performance, but we recommend the robust mixture prior for its ease of implementation.     

Microfinance Participation and Women's Empowerment: Evidence from a Nationally Representative Sample of Women in Bangladesh

ABSTRACT

More than 30 million married women in Bangladesh access microfinance, an empowering anti-poverty tool, amidst mixed responses from scholars about microfinance's empowering effect. The present study evaluates whether microfinance participation empowers women using a culturally suitable conceptualization of empowerment constituting autonomy, decision-making power in the household, and justification of partner violence. This study utilizes data from a representative probability sub-sample of 6,150 married women aged between 15 and 49 years from the Bangladesh Demographic and Health Survey 2011 to assess the difference in empowerment between microfinance participants and a control group using propensity score matching techniques. Findings revealed that women who participated in microfinance were not statistically different at the 0.05 level from women who did not participate in microfinance in terms of empowerment when groups were matched on socio-demographic variables ensuring that treatment and comparison groups had equal propensity to participate in microfinance, casting doubt on the assertion that microfinance participation positively affects women's empowerment. Future research needs to focus on what empowerment may mean in relation to the outside world; we need to move beyond a familial understanding of empowerment to examine the individual in terms of her individual identity in the socio-political world in which she resides.     

学术话语权与中国社会学发展(英文)

作为“权利”的学术话语权,主要有创造更新权、意义赋予权、学术自主权等类型;作为“权力”的学术话语权,主要有指引导向权、鉴定评判权、行动支配权等类型。这些也体现在中国社会学百余年的发展历程中。在中国社会学初创阶段,严复等人在社会学本土化和学术话语创新方面进行了尝试。费孝通经历了中国社会学前期发展阶段近20年及后期56年全过程,其学术历程对于中国社会学发展史具有典型意义。在理论自觉基础上努力达致学术话语权的制高点,是中国社会学从世界学术格局边陲走向中心的一条必由之路。     

家族企业权力配置对会计稳健性影响的实证分析

以2005~2014年福建省家族企业作为研究对象,考察家族企业的权力配置对企业会计稳健性的影响。通过对310个样本企业的实证分析发现,与家族企业实际控制人不担任董事长和总经理任何一个职位的企业相比,家族企业实际控制人担任董事长、总经理之一或者同时担任董事长和总经理的企业,会计稳健性更差;家族控制力越强,会计稳健性越差。研究结果表现,家族介入企业运营管理削弱了企业会计信息质量。     

历史记忆与家族建构——以湘西田氏土司后裔为中心的考察

作为传递历史记忆的媒介,口述传说、文字、身体、仪式、碑刻等不一定能完全客观地呈现历史事实,但透过这些方式选择、重组与诠释的“过去”,往往成为人们合理化当前社会现实的重要方式。湘西古丈县田家洞为改土归流前永顺宣慰司下辖的小长官司,村中土司后裔——田氏自改革开放后,藉由祖先传说、修谱与立碑、仪式展演等活动叙写家族历史,强化族众认同。实际上,围绕历史记忆展开的家族建构不仅体现了不同能动者之间的权力角逐,也为诠释“传统”在现代社会的复苏提供了一种视角。