The effect of small sample on optimal designs for logistic regression models

Asymptotic methods are commonly used in statistical inference for unknown parameters in binary data models. These methods are based on large sample theory, a condition which may be in conflict with small sample size and hence leads to poor results in the optimal designs theory. In this paper, we apply the second order expansions of the maximum likelihood estimator and derive a matrix formula for the mean square error (MSE) to obtain more precise optimal designs based on the MSE. Numerical results indicate the new optimal designs are more efficient than the optimal designs based on the information matrix.     

Investigating the impact of violations of the “left and top means first” heuristic on response behavior and data quality

ABSTRACT

Web surveys are an established data collection mode that use written language to provide information. The written language is accompanied by visual elements, such as presentation formats and shapes. However, research has shown that visual elements influence response behavior because respondents sometimes use interpretive heuristics to make sense of the visual elements. One such heuristic is the ‘left and top means first’ (LTMF) heuristic, which suggests that respondents tend to believe that a response scale consistently runs from left to right or from top to bottom. We conducted a web survey experiment to investigate how violations of the LTMF heuristic affect response behavior and data quality. For this purpose, a random half of respondents received response options that followed a consistent order and the other half received response options that followed an inconsistent order. The results reveal significantly different response distributions between the two groups. We also found that inconsistently ordered response options significantly increase response times and decrease data quality in terms of criterion validity. We, therefore, recommend using options that follow the design strategies of the LTMF heuristic.     

To what extent is social security spending associated with enhanced firm-level performance? A case study of SMEs in Indonesia

Although the relationship between social protection and enterprise performance is much debated in the literature, evidence is particularly limited in the case of small and medium-sized enterprises in developing economies. Using census data from 2010 to 2014, this article examines how the provision of social security influenced business performance in Indonesia. The author finds that increased social security spending of 10 per cent is associated with a per-worker revenue gain of up to 2 per cent. Moreover, profits are not found to decrease with increased social protection coverage, suggesting that increasing worker benefits may be a worthwhile business investment.     

A class of additive transformation models for recurrent gap times

Abstract

The gap time between recurrent events is often of primary interest in many fields such as medical studies, and in this article, we discuss regression analysis of the gap times arising from a general class of additive transformation models. For the problem, we propose two estimation procedures, the modified within-cluster resampling (MWCR) method and the weighted risk-set (WRS) method, and the proposed estimators are shown to be consistent and asymptotically follow the normal distribution. In particular, the estimators have closed forms and can be easily determined, and the methods have the advantage of leaving the correlation among gap times arbitrary. A simulation study is conducted for assessing the finite sample performance of the presented methods and suggests that they work well in practical situations. Also the methods are applied to a set of real data from a chronic granulomatous disease (CGD) clinical trial.     

The effects of individually varying times of observations on growth parameter estimations in piecewise growth model

When using latent growth modeling (LGM), researchers often restrict the factor loadings, while the multilevel modeling (MLM) treats time as a metric variable. However, when individually varying times of observations are concerned in the longitudinal studies, the use of specified loadings would lead to inaccurate estimation. Based on piecewise growth modeling (PGM), this simulation study showed that (i) individually varying times of observations with larger boundaries got worse estimates and model fits when LGM was used; (ii) estimating the PGM across all the simulation situations was robust within MLM, whereas LGM got identically equal estimation with MLM only in the case of time boundaries of ±1 month or shorter; (iii) larger change of slope in piecewise modeling indicated better estimation.     

基于违约鉴别能力组合赋权的小企业信用评级——基于小型工业企业样本数据的实证分析

信用评级是衡量债务违约的可能性,因此评级体系要有违约风险识别能力,能够将违约客户和非违约客户显著地区分开.通过逼近理想点的思路,构建多目标规划模型求解最优的组合权重,并对中国某区域性商业银行1 814笔小型工业企业贷款进行实证分析.本文的创新与特色一是以非违约企业的数据到正理想点的距离代数和最小为第一个目标函数,以违约企业的数据到负理想点的距离代数和最小为第二个目标函数,构建多目标非线性规划模型进行组合赋权,在满足了“非违约企业的评价得分越高、违约企业的评价得分越低”要求的目标下得到最优的组合赋权的权重系数,使赋权结果保证了评级模型能够将违约企业与非违约企业最大地区分开.改变了现有研究的组合赋权脱离评价目的的弊端,改变了现有研究中违约与非违约企业的评价得分存在大量重叠、对两类企业的区分能力低的弊端.二是通过检验“违约企业的信用得分是否显著小于非违约企业的信用得分”的J-T非参数检验,验证信用评价模型的合理性.改变现有研究忽略对信用评价模型的合理性进行验证的弊端.三是经过实证,发现本研究建立的组合赋权模型的违约鉴别能力(Z=5.546)要高于现有研究的两种常用组合赋权模型、即基于方差最大的组合赋权(Z=4.298)和基于偏差最小的组合赋权(Z=5.182)     

从主权国家的兴衰看权力博弈形态的转型

传统的国际关系理论,无论是现实主义、自由主义、建构主义还是科学行为主义理论,都是把主权国家抽象成一个统一的国际关系行为体。这一行为主体有一致的利益,也自然要有一致的对外政策目标和手段。在20世纪,尤其是在两次世界大战和冷战期间,这一概念抽象是非常准确的。但冷战结束以后,尤其是进入21世纪以后,这一概念抽象逐渐与国际关系的现实相违背。一方面,国家综合实力并不能直接转化为具体领域的竞争优势;另一方面,很多国家,包括超级大国在内,其对外政策的主要阻力可能不是所谓的竞争对手,而是其国内不同的利益集团。这导致传统的国际关系理论,从假设到概念和推理层面,都已经无法解释和预测今天的世界,而权力小博弈理论可以为认识多元复杂互动博弈时代的国际关系提供一个新的解释框架。     

A more powerful unconditional exact test of homogeneity for 2 × c contingency table analysis

The classical unconditional exact p-value test can be used to compare two multinomial distributions with small samples. This general hypothesis requires parameter estimation under the null which makes the test severely conservative. Similar property has been observed for Fisher's exact test with Barnard and Boschloo providing distinct adjustments that produce more powerful testing approaches. In this study, we develop a novel adjustment for the conservativeness of the unconditional multinomial exact p-value test that produces nominal type I error rate and increased power in comparison to all alternative approaches. We used a large simulation study to empirically estimate the 5th percentiles of the distributions of the p-values of the exact test over a range of scenarios and implemented a regression model to predict the values for two-sample multinomial settings. Our results show that the new test is uniformly more powerful than Fisher's, Barnard's, and Boschloo's tests with gains in power as large as several hundred percent in certain scenarios. Lastly, we provide a real-life data example where the unadjusted unconditional exact test wrongly fails to reject the null hypothesis and the corrected unconditional exact test rejects the null appropriately.     

中日史前拔牙年龄和次数比较研究

探讨史前拔牙个体的年龄和次数,对了解史前社会生活和社会意识、宗教信仰具有重要意义。认为中国和日本新石器时代的原生拔牙应该是青春期或成年期拔牙。中国新石器时代只存在一次拔牙现象,而日本新石器时代存在多次拔牙现象。这说明虽然同处新石器时代,但社会结构和社会意识有所不同。     

Supply chain agility as an acclimatisation process to environmental uncertainty and organisational vulnerabilities: insights from British SMEs

Abstract

Even though supply chain agility (SCA) has been considered an essential concept in supply chain management (SCM) research, the way it is experienced and manifested, especially by small and medium-sized enterprises (SMEs), has received much less attention. Our purpose is to focus on SME organisational vulnerabilities in the context of increased environmental uncertainty, and explore how SCA is developed and applied by SMEs amid their vulnerabilities. By relying on insights from comparative case studies of three British SMEs, we examine SME SCA as an acclimatisation process and delve into SMEs’ experiences of facing environmental uncertainty while developing and applying SCA. Our findings highlight that organisational attitudes underlie how SMEs perceive environmental uncertainty, tackle organisational vulnerabilities and develop SCA as an acclimatisation process. Our findings also reveal that resource constraints, supply chain relationships, interorganisational power dynamics, and access to information play important roles in developing SCA.