A Comparison of Modern and Popular Approaches to Calculating Reliability for Dichotomously Scored Items

Recent work on reliability coefficients has largely focused on continuous items, including critiques of Cronbach’s alpha. Although two new model-based reliability coefficients have been proposed for dichotomous items (Dimitrov, 2003a,b; Green & Yang, 2009a), these approaches have yet to be compared to each other or other popular estimates of reliability such as omega, alpha, and the greatest lower bound. We seek computational improvements to one of these model-based reliability coefficients and, in addition, conduct initial Monte Carlo simulations to compare coefficients using dichotomous data. Our results suggest that such improvements to the model-based approach are warranted, while model-based approaches were generally superior.     

Item format and the structure of the buss-durkee hostility inventory

The Buss-Durkee Hostility Inventory is a widely employed multidimensional measure of aggression. Two studies, each involving the administration of both two-choice and seven-choice response format versions of the instrument, were conducted to determine if (1) the theoretical scales could be reproduced empirically, (2) the change in response format either changes or improves the structure, and (3) the structure of either response format replicates across administrations. The two-choice version provided some support for the present theoretical scoring but was not very stable across administrations. The seven-choice version resulted in a structure that was different from both the two-choice structure and theoretical scoring but was more stable across administrations.     

Exploratory factor analysis in transportation research: Current practices and recommendations

Exploratory factor analysis (EFA) is a widely used statistical method in traffic and transportation research, particularly for the development and validation of measurement instruments. This article critically examines current practices in conducting and reporting EFA in published transportation studies. One hundred and eighty papers published between 2016 and 2018 were examined, of which eighty-two were included in the present study after applying eligibility criteria. The review suggests that the quality of EFA reported in the field is routinely poor: (a) researchers fail to provide sufficient information to be able to adequately assess the appropriateness and quality of both the input data and the reported output; and (b) the decisions underlying the choices of EFA methods are not justified and rely mostly on procedures advised against, particularly the Little-Jiffy approach. In summary, a significant gap between current practice and experts' recommendations exists. We provide some guidelines that may help in conducting, reporting and reviewing EFA in transportation research.     

The anatomy of an insult: Popular derogatory terms connote important individual differences in Agreeableness/Antagonism

In the current series of studies, we investigate the psychosocial connotations of common insults. In Studies 1 and 2, we investigated the most frequently used insults to denigrate men and women (asshole, dick, bitch), and generated trait profiles that can be considered prototypical of each insult. In Studies 3 and 4, we examined how these insults are relevant to other key indicators of interpersonal functioning, including aggression, social information processing, personality disorders, and substance use. We also gathered thin-slice and informant reports. Each of the insults was associated with trait Antagonism, as well as other behaviors that comprise Antagonism’s nomological network (e.g., bullying, psychopathy, etc.). Results are discussed in terms of the importance of everyday language to psychological research.     

A conceptual dismantling of the Five Factor Form: Lexical support for the bipolarity of maladaptive personality structure

The Five Factor Form (FFF) assesses adaptive and maladaptive variants for both poles of the five-factor model (FFM), consistent with the hypothesis that there are indeed maladaptive variants for all 10 poles of the FFM. The current study dismantled the 30 FFF items. It was hypothesized that for each FFF item, the two maladaptive and adaptive components occupying the same side would be rated as similar in meaning, whereas components occupying opposite sides would be dissimilar (opposite) in meaning. The results supported the FFF scoring for four domains with mixed support for openness. The findings support not only the validity of the FFF but as well the perspective that there are maladaptive variants of all ten poles of the FFM.     

乳腺微乳头状癌的临床病理特征分析

回顾性分析乳腺浸润性微乳头状癌(IMPC)的临床病理特征.选取河北医科大学第四医院乳腺中心手术切除并经病理证实的女性原发性乳腺癌共3 383例,筛选出符合IMPC为实验组,同期乳腺浸润性导管癌(IDC)为对照组.结果显示,本组IMPC 167例,占同期乳腺癌4.94％,年龄29岁～80岁,中位年龄54岁.淋巴结转移者共135例,占80.8％,淋巴结转移数目≥4个共105例,占62.9％,HER2阳性率58.7％,与IDC组相比差异均有统计学意义(P＜0.05).IMPC为一种少见类型的浸润性乳腺癌,具有淋巴管侵袭性强、淋巴结转移率高的生物学行为.应与其他类型肿瘤进行鉴别,明确诊断.     

An estimate of the covariance between variables which are not jointly observed

Situations sometimes arise in which variables collected in a study are not jointly observed. This typically occurs because of study design. An example is an equating study where distinct groups of subjects are administered different sections of a test. In the normal maximum likelihood function to estimate the covariance matrix among all variables, elements corresponding to those that are not jointly observed are unidentified. If a factor analysis model holds for the variables, however, then all sections of the matrix can be accurately estimated, using the fact that the covariances are a function of the factor loadings. Standard errors of the estimated covariances can be obtained by the delta method. In addition to estimating the covariance matrix in this design, the method can be applied to other problems such as regression factor analysis. Two examples are presented to illustrate the method. This research was partially supported by NIMH grant MH5-4576     

互联网的使用对中老年人生活幸福感的影响

采用2018年中国健康与养老追踪调查数据(CHARLS),运用主成分回归和结构方程模型,探究互联网的使用对中国中老年人生活幸福感的影响。主成分回归的结果显示中老年人互联网使用程度、家庭情况以及其身体状况都会对其生活幸福感产生积极的影响,结构方程模型的结果显示中老年人家庭情况会直接或通过影响其互联网使用程度间接的对其身体状况产生积极的影响,进而提升其生活幸福感。