The effect of additional variables on factor indeterminacy in models with a single common factor

Determinate solutions for the indeterminate common factor ofp variables satisfying the single common factor model are not unique. Therefore an infinite sequence of additional variables that conform jointly with the originalp variables to the original single common factor model does not determine a unique solution for the indeterminate factor of thep variables (although the solution is unique for the factor of the infinite sequence). Other infinite sequences may be found to determine different solutions for the factor of the originalp variables. The paper discusses a number of theorems about the effects of additional variables on factor indeterminacy in a model with a single common factor and draws conclusions from them for factor theory in general.     

Latent roots of random data correlation matrices with squared multiple correlations on the diagonal: A monte carlo study

In order to make the parallel analysis criterion for determining the number of factors easy to use, regression equations for predicting the logarithms of the latent roots of random correlation matrices, with squared multiple correlations on the diagonal, are presented. The correlation matrices were derived from distributions of normally distributed random numbers. The independent variables are log (N–1) and log {[n(n–1)/2]–[(i–1)n]}, whereN is the number of observations;n, the number of variables; andi, the ordinal position of the eigenvalue. The results were excellent, with multiple correlation coefficients ranging from .9948 to .9992.This research was supported by the Office of Naval Research under Contract N00014-67-A-0305-0012, Lloyd G. Humphreys, principal investigator, and by the Department of Computer Science of which Richard G. Montanelli, Jr., is a member.     

Comments on “the measurement of factorial indeterminacy”

Guttman's index of indeterminacy (2² – 1) measures the potential amount of uncertainty in picking the right alternative interpretation for a factor. When alternative solutions for a factor are equally likely to be correct, then the squared multiple correlation ² for predicting the factor from the observed variables is the average correlation _AB between independently selected alternative solutionsA andB, while var ( _AB )=(1 – ²)²/s, wheres is the dimensionality of the space in which unpredicted components of alternative solutions are to be found. When alternative solutions for the factor are not equally likely to be chosen, ² is the lower bound for E( _AB ); however, E( _AB ) need not be a modal value in the distribution of _AB . Guttman's index and E( _AB ) measure different aspects of the same indeterminacy problem.     

2004至2016年中国大学生身体自尊的变迁:一项横断历史研究

大学生身体自尊是如何随年代变化的呢？研究对2004年至2016年107篇使用身体自尊量表的研究进行了横断历史研究,涉及大学生30738名。结果显示：（1）我国大学生身体自我价值感、运动能力和身体素质与年代有着显著正相关关系;（2）男女大学生身体自尊水平都有了一定提升;（3）男生在身体自尊各个因子的得分高于女生0.2~0.3个标准差,显示出了大学生在身体自尊水平上的性别差异;（4）从大学生整个群体来看,经济因素、高等教育因素与大学生身体自尊具有显著相关,而从不同性别群体来看,经济因素与人口压力对于男大学生的身体自尊影响更为明显。     

Children’s street crossing performance when auditory information about traffic is lacking

PurposeThe current study examined the impact on children’s street crossing behaviors of not having auditory-based information about traffic when crossing streets.MethodUsing a fully-immersive virtual reality system, numerous indices of children’s street crossing behaviors were measured both when they had auditory-based information about traffic and when this was lacking.ResultsThe lack of traffic sounds did not influence the inter-vehicle gap size that children crossed into but it did result in slower initiations and, ultimately, more high-risk outcomes (close calls and hits).ConclusionTraffic sounds significantly contribute to enhance children’s safety when crossing streets. Cars with reduced sounds (e.g., electric) and anything that interferes with children accessing auditory-based traffic information (e.g., wearing headphones) could increase their risk of pedestrian injury.     

Evaluating pedestrian interaction preferences with a game theoretic autonomous vehicle in virtual reality

Localisation and navigation of autonomous vehicles (AVs) in static environments are now solved problems, but how to control their interactions with other road users in mixed traffic environments, especially with pedestrians, remains an open question. Recent work has begun to apply game theory to model and control AV-pedestrian interactions as they compete for space on the road whilst trying to avoid collisions. But this game theory model has been developed only in unrealistic lab environments. To improve their realism, this study empirically examines pedestrian behaviour during road crossing in the presence of approaching autonomous vehicles in more realistic virtual reality (VR) environments. The autonomous vehicles are controlled using game theory, and this study seeks to find the best parameters for these controls to produce comfortable interactions for the pedestrians. In a first experiment, participants’ trajectories reveal a more cautious crossing behaviour in VR than in previous laboratory experiments. In two further experiments, a gradient descent approach is used to investigate participants’ preference for AV driving style. The results show that the majority of participants were not expecting the AV to stop in some scenarios, and there was no change in their crossing behaviour in two environments and with different car models suggestive of car and last-mile style vehicles. These results provide some initial estimates for game theoretic parameters needed by future AVs in their pedestrian interactions and more generally show how such parameters can be inferred from virtual reality experiments.     

Safety of micro-mobility: Riders’ psychological factors and risky behaviors of cargo TTWs in China

Cargo two- or three-wheeled vehicles (TTWs), as a new form of micro-mobility, have become a popular mode of urban cargo transportation in China. Cargo TTW riders’ psychological factors and risky behaviors lead to a number of accidents. A questionnaire is designed by comprehensively considering these factors and behaviors of cargo TTW riders that includes eleven risk factors to quantitatively analyze the risky behaviors based on structural equation modeling (SEM). One thousand three hundred nineteen participants reported using cargo TTWs on a questionnaire distributed across the country. The characteristics of riding behavior data are analyzed to verify the three-layer risk theoretical framework of “Psychological factors (Personality traits/specific factors) - Psychological acceptability of risks (confidence/perception/attitude) - Risky behaviors”. The results show that anger has a strong direct effect on riding violations, while normlessness and altruism have a direct effect on riding errors. Workload has a weak but direct effect on risky behaviors, and riding feedback has a weak and mixed effect. In addition, high-risk groups are identified by analysis of variance (ANOVA) with rider population attributes. These quantitative analyses can help guide safety countermeasures to mitigate accidents involving cargo TTWs.     

空间交互研究新视角：多重社会因素的影响

空间交互是人类生存和社交的重要内容, 主要包括语言交流和视角采择两大范畴。对空间交互策略和效率的影响因素的研究, 传统上集中于空间因素, 近年来逐渐开始关注各种社会因素, 包括个体自身的社会认知特质、交互对象的社会属性和空间环境中的社会线索, 并从不同角度提出了理论解释。未来研究应关注社会认知与空间认知的跨领域融合, 考察更加多元的空间交互对象, 最终建立一个整合空间和社会因素的空间交互理论框架。     

Personality pathology severity,cluster type and specific therapeutic interventions in outpatient psychotherapy

We explored the relationship between severity of personality pathology, cluster type and therapeutic interventions (psychodynamic–interpersonal [PI] and cognitive–behavioural [CB]) in 76 outpatients across two early sessions (3rd and 9th) of psychodynamic psychotherapy, while accounting for patients' baseline global symptom severity. Pretreatment personality pathology severity was assessed using the Personality Disorder Index (PDI), where DSM‐IV Axis II PD was assigned a value of 2, subclinical traits and features were assigned a 1 and absence of Axis II psychopathology was assigned a 0. Interrater reliability of personality pathology severity was excellent (ICC [1, 1]: 0.85). Interrater agreement for Cluster A (κ = 0.75), Cluster B (κ = 0.92) and Cluster C (κ = 0.70) was high. Interventions were coded with Comparative Psychotherapy Process Scale (CPPS) from videotapes, and reliability was excellent (CPPS‐PI = 0.86; CPPS‐CB = 0.78). Stepwise linear regressions indicated that therapists' focus on mood shift/topic avoidance (B = 0.29, p = .009) and future events (B = ?0.26, p = .020) predicted Axis II severity. Overall use of PI techniques and Cluster A personality disorder (CLA) were positively correlated (r = .312, p = .006). Stepwise binomial logistic regressions indicated that therapists' focus on uncomfortable feelings (B = 1.915, p = .008) and explaining rationale behind approach (B = 1.276, p =. 038) predicted CLA. All results remained significant when controlling for patients' baseline general symptomatology (Brief Symptom Inventory‐Global Severity Index [BSI‐GSI]), except for the relation between explaining rationale and CLA. Discussion highlights how using psychodynamic treatment model, therapists' focus on patient's in‐session affect expression and explaining rationale behind approach are highly relevant when working with CLA patients.     

解读不显著结果：基于500个实证研究的量化分析

不显著结果(如, p > 0.05)在心理学研究中十分常见, 且容易被误解为接受零假设的证据, 并可能导致分组匹配研究的错误推断或者忽视被小样本的不显著结果掩盖的真实效应。但国内目前尚无实证研究对不显著结果的普遍性及其解读进行调查。本研究调查500篇中文心理学实证研究, 统计其摘要中出现与不显著结果相关的阴性陈述的频率, 判断并统计基于阴性陈述的推断准确性, 并使用贝叶斯因子对不显著结果中包含t值的研究进行重新评估。结果表明, 36%的摘要提及不显著结果, 共包含236个阴性陈述。其中, 41%的阴性陈述对不显著结果的解读出现偏差(如, 解读为支持了零假设)。对包含t值的研究进行贝叶斯因子分析, 结果显示仅有5.1%的不显著结果可以提供强证据支持零假设(BF₀₁ > 10)。与先前对国际心理学期刊的调查结果相比(32%的摘要包含阴性陈述; 72%的阴性陈述对不显著结果的解读错误), 中文心理学期刊中报告不显著结果的比例更高, 且对不显著结果解读错误的比例更低。但国内研究者仍需进一步加强对不显著结果的认识, 推广适于评估不显著结果的统计方法。