Principles and Practice of Structural Equation Modeling (2nd ed.)

Framework Convention on Climate Change

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Applied Missing Data Analysis

Survey questions asking about taboo topics such as sexual activities, illegal behaviour such as social fraud, or unsocial attitudes such as racism, often generate inaccurate survey estimates which are distorted by social desirability bias. Due to self-presentation concerns, survey respondents underreport socially undesirable activities and overreport socially desirable ones. This article reviews theoretical explanations of socially motivated misreporting in sensitive surveys and provides an overview of the empirical evidence on the effectiveness of specific survey methods designed to encourage the respondents to answer more honestly. Besides psychological aspects, like a stable need for social approval and the preference for not getting involved into embarrassing social interactions, aspects of the survey design, the interviewer’s characteristics and the survey situation determine the occurrence and the degree of social desirability bias. The review shows that survey designers could generate more valid data by selecting appropriate data collection strategies that reduce respondents’ discomfort when answering to a sensitive question.

Determinants of social desirability bias in sensitive surveys: a literature review

在翟象俊主编的《大学英语》第2册第5单元中，有这样一个句子：“As a boy and then as an adult, I never lost my wonder at the personality that was Einstein.”教参中指出“the personality that was Einstein”应理解为“the personality which was the most striking characteristic of Einstein”，该句译为“作为一个孩子，到后来作为一个成人，我一直对爱因斯坦的个性惊叹不已”。很明显，在这里译者把“personality”理解为“个性，人格”，但本人认为应译为“人物，名人”更妥。“personality”可作“个性，人格”讲，但它还有另外一个重要意思。在陆谷孙主编的《英汉大词典》（1993年版）中，“personality”第3条释义为：“个人，人物，名人”：“appoint a personality to lead a campaign，派一个人去领导一场运动”。“a personality in the news，新闻人物”。在...

此处“personality”译法探析

Visual aesthetics has been shown to critically affect a variety of constructs such as perceived usability, satisfaction, and pleasure. Given the importance of visual aesthetics in human-computer interaction, it is vital that it is adequately assessed. The present research aimed at providing a precise operational definition and to develop a new measure of perceived visual aesthetics of websites. Construction of the Visual Aesthetics of Website Inventory (VisAWI) was based on a comprehensive and broad definition of visual aesthetics so that the resulting instrument would completely describe the domain of interest. Four interrelated facets of perceived visual aesthetics of websites were identified and validated in a series of seven studies. Simplicity and Diversity have repeatedly been treated as formal parameters of aesthetic objects throughout the history of empirical aesthetics, Colors are a critical property of aesthetic objects, and Craftsmanship addresses the skillful and coherent integration of the relevant design dimensions. These four facets jointly represent perceived visual aesthetics, but are still distinguishable from each other and carry unique meaning. The subscales contained in the VisAWI demonstrate good internal consistencies. Evidence for the convergent, divergent, discriminative, and concurrent validity of the VisAWI is provided. Overall, the present research suggests that the VisAWI appears to be a sound measure of visual aesthetics of websites comprising facets of both practical and theoretical interest.

/pdf/facets-of-visual-aesthetics-28tdyzse2v.pdf

Facets of visual aesthetics

Multinomial processing tree (MPT) models are a family of stochastic models for psychology and related sciences that can be used to model observed categorical frequencies as a function of a sequence of latent states For the analysis of such models, the present article presents a platform-independent computer program called multiTree, which simplifies the creation and the analysis of MPT models This makes them more convenient to implement and analyze Also, multiTree offers advanced modeling features It provides estimates of the parameters and their variability, goodness-of-fit statistics, hypothesis testing, checks for identifiability, parametric and nonparametric bootstrapping, and power analyses In this article, the algorithms underlying multiTree are given, and a user guide is provided The multiTree program can be downloaded from http://psycho3uni-mannheimde/multitree

https://link.springer.com/content/pdf/10.3758/BRM.42.1.42.pdf

multiTree: A computer program for the analysis of multinomial processing tree models.

Multinomial processing tree (MPT) models have become popular in cognitive psychology in the past two decades. In contrast to general-purpose data analysis techniques, such as log-linear models or other generalized linear models, MPT models are substantively motivated stochastic models for categorical data. They are best described as tools (a) for measuring the cognitive processes that underlie human behavior in various tasks and (b) for testing the psychological assumptions on which these models are based. The present article provides a review of MPT models and their applications in psychology, focusing on recent trends and developments in the past 10 years. Our review is nontechnical in nature and primarily aims at informing readers about the scope and utility of MPT models in different branches of cognitive psychology. In a now classical article, Riefer and Batchelder (1988) proposed a class of substantively motivated stochastic mod- els for categorical behavioral data which was relatively well known in statistical genetics at the time (e.g., Elandt- Johnson, 1971), but had received little attention in psycho- logical research up to the 1980s. These models are now known as multinomial processing tree (MPT) models. About 10 years later, Batchelder and Riefer (1999) already identified no less than 30 published MPT models in the psychological literature, most of which were applied to different agendas in cognitive research. The present article provides an update of Batchelder and Riefer's review and focuses on models and their applications published in the past 10 years. Our review includes 70 MPT models and model variants from more than 20 research areas. In the first section, we will present a brief conceptual outline of MPT models using a simple example to illustrate the basics and main advantages of this approach. Technical details will be omitted almost entirely because they have been described elsewhere (e.g., Batchelder & Riefer, 1999; Hu & Batchelder, 1994). The second section sum- marizes MPT models and their applications in different branches of cognitive psychology, with a special focus on models for various memory paradigms. In the third sec- tion, psychological applications of MPT models outside the realm of cognitive psychology will be briefly summarized. The fourth section describes recent developments, general- izations, and innovations in the statistical methodology of MPT models that might be useful for those interested in applying such models. The fifth and final section of our review provides a sketch of computer programs that are currently available for statistical analyses in the MPT framework, along with a summary of the main advantages of each program.

https://psycnet.apa.org/journals/zfp/217/3/108.pdf

Multinomial processing tree models: A review of the literature.

Many negatively connoted personality traits (often termed "dark traits") have been introduced to account for ethically, morally, and socially questionable behavior. Herein, we provide a unifying, comprehensive theoretical framework for understanding dark personality in terms of a general dispositional tendency of which dark traits arise as specific manifestations. That is, we theoretically specify the common core of dark traits, which we call the Dark Factor of Personality (D). The fluid concept of D captures individual differences in the tendency to maximize one's individual utility-disregarding, accepting, or malevolently provoking disutility for others-accompanied by beliefs that serve as justifications. To critically test D, we unify and extend prior work methodologically and empirically by considering a large number of dark traits simultaneously, using statistical approaches tailored to capture both the common core and the unique content of dark traits, and testing the predictive validity of both D and the unique content of dark traits with respect to diverse criteria including fully consequential and incentive-compatible behavior. In a series of four studies (N > 2,500), we provide evidence in support of the theoretical conceptualization of D, show that dark traits can be understood as specific manifestations of D, demonstrate that D predicts a multitude of criteria in the realm of ethically, morally, and socially questionable behavior, and illustrate that D does not depend on any particular indicator variable included. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

/pdf/the-dark-core-of-personality-2sdnwim5mz.pdf

The dark core of personality.

The size of a model has been shown to critically affect the goodness of approximation of the model fit statistic T to the asymptotic chi-square distribution in finite samples. It is not clear, however, whether this “model size effect” is a function of the number of manifest variables, the number of free parameters, or both. It is demonstrated by means of 2 Monte Carlo computer simulation studies that neither the number of free parameters to be estimated nor the model degrees of freedom systematically affect the T statistic when the number of manifest variables is held constant. Increasing the number of manifest variables, however, is associated with a severe bias. These results imply that model fit drastically depends on the size of the covariance matrix and that future studies involving goodness-of-fit statistics should always consider the number of manifest variables, but can safely neglect the influence of particular model specifications.

Morten Moshagen

Papers

Facets of visual aesthetics

multiTree: A computer program for the analysis of multinomial processing tree models.

Multinomial processing tree models: A review of the literature.

The dark core of personality.

The Model Size Effect in SEM: Inflated Goodness-of-Fit Statistics Are due to the Size of the Covariance Matrix.