The Use of Exploratory Factor Analysis and Principal Components Analysis in Communication Research

Exploratory factor analysis is a popular statistical technique used in communication research. Although exploratory factor analysis (EFA) and principal components analysis (PCA) are different techniques, PCA is often employed incorrectly to reveal latent constructs (i.e., factors) of observed variables, which is the purpose of EFA. PCA is more appropriate for reducing measured variables into a smaller set of variables (i.e., components) by keeping as much variance as possible out of the total variance in the measured variables. Furthermore, the popular use of varimax rotation raises some concerns about the relationships among the factors that researchers claim to discover. This paper discusses the distinct purposes of PCA and EFA, using two data sets as examples to highlight the differences in results between these procedures, and also reviews the use of each technique in three major communication journals: Communication Monographs, Human Communication Research, and Communication Research.     

Factor analysis and scale revision

This article reviews methodological issues that arise in the application of exploratory factor analysis (EFA) to scale revision and refinement. The authors begin by discussing how the appropriate use of EFA in scale revision is influenced by both the hierarchical nature of psychological constructs and the motivations underlying the revision. Then they specifically address (a) important issues that arise prior to data collection (e.g., selecting an appropriate sample), (b) technical aspects of factor analysis (e.g., determining the number of factors to retain), and (c) procedures used to evaluate the outcome of the scale revision (e.g., determining whether the new measure functions equivalently for different populations).     

A general rotation criterion and its use in orthogonal rotation

Measures of test parsimony and factor parsimony are defined. Minimizing their weighted sum produces a general rotation criterion for either oblique or orthogonal rotation. The quartimax, varimax and equamax criteria are special cases of the expression. Two new criteria are developed. One of these, the parsimax criterion, apparently gives excellent results. It is argued that one of the most important factors bearing on the choice of a rotation criterion for a particular problem is the amount of information available on the number of factors that should be rotated. This research was supported by the National Research Council of Canada research grant 291-13 to Dr. G. A. Ferguson.     

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.     

Adolescent coping scales: a critical psychometric review

Individual coping is identified as an important factor in relation to health and well-being. Although several coping scales have been developed, key terms of coping such as nature and a number of primary and secondary factors (dimensions) are obscure. Coping scales, such as those that have been developed through exploratory factor analysis (EFA), have been criticized for poor psychometric properties, yet the critique so far does not evaluate development of the scales against best test-theoretical practice. The present study reviews six adolescent coping scales against ten detailed psychometric criteria in relation to statistical choices throughout the process of scale development. All six scales measured poorly on several criteria. Best practice had not been followed throughout their development and they suffered serious psychometric limitations. These findings indicate that there still is empirical research to be pursued in search of latent constructs and possible dimensions of coping through the implementation of EFA.     

Enhancing Interpretability in Factor Analysis by Means of Mathematical Optimization

Abstract

Exploratory Factor Analysis (EFA) is a widely used statistical technique to discover the structure of latent unobserved variables, called factors, from a set of observed variables. EFA exploits the property of rotation invariance of the factor model to enhance factors’ interpretability by building a sparse loading matrix. In this paper, we propose an optimization-based procedure to give meaning to the factors arising in EFA by means of an additional set of variables, called explanatory variables, which may include in particular the set of observed variables. A goodness-of-fit criterion is introduced which quantifies the quality of the interpretation given this way. Our methodology also exploits the rotational invariance of EFA to obtain the best orthogonal rotation of the factors, in terms of the goodness-of-fit, but making them match to some of the explanatory variables, thus going beyond traditional rotation methods. Therefore, our approach allows the analyst to interpret the factors not only in terms of the observed variables, but in terms of a broader set of variables. Our experimental results demonstrate how our approach enhances interpretability in EFA, first in an empirical dataset, concerning volumes of reservoirs in California, and second in a synthetic data example.     

The Phantom Decoy Effect in Perceptual Decision Making

A phantom decoy is an alternative that is superior to another “target” option but is unavailable at the time of choice. In value‐based decisions involving phantom decoys (e.g., consumer choices), individuals often show increased preference for the similar, inferior target option over a non‐dominated competitor alternative. Unlike value‐based decisions that are driven by subjective goals, perceptual decisions typically have an outside criterion that defines the goal of the task (e.g., target is present or absent). Despite their obvious differences, past research has documented a number of commonalities between both types of decisions. In a set of three experiments, we examine the influence of phantom options on simple perceptual decisions and point out a critical difference between perceptual and value‐based decisions. Our results show that in perceptual choice, participants prefer competitor options to target options, the opposite of the pattern typically found in consumer choice. We use the results of the experiments to examine the predictions of four different models of context effects including loss aversion and dynamic, preference accumulation models. We find that accumulation models provide the best explanation for our results as well as being able to generalize to other context effects. Copyright © 2015 John Wiley & Sons, Ltd.     

Psychological Perspectives on Entrepreneurship: Cognitive and Social Factors in Entrepreneurs' Success

Why are some entrepreneurs so much more successful than others in starting new companies—ones that create wealth for their societies as well as themselves? Growing evidence suggests that the answer involves the influence of both cognitive and social factors. Successful entrepreneurs appear to think differently than other persons in several respects (e.g., they are less likely to engage in counterfactual thinking but more likely to show overconfidence in their judgments). Similarly, successful entrepreneurs appear to be higher in social competence —the ability to interact effectively with others (e.g., they are better at social perception and adapting to new social situations). These results suggest that the principles and findings of psychology can be invaluable to researchers in the field of entrepreneurship, providing important insights into the factors that influence entrepreneurs' success.     

探索性因素分析——最近10年的评述

目的：(1)介绍国外心理统计学界对探索性因素分析中几个重大问题的基本观点;(2)系统地评述过去10年里(1991～2000年)我国心理学研究对这一技术的使用情况;(3)强调运用这一技术时值得注意的一些事项,以期这一技术对我国心理学研究发挥更大的作用。方法：作检索了《心理学报》和《心理科学》在1991～2000年间与探索性因素分析有关的章,对其中以探索性因素分析为主要研究方法的重点章(feature article)进行了编码,统计了频数及百分比分布。结果：我国心理学研究在积极使用探索性因素分析这一先进统计技术时还存在一些问题,主要表现在：(1)在确定因素个数时,倾向于机械地依靠桌个单一方法来作决定,(2)大量使用正交旋转,(3)过于依赖SPSS,(4)对因素分析过程中的重要信息／结果报告不够。结论：探索性因素分析在过去十年得到了广泛的应用,如能吸收国外同行的一些观点,探索性因素分析这一技术在我国心理学研究中必将获得更广泛有效的应用。     

Positive and negative implications of the causal illusion

The human cognitive system is fine-tuned to detect patterns in the environment with the aim of predicting important outcomes and, eventually, to optimize behavior. Built under the logic of the least-costly mistake, this system has evolved biases to not overlook any meaningful pattern, even if this means that some false alarms will occur, as in the case of when we detect a causal link between two events that are actually unrelated (i.e., a causal illusion). In this review, we examine the positive and negative implications of causal illusions, emphasizing emotional aspects (i.e., causal illusions are negatively associated with negative mood and depression) and practical, health-related issues (i.e., causal illusions might underlie pseudoscientific beliefs, leading to dangerous decisions). Finally, we describe several ways to obtain control over causal illusions, so that we could be able to produce them when they are beneficial and avoid them when they are harmful.     

Explaining the impact of policy information on policy-making

This article has called past studies into question as they relate to describing and explaining the impact of information on policy-making. More specifically, it attempts to empirically investigate the causality of the factors involved in the impact of information on governmental decision-making. Based on an integrated conceptual framework for when and how information helps to make policy decisions, a path model (or a covariance structure model without latent variables) is built and tested against the data in two areas of mental health policy (i.e., service provision and financing). Findings of the study demonstrate that how and when information influences governmental decision-making is directly and indirectly affected by a variety of factors and their linkages, not dominated by one set of factors (e.g., trustworthiness of information source or format of reports) defined by a single perspective (e.g., the organizational interest or the communications perspective). The most important paths in the model are those between factors related to information (e.g., the amount of information received or its use) and the impact of information on policy-making. Interestingly, these factors also play a major role in linking other variables (e.g., demographics or decision makers’ distrust of information) to the impact of information on policy-making. Furthermore, the general pattern of the findings indicates that policy areas make a difference in accounting for the impact of information on policy-making. Overall, the single most important lesson is that past perspectives are not alternative or competing tools for understanding the phenomena, and, thus, the theoretical and/or empirical task of explaining when and why information affects policy-making is equivalent to explaining why a certain set of factors is not appropriate or appropriate for a particular context and to identifying such a context.     

Appraising the Appraisal‐Tendency Framework

This article considers the consumer research implications of the Appraisal‐Tendency Framework (ATF; Han, Lerner, & Keltner, 2007). This article outlines how the ATF approach could be applied to sequential consumer choices (e.g., effects of emotional responses to stockouts on later decisions) and high‐stakes decisions (e.g., medical decisions). This article also proposes several areas in which the ATF might be extended: examining complex sequences of choices with emotional consequences, considering how incidental and integral emotions interact, characterizing how both evaluative and regulatory mechanisms may influence the effects of emotion on judgment and choice, and extending the range of positive emotions and appraisal dimensions considered.     

CHull: A generic convex-hull-based model selection method

When analyzing data, researchers are often confronted with a model selection problem (e.g., determining the number of components/factors in principal components analysis [PCA]/factor analysis or identifying the most important predictors in a regression analysis). To tackle such a problem, researchers may apply some objective procedure, like parallel analysis in PCA/factor analysis or stepwise selection methods in regression analysis. A drawback of these procedures is that they can only be applied to the model selection problem at hand. An interesting alternative is the CHull model selection procedure, which was originally developed for multiway analysis (e.g., multimode partitioning). However, the key idea behind the CHull procedure—identifying a model that optimally balances model goodness of fit/misfit and model complexity—is quite generic. Therefore, the procedure may also be used when applying many other analysis techniques. The aim of this article is twofold. First, we demonstrate the wide applicability of the CHull method by showing how it can be used to solve various model selection problems in the context of PCA, reduced K-means, best-subset regression, and partial least squares regression. Moreover, a comparison of CHull with standard model selection methods for these problems is performed. Second, we present the CHULL software, which may be downloaded from http://ppw.kuleuven.be/okp/software/CHULL/, to assist the user in applying the CHull procedure.     

有限理性的“占优启发式”和“齐当别”决策模型的作为 ——当Allais悖论杠杆撬动了期望效用理论

人们在做决策时常常要受到时间或知识的限制,有时还要受到其双重限制。关于人们是如何进行风险决策,早期有期望效用理论对其加以解释,但Allais悖论对其标准化地位提出了挑战。Simon的“有限理性”观点提出后,一些研究者开始致力于开发决策的“有限理性”模型。文章讨论并比较了无限理性的期望效用理论被Allais悖论杠杆撬动之后,有限理性的“占优启发式”和“齐当别”决策模型所能做的和所不能做的。两种模型的决策标准、计算策略以及未来研究的展望也一并作了讨论     

The Relation Between People's Connection With a Target and the Perceived Importance of Justice

We propose that actors will perceive justice as more important with respect to a target when they experience moderate versus extremely high or extremely low connection with the target. In two studies, we manipulated actors’ connection with (e.g., similarity to) a target and the target's standing on the appropriate justice criterion. Both studies yielded the predicted curvilinear relation between connectedness and the perceived relevance of justice. In Study 2, actors’ decisions were more affected by the justice criterion in the moderate versus extreme connectedness conditions. Our findings have important implications for the interplay between connection with others and moral motivations.     

Are Adewale and Ngochi more employable than Jamal and Lakeisha? The influence of nationality and ethnicity cues on employment-related evaluations of Blacks in the United States

ABSTRACT

Previous research has consistently shown that racial bias can influence employers’ perceptions and evaluations of Black individuals in hiring and promotion decisions. However, within-race differences (e.g., skin tone, Afrocentric features) can lead to variation in these decisions. In addition to phenotypical variation, ethnicity cues (e.g., perceived country of origin, name) may be important within-race factors influencing the perception and evaluations of Black job applicants. Using a resume evaluation paradigm, participants evaluated one of three resumes in which the target applicant’s name provided cues about ethnicity (either Black American, Black African, or White American). Results suggest that Black Americans may experience more discrimination in hiring and are generally perceived less positively across several employment-related domains than both White and Black African applicants. Specifically, we find that Black Americans are less likely to be selected for an interview or offered a job and are evaluated more negatively overall relative to Black Africans.     

The effects of response mode and importance on decision-making strategies: Judgment versus choice

Judgment and choice have not always been clearly distinguished, and there is little direct research on their effects on the decision process. As compared to choice, judgment is predicted to lead to more information searched, a less variable pattern of search, and a greater amount of interdimensional search. In essence, search processes that imply elimination by aspects will occur more often under choice than judgment. It is further argued that a number of variables may moderate this response mode effect. The potential moderator examined here is decision importance, which is predicted to produce analytical judgment processes prior to choice. Using an information search board, 104 subjects made decisions (choices or judgments) on candidates for residence hall advisor, under high or low decision importance. Response mode produced strong effects on all measures of the decision process. Importance had fewer effects; it affected the frequency of an intradimensional/variable search mode, but moderated the response mode effect only for amount of information searched. Given these results, several implications follow. Research which uses ajudgment response (e.g., policy capturing) should not be generalized to choice tasks. Also, requiring an explict judgment even when only the final choice matters may be a useful procedure. Further research is needed to examine the effects of response mode on additional outcomes, such as how the information is organized in memory and which alternative is actually selected.     

The Interactive Effects of Self‐Perceptions and Job Requirements on Creative Problem Solving

Over the years, researchers have focused on ways to facilitate creativity in the workplace by looking at individual factors and organizational factors that affect employee creativity (Woodman, Sawyer, & Griffin, 1993 ). In many cases, the factors that affect creativity are examined independently. In other words, it is uncommon for researchers to look at the interaction among individual and organizational factors. In this study, it is argued that to get a true understanding of how to maximize creativity in the workplace, organizational researchers must look at the interaction between organizational factors and individual factors that affect employee creativity. More specifically, the current study looked at an individual's perceptions about his or her ability to be creative (i.e., individual factor) and perceptions of requirements for creativity in the workplace (i.e., an organizational factor). The results indicated that individuals who have a high belief about their ability to be creative (an individual factor) were most creative when they also perceived requirements for creativity in the workplace (an organizational factor). Furthermore, individuals who had low perceptions of creative ability were still able to perform creatively when they had high perceptions of requirements for creativity. This suggests that, to maximize creativity, organizations should focus on both individual and organizational factors that affect employee creativity.     

A comparison of general and work-specific measures of core self-evaluations

During the past decade, considerable research attention has been given to core self-evaluations (CSEs). Although this research has found that CSE is related to several important work-related outcomes (e.g., job satisfaction, job performance), we believe that researchers’ reliance on general rather than work-specific CSE has resulted in underestimates of the importance of CSE. Based on the literature on frame-of-reference effects in personality assessment, we predict that work-related CSE will yield stronger relationships with work-related criteria than general CSE will and that work-specific CSE will be related to work-specific criteria after general CSE has been controlled. Using two independent samples, we found that when compared with general CSE, work-specific CSE generally failed to yield significantly stronger zero-order relationships with work-related criteria. However, we found several instances in which work-specific CSE predicted incremental variance in work-related criteria after the effects of general CSE were controlled.     

Examining recognition criterion rigidity during testing using a biased-feedback technique: Evidence for adaptive criterion learning

Recognition models often assume that subjects use specific evidence values (decision criteria) to adaptively parse continuous memory evidence into response categories (e.g., "old," "new"). Although explicit pretest instructions influence criterion placement, these criteria appear extremely resistant to change once testing begins. We tested criterion sensitivity to local feedback using a novel biased-feedback technique designed to tacitly encourage certain errors by indicating they are the correct choices. Experiment 1 demonstrated that fully correct feedback had little effect on criterion placement, whereas biased feedback during Experiments 2 and 3 yielded prominent, durable, and adaptive criterion shifts, with observers reporting that they were unaware of the manipulation in Experiment 3. These data suggest that recognition criteria can be easily modified during testing through a form of feedback learning that operates independently of stimulus characteristics and observers' awareness of the nature of the manipulation. This mechanism may be fundamentally different from criterion shifts following explicit instructions and warnings, or shifts linked to manipulations of stimulus characteristics combined with feedback highlighting those manipulations.