In the past Michael C. Ashton has collaborated on articles with Sampo V. Paunonen and Beth A. Visser. One of their most recent publications is Chapter 1 - Basic Concepts in Psychological Measurement. Which was published in journal .

More information about Michael C. Ashton research including statistics on their citations can be found on their Copernicus Academic profile page.

Michael C. Ashton's Articles: (16)

Chapter 1 - Basic Concepts in Psychological Measurement

AbstractIn this chapter, we will introduce some basic concepts that allow us to describe psychological measurements. By using these concepts, we will have some quick and simple ways of understanding the results of personality research. For example, if a researcher reports that women have a higher level than do men of some personality characteristic, you would probably want to know how much higher. Or, if a researcher reports that a given personality characteristic is related to enjoyment of a particular kind of music, you would probably want to know how much they are related.Also in this chapter, we will consider the basic ways of evaluating whether or not our measurements are accurate. Whenever we try to measure a psychological characteristic, we need to make sure (a) that we really have measured some meaningful characteristic, and (b) that this characteristic really is the same one that we are trying to measure. Measuring psychological characteristics accurately can be tricky, so it is important to have some ways of expressing how well we have measured those characteristics.And finally, we will also explore in this chapter some of the methods that psychologists use when measuring personality and related characteristics. As you will see later in this chapter, there exists a variety of methods, each of which has its advantages and disadvantages.

Chapter 11 - Vocational Interests

AbstractIn this chapter, we will begin by discussing several issues in the measurement of vocational interests. We will then examine the factor structure of vocational interests, their relations with personality characteristics, and their validity in predicting important job-related criteria. Finally, we will also address such issues as the stability, heritability, biological bases, and evolutionary function of vocational interests.

Chapter 12 - Religion and Politics

AbstractIn this chapter we will consider religion and politics—two topics that you are not supposed to discuss in polite company. These topics are the source of much passion and conflict in people’s lives, but they are also of great interest to psychologists. For the personality psychologist, several major questions come to mind. What are the main ways in which people differ in their religious beliefs and political attitudes? How are those beliefs and attitudes related to personality characteristics? Why do people differ so sharply in their religious and political orientations?

Chapter 13 - Sexuality

AbstractSex, in case you did not notice, is an important part of the human condition. And just as people differ in their personality characteristics—that is, in their general patterns of behavior, thought, and feeling—so too do they differ in various aspects of their sexuality—that is, in their sexual behaviors, attitudes, and preferences. In this chapter, we will begin by identifying some important aspects of sexuality, and examining their relations with personality. We will then examine several important issues concerning the nature of these sexuality dimensions, including their biological bases, their genetic and environmental origins, and their evolutionary history.

Chapter 2 - Personality Traits and the Inventories That Measure Them

AbstractIn this chapter, we discuss the definition of the term “personality trait,” as well as the evidence that personality traits do in fact exist. We then describe the workings of structured personality inventories, which are used in the measurement of personality traits by self-report or observer report. Finally, we discuss the evidence of the validity of self-reports and observer reports on personality inventory scales.

Chapter 7 - The Evolutionary Function of Personality

AbstractLike the human body, human behavior has been influenced by the process of evolution by natural selection. In this chapter, we will begin with a brief summary of how evolution works and then turn to the question of how personality variation has evolved. In doing so, we will consider the ways by which evolution can act to preserve the differences among people in personality, and we will consider the advantages and disadvantages—from an evolutionary standpoint—that are associated with high and low levels of each personality dimension.

Chapter 8 - Personality Disorders

AbstractIn previous chapters, we considered personality variation as if all levels of all personality characteristics were equally adaptive. From an evolutionary perspective, this is probably almost accurate: The fact that higher and lower levels of a given characteristic have persisted for so long suggests that they might be equally successful in promoting survival and reproduction.But in another important sense, the different levels of personality characteristics are far from being equally adaptive. If we consider the influence of an individual's personality on his or her own well-being—or on the well-being of persons who interact with that individual—then some personalities clearly seem better than others, and some personalities seem downright harmful. This is certainly the view held by people who work in mental health settings, such as psychiatrists and clinical psychologists, who believe that extreme levels of some personality characteristics are maladaptive enough to result in personality disorders. In this chapter, we will describe in some detail the meaning of a personality disorder as currently understood by psychiatrists and clinical psychologists.

The HEXACO model of personality structure and indigenous lexical personality dimensions in Italian, Dutch, and English☆

AbstractWe correlated the scales of the HEXACO Personality Inventory (HEXACO-PI) with adjective scale markers of personality factors previously obtained in indigenous lexical studies of personality structure in the Italian, Dutch, and English languages. Self-ratings were obtained from samples of 327 Italian, 161 Dutch, and 214 English-speaking Canadian participants. Results showed that each of the six HEXACO variables—including Honesty–Humility—correlated strongly with its hypothesized six-factor adjective scale counterpart in all three languages. In each case, convergent correlations were substantially stronger than discriminant correlations. Because the HEXACO model was developed without prior knowledge of the indigenous Dutch and English lexical factors, the results suggest that the HEXACO model of personality structure can be extended to the personality lexicons of those languages.

The prediction of Honesty–Humility-related criteria by the HEXACO and Five-Factor Models of personality

AbstractWe examined two questions involving the relative validity of the HEXACO and Five-Factor Models of personality structure. First, would the HEXACO model outpredict the Five-Factor Model (FFM) with regard to several diverse criteria that are conceptually relevant to the Honesty–Humility dimension of personality? If so, would the addition of a proxy Honesty–Humility scale—as computed from relevant facets of the FFM Agreeableness domain—allow the FFM to achieve predictive validities matching those of the HEXACO model? Results from self- and observer ratings in three samples (each N > 200) indicated that the HEXACO model showed considerable predictive validity advantages over the FFM. When a measure of Honesty–Humility derived from the FFM was added to the original five domains of that model, the predictive validity reached that of the HEXACO model for some criteria, but remained substantially below for others.

Brief ReportStatus-driven risk taking and the major dimensions of personality

AbstractDemographic differences in rates of mortality, violence, and accidents are frequently attributed to underlying differences in a personality disposition of competitive risk seeking. Here we describe a new Status-Driven Risk Taking (SDRT) scale that assesses this construct, and we examine its relations with the major dimensions of personality. We found that self-reports of SDRT were substantially correlated with observer reports from close acquaintances, and that men averaged about two-thirds of a standard deviation higher than did women. Within the space of the HEXACO personality factors, SDRT represented, as hypothesized, a blend of low Honesty–Humility and low Emotionality; relations with the Five-Factor Model were weaker.

Brief ReportOn the prediction of academic performance with personality traits: A replication study

Highlights•This is a replication of a 2001 JRP study by Paunonen and Ashton.•We compared personality traits against personality factors in predicting GPA.•Traits of achievement motivation and intellectual curiosity predicted grades.•Personality factors of Conscientiousness and Openness showed weaker results.•It was trait-specific variance in the lower-level traits that added to prediction.

“Minimally biased” g-loadings of crystallized and non-crystallized abilities☆

AbstractGignac [Gignac, G. E. (2006). Evaluating subtest ‘g’ saturation levels via the single trait-correlated uniqueness (STCU) SEM approach: Evidence in favor of crystallized subtests as the best indicators of ‘g’. Intelligence, 34, 29–46.] used a single-trait correlated uniqueness (STCU) CFA approach to calculate “minimally biased” g-loadings of the subtests of Wechsler-derived intelligence batteries. On the basis of results showing that g-loadings were higher for crystallized than for non-crystallized abilities, Gignac concluded “in favor of crystallized subtests as the best indicators of ‘g’”. In this article, we show that this conclusion is incorrect. First, we demonstrate using simulated data that STCU models having very good fit to the data of small variable sets can nevertheless calculate subtest g-loadings that are substantially biased. Second, we show that analyses of large and diverse variable sets do not reveal crystallized subtests to have the highest g-loadings.

g and the measurement of Multiple Intelligences: A response to Gardner

AbstractGardner [Gardner, H. (2006-this issue). On failing to grasp the core of MI theory: A response to Visser et al. Intelligence] criticized some aspects of our empirical examination [Visser, B. A., Ashton, M. C., & Vernon, P. A. (2006-this issue). Beyond g: Putting multiple intelligences theory to the test. Intelligence] of his “Theory of Multiple Intelligences”. Specifically, Gardner questioned the construct validity of g, and suggested that the measures we used to test his theory were contaminated with verbal and logical demands. In this reply, we explain that the construct validity of g is well established, pointing out (a) that g is expressed in a wide variety of tasks (not all of which are “school-like” tasks), (b) that g predicts many important criterion variables (not only academic achievement), and (c) that g has a well-established biological basis. With regard to the measures used in our study, we point out that the verbal content of those tasks is unlikely to contribute to individual differences in task performance, and that the logical content of those tasks is consistent with Gardner's description of his intelligence domains.

Higher-order g versus blended variable models of mental ability: Comment on Hampshire, Highfield, Parkin, and Owen (2012)☆

Highlights•We test the “task mixing” model of intelligence (Hampshire et al., 2012).•CFA models support a higher-order g model over the task mixing (or blended variable) model.•A well-fitting task mixing model would require every task to load on several independent factors.•We note the implausibility of such a model with reference to Thurstone’s early work.

Orthogonal factors of mental ability? A response to Hampshire et al.

Highlights•We respond to the main points raised by Hampshire et al. (this issue).•Orthogonality of individual differences in brain network capacities cannot be assumed.•Factor analyses of ability data favor g-based models over task-mixing (blended variable) models.

Hogan's framework for the study of behavior as applied to personality psychology

Highlights•Hogan's framework for the study of behavior is reviewed.•The framework can also be applied to the study of personality variation.•Research findings on human and animal personality are summarized.

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