Stéphane Vautier

Dimensionality of the Revised Life Orientation Test and the status of filler items

Dispositional optimism was originally construed as unidimensional (Scheier & Carver, 1992). However, LOT‐R data (Scheier, Carver, & Bridges, 1994) generally appeared bidimensional as a number of studies suggest a two‐correlated‐factor model representing optimism and pessimism. Attempts at corroborating one‐factor models suggest that correlated errors between positively worded items are required for an adequate account of the data. This article explains bidimensionality by the influence of social desirability (i.e., being positive is desirable). Namely, in the present study, correlated errors are interpreted as the presence of individual differences related to the tendency to present oneself in a positive manner. Moreover, response styles can be corroborated by appropriately modelling the entire covariance matrix (i.e., including fillers), by checking that fillers with positive meaning correlate with the faking‐good group factor. Students (N = 442) responded to a French adaptation of the LOT‐R. The data we...

A Longitudinal SEM Approach to STAI Data: Two Comprehensive Multitrait-Multistate Models

I investigated psychometric properties of data gathered with the State-Trait Anxiety Inventory (STAI; Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983, 1993) using structural equation modeling. Two features were integrated into the modeling: Bistability refers to the duality that is raised once the wording effect is recognized, and second-order, state-residual/trait decomposition refers to the basic bidimensionality of the data, which is revealed in a longitudinal perspective. I tested the approach on 2 samples of French adults (total N = 888) borrowed from Vautier and Jmel (2003). The models provided acceptable goodness of fit and supported the empirical need for hypothesizing 2 trait factors and 4 transient sources of true variance. I assessed the multidimensional composition of the composites using reliability analyses. I discuss theoretical consequences of the approach.

Do Balanced Scales Assess Bipolar Constructs? The Case of the STAI Scales.

Balanced scales, that is, scales based on items whose content is either negatively or positively polarized, are often used in the hope of measuring a bipolar construct. Research has shown that usually balanced scales do not yield 1-dimensional measurements. This threatens their construct validity. The authors show how to test bipolarity while accounting for method effects. This is demonstrated on a data set of state and trait anxiety measured with the State-Trait Anxiety Inventory (STAI; C. D. Spielberger, R. L. Gorsuch, R. Lushene, P. R. Vagg, & G. A. Jacobs, 1983) scales. Taking a test-retest perspective, assuming temporally stable method effects, the authors tested the bipolarity of the temporal change through suitable constraints specified in a structural equation model adapted from S. Vautier, R. Steyer, and A. Boomsma (2008). The model fit the data closely, chi(2)(13, N = 888) = 20.75, p = .07. Thus, the state and trait scales seem to measure bipolar constructs plus temporally stable method effects. Parameter estimates suggest reliable change scores for the state anxiety scale (rho = .90) and specific method effects for the state and trait scales of the STAI.

Imperfect or Perfect Dynamic Bipolarity? The Case of Antonymous Affective Judgments.

How is affective change rated with positive adjectives such as good related to change rated with negative adjectives such as bad? Two nested perfect and imperfect forms of dynamic bipolarity are defined using latent change structural equation models based on tetrads of items. Perfect bipolarity means that latent change scores correlate -1. Meaningful structural equation modeling (SEM) analyses of self-rated affect may require analyzing polychoric correlations, if self-ratings are collected using ordered categories. The models were applied to 6 4-wave datasets from Steyer and Riedl (2004). Results suggest that perfect bipolarity is generally compatible with valence self-ratings, whereas imperfect bipolarity is compatible with tension and energy self-ratings. Methodological and substantive limits of the approach are discussed.

Course of posttraumatic stress symptoms over the 5 years following an industrial disaster: A structural equation modeling study

The present study examined individual latent changes in posttraumatic stress disorder (PTSD) symptoms over a 60-month period after an industrial disaster. Participants were recruited from survivors of a factory explosion. Participants were assessed retrospectively for peritraumatic reactions and acute stress symptoms. Posttraumatic stress disorder symptoms were then assessed at 6, 15, and 60 months. Using structural equation modeling, the authors tested 3 hypotheses of individual latent change: stability of PTSD symptoms between 6, 15, and 60 months; change between 6 and 15 months; and change between 15 and 60 months. Only one model provided a good fit suggesting that PTSD symptoms evolved between 6 and 15 months after trauma exposure and remained stable at the individual level thereafter.

Transient error or specificity? An alternative to the staggered equivalent split-half procedure.

The data-based partial and complete reliability coefficients defined by G. Becker (2000) in his staggered equivalent split-half procedure (SESHP) were compared with the model-based specificity and consistency reliability coefficients defined by R. Steyer, M. J. Schmitt, and M. Eid (1999) in their latent state-trait model (LSTM). Partial reliability is based on coefficient alpha, which contains transient error. State and trait anxiety, measured using the State-Trait Anxiety Inventory on 2 occasions among French adults, illustrated both approaches. Theoretical and empirical analyses demonstrated that the specificity and consistency coefficients offer a testable alternative to the SESHP coefficients. In addition, dynamics of the state residual variance could be modeled and estimated in LSTM.

Measuring dynamic bipolarity in positive and negative activation.

The dynamic bipolarity of the positive and negative affective activation, measured with the PANAS scales, was studied using a pre-post design with an intervening experiment. The correlations between (a) the initial positive and negative constructs and (b) the respective change scores were estimated, random and systematic error being removed owing to a convenient structural equation modeling technique. Results demonstrated that a moderate perturbation may induce a medium correlation between latent change scores. Both strict dynamic independence and bipolarity were rejected. This result highlights the importance of individual differences in the way people perceive their affective changes. It is concluded that the PANAS two-factor model of affect provides only an approximate view of the structure and dynamics of mood.

The ambiguous utility of psychometrics for the interpretative foundation of socially relevant avatars

The persisting debates that measurement in psychology elicits can be explained by the conflict between two aspiration types. One, the epistemologic aspiration, resting on the search for scientific truth, and two, the social aspiration, resting on the demonstration of a capacity to contribute to psychological assessment problems in particular. Psychometrics answer essentially to psychology’s demand for social utility, leading to the quasi-exclusive attribution of importance to quantitative interpretation. For psychology to be considered an empirical science, it has to establish its capacity for the measurement of psychological phenomena, even if this means that it recognizes that these phenomena are essentially qualitative.

A Bistable View of Single Constructs Measured Using Balanced Questionnaires: Application to Trait Anxiety.

Single constructs measured using positively and negatively worded items are often incompatible with a congeneric model, but require 2 correlated factors. Imperfect correlation entails that 2 independent dimensions are required for representing the true variance. If 2 dimensions are sought, how can they be interpreted? This study shows how to extract a group factor orthogonal to the common factor, from either the positive or the negative variables. Applied to trait anxiety measured using the State–Trait Anxiety Inventory (STAI), the approach generates a bistable view of the construct, stressing basic definitional ambiguity.

Test-Specificity of the Advantage of Retaking Cognitive Ability Tests

In selection settings, when people retake the same cognitive ability tests, scores are generally positively biased. Our approach aimed to test whether these previous exposure effects are test-specific or transferable to other tests. We compared the differences between scores for first-time test takers and retakers for 2 kinds of material: old tests, known only to the retakers, and new tests, unknown to both groups. The current study used data collected during 2 sessions S and S+1 of a selection process for entry into the French national air transport pilot training system, with at least 500 first-time test takers and 130 retakers in each session. For Session S, on average, retakers scored higher on the old tests, but not on the new tests. Moreover, the material that was new to retakers at Session S was old at Session S+1, and the finding for old tests could be replicated at Session S+1. The finding that the acquired skills that led to higher scores on old tests were only test-specific is discussed.