Procedure and measures

Participants completed the following instruments as part of a larger study on

negotiation⁶. All instructions and materials were provided in French. The following tests were administered during the laboratory session of the study:

6 This study is described in more detail in chapter 7.

115 GERT – The GERT (Schlegel et al., under review) consists of 83 short video clips with sound (duration 1-3s), each representing one of 14 emotions (6 positive: Pride, joy, amusement, pleasure, relief, and interest; surprise; 7 negative: Anger, irritation, disgust, sadness, despair, fear, and anxiety) which is portrayed by one of ten actors (5 male, 5 female).

The verbal content is one of two pseudo-linguistic sentences. After each portrayal, participants are asked to choose which of the 14 emotions was expressed by the actor.

JACBART – We used a version that was programmed by Bänziger et al. (2009)

according to the information provided in Matsumoto et al. (2000) with the original stimuli, as the JACBART is no longer available from the test authors. The JACBART consists of 56 pictures of emotion expressions, each picture showing one of seven emotions (surprise, sadness, anger, happiness, fear, disgust, and contempt) portrayed by a different individual.

Each picture was displayed for 200 ms between two 500 ms presentations of the same individual with a neutral facial expression. After each of these 56 stimuli, participants were asked to choose which of the seven emotions had been shown in the brief emotion expression.

NV5R – This battery of tests (Thiébaut & Bidan-Fortier, 2003) measures cognitive aptitudes in young adults. We administered three subtests of the NV5R, namely general reasoning (inductive and deductive reasoning with numeric, spatial, and lexical content), attention (ability to maintain mental effort and perception speed), and vocabulary (knowledge of French, identifying synonyms and antonyms). As specified by the test authors, these subtests were administered with a time limit of 20, 3, and 4 minutes, respectively.

In addition, participants completed the following tests in an online session before coming to the lab:

116 MERT – The MERT (Bänziger et al., 2009) consists of 30 actor portrayals (three portrayals for each of 10 emotions: Irritation, anger, anxiety, fear, happiness, elated joy, disgust, contempt, sadness, despair) presented in four modalities (still picture, video, audio, audio–video). A standard pseudo-linguistic sentence is used as verbal content. After each of the 120 stimuli, participants were asked to choose which of the 10 emotions had been expressed by the actor.

MiniPONS – This test developed by Bänziger et al. (2011) consists of 64 portrayals of one actor displaying different affective states that are presented in one of six modalities (face, two voice versions, body, and combinations of the voice versions with face). After each portrayal, participants chose which one out of two affective states had been expressed by the actor.

MSCEIT - The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT; Mayer et al., 2003) consists of 141 Items that measure four branches of EI (Perceiving Emotions, Facilitating Thought, Understanding Emotions, Managing Emotions) using eight different tasks such as identifying emotions from abstract pictures, evaluating how moods impact thinking, and indicating the effectiveness of different solutions to problems. The MSCEIT yields scores for each branch and an overall EI score.

We also assessed the personality dimensions Extraversion, Openness,

Conscientiousness, Neuroticism, and Agreeableness using the 44-item French version of the Big Five Inventory (Plaisant, Courtois, Réveillère, Mendelsohn, & John, 2010).

6.3.3 Data analysis

Assessment of measurement properties according to the Rasch model. The Rasch model (Rasch, 1993) is a simple IRT model that can be used for developing and evaluating

117 scales in which items have two response options (e.g., here we coded responses as correct/

incorrect). The basic idea is that the probability of correctly responding to an item depends on a person’s ability (here: ERA) and the difficulty of an item, which are both located on the same latent scale θ. For any item, a person with a higher ability (located on the right side of the scale) has a higher probability of solving it than a person with a lower ability (located at the left side of the scale). In addition, items with a lower difficulty have a higher probability of being solved by an individual with a given ability than items with a higher difficulty. These theoretically postulated relationships can be displayed for each item with an Item

Characteristic Curve (ICC; for more details, see the Supplementary Material in Schlegel, Grandjean, & Scherer, 2012; and Embretson & Reise, 2000). The first aim of this study was to test whether these postulated relationships hold for our data, i.e., if the Rasch model fits.

We evaluated model fit by inspecting the weighted-fit or “Infit” and unweighted-fit or

“Outfit” index for each item using the eRm package in R (Mair & Hatzinger, 2007). These statistics indicate how much the observed ICC differs from the ICC that is theoretically expected from the Rasch model, the Outfit being more susceptible to outliers in individuals’

response patterns. Values between .80 and 1.20 are usually considered an “indication of useful fit” (Wright, Linacre, Gustafson, & Martin-Lof, 1994), with 1.00 representing perfect fit.

After establishing model fit, we computed the average difficulty of the GERT and assessed measurement precision by inspecting the so-called Test Information Curve (TIC) which shows the range of the latent dimension θ in which the test discriminates best among individuals, the standard error of measurement (SDEM) in the range of θ where the ability scores of most participants were located, and classic Cronbach’s alpha. We also tested

whether each item behaves in the same way, i.e., has the same ICCs, for both men and women

118 using the overall Andersen Likelihood Ratio Test implemented in the eRm package and the item-specific Raju’s Area index implemented in the difR package (Magis, Béland,

Tuerlinckx, & De Boeck, 2010). Given that gender differences have been reported for ERA (Hall, 1978), this evaluation of differential item functioning (DIF) provides an additional test of the psychometric quality of the GERT.

Assessment of construct validity. We investigated construct validity by computing correlation coefficients between the GERT total score and the total test scores, Big Five personality dimensions, and, where applicable, subtest scores of all measures reported above.

In order to visualize these relationships and enhance the understanding of the nomological net of the GERT, we created a correlation plot with the qgraph package in R (Epskamp, Cramer, Waldorp, Schmittmann, & Borsboom, 2012). Furthermore, we performed a stepwise

regression entering the overall test scores of the MERT, MiniPONS, JACBART, and MSCEIT as well as the three cognitive aptitude tests and the Big Five as independent

variables in order to identify the most substantial predictors of the GERT score. The stepwise algorithm performed both a forward and backward search using the p-value as a selection criterion (entry: 0.05, removal: 0.10). The selected model was then submitted to residual diagnostics. A Durbin-Watson test for independence of errors showed no indication of auto-correlation, DW = 1.95, p = .404. A visual inspection of a normal-quantile plot of the residuals showed no deviation from normality. A Breusch-Pagan test for homoscedasticity revealed that residuals had non-constant variance, BP = 20.91, p = .0003. To correct for heteroscedasticity, we recalculated the final regression model using weighted least squares (WLS) estimation. Finally, outlier diagnostics suggested that no influential cases were present in the data.

119 6.4 Results