Personal assessment of intimacy in relationships: Validity and measurement invariance across gender

IntroductionIntimacy is central in close relationships and a variety of definitions and instruments exist in scientific literature, making this concept complex to investigate. Furthermore, gender differences were identified in the definition and experience of intimacy.ObjectivesThis study aims to confirm the three-factor structure of the personal assessment of intimacy in relationships (PAIR, Schaefer & Olson, 1981), commonly used in research and marital therapy, developed by Moore et al. (1998) and to examine the measurement equivalence of the scale across gender.MethodA confirmatory factor analysis (CFA) was performed on the responses of 313 women and 251 men in committed relationships in a French population. Measurement equivalence of the scale across gender was then conducted with the best-fitting model.ResultsThe results of CFA and post-hoc analyses revealed that the three-factor model revised with 18 items was the best fit to the data: (1) engagement (10 items), (2) communication (5 items), (3) shared friends (3 items). PAIR-18 displayed a lack of metric and scalar invariance across gender but estimated means of latent variables is not very different between the full invariant model and the unconstraint models.ConclusionNevertheless, consideration of gender differences in the construct of intimacy is very important for theoretical research on intimacy in romantic relationships and for the interventions of marital therapists based on intimacy.     

Invariance Properties for General Diagnostic Classification Models

In item response theory (IRT), the invariance property states that item parameter estimates are independent of the examinee sample, and examinee ability estimates are independent of the test items. While this property has long been established and understood by the measurement community for IRT models, the same cannot be said for diagnostic classification models (DCMs). DCMs are a newer class of psychometric models that are designed to classify examinees according to levels of categorical latent traits. We examined the invariance property for general DCMs using the log-linear cognitive diagnosis model (LCDM) framework. We conducted a simulation study to examine the degree to which theoretical invariance of LCDM classifications and item parameter estimates can be observed under various sample and test characteristics. Results illustrated that LCDM classifications and item parameter estimates show clear invariance when adequate model data fit is present. To demonstrate the implications of this important property, we conducted additional analyses to show that using pre-calibrated tests to classify examinees provided consistent classifications across calibration samples with varying mastery profile distributions and across tests with varying difficulties.     

Measurement invariance of the Utrecht Work Engagement Scale for Students: A study across secondary school pupils and university students

School engagement is a multidimensional construct characterized by vigour, dedication, and absorption towards academic work that is related to school achievement. This study aimed to examine the measurement invariance of a school engagement measure – the Utrecht Work Engagement Scale-Students (UWES-S) – across secondary school pupils and university students. Two samples of secondary school pupils (n = 251) and university students (n = 229) were used. The results supported the original three-factor structure (vigour, dedication and absorption) of the UWES-S instead of a two- or a one-factor structure in both samples. Evidence for the metric and scalar invariance of the measure across secondary school pupils and university students was also found. The university sample had higher scores in vigour and absorption but not in dedication. These findings demonstrate that the UWES-S can be used for developmental studies where school engagement and its relation with other variables needs to be compared across distinct educational levels.     

On the relationship between sources of within- and between-group differences and measurement invariance in the common factor model

Investigating sources of within- and between-group differences and measurement invariance (MI) across groups is fundamental to any meaningful group comparison based on observed test scores. It is shown that by placing certain restrictions on the multigroup confirmatory factor model, it is possible to investigate the hypothesis that within- and between-group differences are due to the same factors. Moreover, the modeling approach clarifies that absence of measurement bias implies common sources of within- and between-group variation. It is shown how the influence of background variables can be incorporated in the model. The advantages of the modeling approach as compared with other commonly used methods for group comparisons is discussed and illustrated by means of an analysis of empirical data.     

Biased extensive measurement: The homogeneous case

In the homogeneous case of one type of objects, we prove the existence of an additive scale unique up to a positive scaling transformation without transitivity of indifference and with a property of homothetic invariance weaker than monotonicity. The representation, which is a particular case of a semiorder representation, reveals a unique positive factor α?1 that biases extensive structures and explains departures from these standard axioms of extensive measurement (α=1). We interpret α as characterizing the qualitative influence of the underlying measurement process and we show that it induces a proportional indifference threshold.     

Is the DOSPERT gender invariant? A psychometric test of measurement invariance

It is well established in the risk literature that men tend to take more risks than women. This gender difference, however, is often qualified by its domain specificity. Considering recent research on the domain generality of risk taking as a disposition, there is a need to examine the degree to which men take more risks than women, in general. In order to make substantive conclusions about the gender differences in risk‐taking propensity, one must first establish measurement invariance, which is required for the meaningful interpretation of observed group differences. In this paper, we examined the measurement invariance of the Domain‐Specific Risk‐Taking scale (DOSPERT)—one of the most popular measures of individual differences in risk taking. We found that the DOSPERT violated configural invariance in a bifactor model, indicating that the underlying factor structure of the DOSPERT differs between men and women. Even after removing the social risk dimension, DOSPERT still failed to reach scalar invariance. Taken together, these findings suggest that score differences in the DOSPERT may be due to response artifacts rather than true differences in the latent construct. Therefore, gender differences in the DOSPERT must be interpreted with caution. Implications for the measurement of risk taking are discussed.     

The structure of trust as a reflection of culture and institutional power structure: Evidence from four East Asian societies

Using the Global Trust Inventory, an integrated measure of trust toward 21 relationships and institutions, the structure of trust was explored in four East Asian societies (Mainland China, Japan, South Korea, and Taiwan). The Western model, in which trust is distributed among seven factors representing different branches of society, did not generalize to these East Asian societies, perhaps due to differences in culture and institutional power structures. Instead, two unique structures of trust were identified. Mainland China had a top‐down structure of trust (the China model), in which trust is hierarchically separated between the central government and subordinate implementing bodies. The other three democratic East Asian societies shared a hybrid structure of trust (the Democratic East Asian model) that has a degree of similarity to both the China model and the Western model. Having established two similar, but still distinct models, a cross‐cultural comparison was made on the proportions of trust profiles generated by latent profile analysis. Mainland China had the largest proportion of people with a high propensity to trust, followed by Japan and South Korea, and Taiwan was the least trusting. Implications of the structure of trust and this alternative approach to conducting cross‐cultural comparisons are discussed.     

Subjective well-being in adolescence: New psychometric evidences on the satisfaction with life scale

The main purpose of the present study was to test the psychometric properties of the Satisfaction with Life Scale (SWLS) in a large sample of Spanish adolescents. The sample consisted of 1020 non-clinical adolescents with a mean age of 15.96 years (SD = 1.68). The level of internal consistency of the SWLS Total score by means of McDonald’s Omega was .85. The one-dimensional model displayed appropriate goodness of-fit indices. Strong measurement invariance for the one factor model across age and gender was found. Younger adolescents reported higher levels of life satisfaction. In addition, SWLS total score was negatively associated with behavioural and emotional. The study confirmed that the SWLS is a useful tool for the screening of self-reported life satisfaction in adolescents.     

Bayesian SEM for Specification Search Problems in Testing Factorial Invariance

Specification search problems refer to two important but under-addressed issues in testing for factorial invariance: how to select proper reference indicators and how to locate specific non-invariant parameters. In this study, we propose a two-step procedure to solve these issues. Step 1 is to identify a proper reference indicator using the Bayesian structural equation modeling approach. An item is selected if it is associated with the highest likelihood to be invariant across groups. Step 2 is to locate specific non-invariant parameters, given that a proper reference indicator has already been selected in Step 1. A series of simulation analyses show that the proposed method performs well under a variety of data conditions, and optimal performance is observed under conditions of large magnitude of non-invariance, low proportion of non-invariance, and large sample sizes. We also provide an empirical example to demonstrate the specific procedures to implement the proposed method in applied research. The importance and influences are discussed regarding the choices of informative priors with zero mean and small variances. Extensions and limitations are also pointed out.     

Measurement invariance of personality traits from a five-factor model perspective: multi-group confirmatory factor analyses of the HP5 inventory

Associations between personality and health may be influenced by contextual factors varying across studied cohorts. Moreover, measurement bias related to contextual factors could also influence these associations. Gender and age have been discussed as important contextual factors when studying personality and health outcomes. An examination of measurement invariance across gender and age may therefore be warranted. In the present study, measurement invariance across age and gender was examined for a five-factor model of personality traits in which scales have been included to operationalise lower-order traits related to health-behaviour or health outcomes. Using multi-group confirmatory factor analysis on a population based cohort (n= 5700), all important parameters of the measurement model were found to be invariant. On the basis of this invariant model, hypotheses of mean differences across age and gender in personality traits were tested. These results were discussed in relation to meta-analyses on personality change and gender differences in personality.