A confirmatory examination of age‐associated personality differences: Deriving age‐related measurement‐invariant solutions using ant colony optimization

Olaru, Gabriel; Schroeders, Ulrich; Wilhelm, Oliver; Ostendorf, Fritz

doi:10.1111/jopy.12373

Cited by 27 publications

(61 citation statements)

References 55 publications

(99 reference statements)

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“…However, constraining the second‐order factor loadings to equality in order to meaningfully compare the means of the traits is equivalent to constraining the factor correlations in a correlated facet model. We argue that these parameters constitute structural parameters rather than measurement parameters and should be freely estimated (see also Olaru et al, 2018). Second, in the scalar invariant higher‐order model, the facet level means must be constrained to equality (Chen, West, & Sousa, 2006).…”

Section: Methodsmentioning

confidence: 99%

Compiling Measurement Invariant Short Scales in Cross–Cultural Personality Assessment Using Ant Colony Optimization

2020

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Examining the influence of culture on personality and its unbiased assessment is the main subject of cross‐cultural personality research. Recent large‐scale studies exploring personality differences across cultures share substantial methodological and psychometric shortcomings that render it difficult to differentiate between method and trait variance. One prominent example is the implicit assumption of cross‐cultural measurement invariance in personality questionnaires. In the rare instances where measurement invariance across cultures was tested, scalar measurement invariance—which is required for unbiased mean‐level comparisons of personality traits—did not hold. In this article, we present an item sampling procedure, ant colony optimization, which can be used to select item sets that satisfy multiple psychometric requirements including model fit, reliability, and measurement invariance. We constructed short scales of the IPIP‐NEO‐300 for a group of countries that are culturally similar (USA, Australia, Canada, and UK) as well as a group of countries with distinct cultures (USA, India, Singapore, and Sweden). In addition to examining factor mean differences across countries, we provide recommendations for cross‐cultural research in general. From a methodological perspective, we demonstrate ant colony optimization's versatility and flexibility as an item sampling procedure to derive measurement invariant scales for cross‐cultural research. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

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Section: Methodsmentioning

confidence: 99%

Compiling Measurement Invariant Short Scales in Cross–Cultural Personality Assessment Using Ant Colony Optimization

2020

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“…NEO‐PI‐R) and sample (i.e. German NEO‐PI‐R normative sample), where scalar measurement invariance was also found for an abbreviated version on a facet level (Olaru, Schroeders, Wilhelm, et al, ). Adequate measurement models included nearly all items (low item effect), and this composition did not change substantially across age (low age effect; refer to the relative homogenous item‐selection frequencies in Figure and the low standard deviations in Table ).…”

Section: Resultsmentioning

confidence: 89%

“…While a number of studies in personality development follow this procedure (Allemand et al, , ; Nye et al, ; Olaru, Schroeders, Wilhelm, et al, ; Small et al, ), results show that obtaining measurement invariance across broad age ranges can be challenging. Satisfying model fit and measurement invariance was only achieved by parcelling items into aggregates (Allemand et al, , ; Small et al, ), by data‐driven modifications to the measurement models (Nye et al, ), or by item selection (Olaru, Schroeders, Wilhelm, et al, ). In addition, less restrictive procedures have been proposed as alternatives to strict testing procedures in personality research.…”

Section: Item Type Classificationmentioning

confidence: 99%

‘Grandpa, Do you like Roller Coasters?’: Identifying Age–Appropriate Personality Indicators

et al. 2019

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Personality development research heavily relies on the comparison of scale means across age. This approach implicitly assumes that the scales are strictly measurement invariant across age. We questioned this assumption by examining whether appropriate personality indicators change over the lifespan. Moreover, we identified which types of items (e.g. dispositions, behaviours, and interests) are particularly prone to age effects. We reanalyzed the German Revised NEO Personality Inventory normative sample (N = 11,724) and applied a genetic algorithm to select short scales that yield acceptable model fit and reliability across locally weighted samples ranging from 16 to 66 years of age. We then examined how the item selection changes across age points and item types. Emotion-type items seemed to be interchangeable and generally applicable to people of all ages. Specific interests, attitudes, and social effect items-most prevalent within the domains of Extraversion, Agreeableness, and Openness-seemed to be more prone to measurement variations over age. A large proportion of items were systematically discarded by the item-selection procedure, indicating that, independent of age, many items are problematic measures of the underlying traits. The implications for personality assessment and personality development research are discussed. © 2019 European Association of Personality Psychology

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“…This is particularly true when considering Big Five structure across the lifespan. Evidence for the lack of measurement invariance across age (Marsh et al, 2012;Nye , Allemand, Gosling, Potter, & Roberts, 2016;Olaru, Schroeders, Wilhelm, & Ostendorf, 2018;Tackett et al, 2009) and distinct trajectories for facets of the same Big Five traits (Jackson et al, 2009;Soto, John, Gosling, & Potter, 2011;Soto & John, 2011) suggest that the content of the Big Five dimensions -and the generalizability of the Big Five structure -may vary across the lifespan. The current study sought to evaluate the structure of the Big Five across the lifespan using a novel network approach rather than traditional factor analytic techniques.…”

Section: Interindividual Age Differences In Personality Network Strucmentioning

confidence: 99%

“…Thus, differentiation among constructs is often largely ignored in favor of evaluations of coherence within constructs. Even with the over emphasis on coherence, measurement invariance across time or age is not always found (Marsh et al, 2012;Nye et al, 2016;Olaru et al, 2018;Tackett et al, 2009) A number of options have been put forth in response to the tendency of measurement models of the Big Five to not fit well (Hopwood & Donnellan, 2010). On the one hand, the misfit can be explained away, as one should not expect a good fit given the complexity of personality.…”

Section: Beyond Internal Consistency: Coherence and Differentiationmentioning

confidence: 99%

Interindividual Age Differences in Personality Structure

Beck¹,

Condon²,

Jj³

2019

Preprint

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Most investigations in the structure of personality traits do not adequately address age; instead they presuppose a constant structure across the lifespan. Further, few studies look at the structure of personality traits a-theoretically, often neglecting to examine the relationship among indicators within a trait (coherence) and across traits (differentiation). Using a network approach, the present study examines (1) age differences in differentiation and coherence, (2) the similarity between the Big Five and network structures, and (3) the consistency of network structure across age groups in a large, cross-sectional sample. Results indicate that coherence shows early gains in adolescence with few changes across the lifespan, while differentiation mostly weakens across adulthood. The result of these age-related changes is that Big Five indicators only parallel the Big Five structure among young but not older adults. The structure of young adults tends to be quite similar while the network structures of older adults appear to greatly differ from one another. These results suggest that older adults have a different structure of personality than younger adults and suggest that future research should not assume consistency in personality structure across the lifespan.

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A confirmatory examination of age‐associated personality differences: Deriving age‐related measurement‐invariant solutions using ant colony optimization

Cited by 27 publications

References 55 publications

Compiling Measurement Invariant Short Scales in Cross–Cultural Personality Assessment Using Ant Colony Optimization

Compiling Measurement Invariant Short Scales in Cross–Cultural Personality Assessment Using Ant Colony Optimization

‘Grandpa, Do you like Roller Coasters?’: Identifying Age–Appropriate Personality Indicators

Interindividual Age Differences in Personality Structure

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