A Comparison of Inverse-Wishart Prior Specifications for Covariance Matrices in Multilevel Autoregressive Models

Multilevel autoregressive models are especially suited for modeling between-person differences in within-person processes. Fitting these models with Bayesian techniques requires the specification of prior distributions for all parameters. Often it is desirable to specify prior distributions that have negligible effects on the resulting parameter estimates. However, the conjugate prior distribution for covariance matrices—the Inverse-Wishart distribution—tends to be informative when variances are close to zero. This is problematic for multilevel autoregressive models, because autoregressive parameters are usually small for each individual, so that the variance of these parameters will be small. We performed a simulation study to compare the performance of three Inverse-Wishart prior specifications suggested in the literature, when one or more variances for the random effects in the multilevel autoregressive model are small. Our results show that the prior specification that uses plug-in ML estimates of the variances performs best. We advise to always include a sensitivity analysis for the prior specification for covariance matrices of random parameters, especially in autoregressive models, and to include a data-based prior specification in this analysis. We illustrate such an analysis by means of an empirical application on repeated measures data on worrying and positive affect.     

Exploring Factor Model Parameters across Continuous Variables with Local Structural Equation Models

Using an empirical data set, we investigated variation in factor model parameters across a continuous moderator variable and demonstrated three modeling approaches: multiple-group mean and covariance structure (MGMCS) analyses, local structural equation modeling (LSEM), and moderated factor analysis (MFA). We focused on how to study variation in factor model parameters as a function of continuous variables such as age, socioeconomic status, ability levels, acculturation, and so forth. Specifically, we formalized the LSEM approach in detail as compared with previous work and investigated its statistical properties with an analytical derivation and a simulation study. We also provide code for the easy implementation of LSEM. The illustration of methods was based on cross-sectional cognitive ability data from individuals ranging in age from 4 to 23 years. Variations in factor loadings across age were examined with regard to the age differentiation hypothesis. LSEM and MFA converged with respect to the conclusions. When there was a broad age range within groups and varying relations between the indicator variables and the common factor across age, MGMCS produced distorted parameter estimates. We discuss the pros of LSEM compared with MFA and recommend using the two tools as complementary approaches for investigating moderation in factor model parameters.     

Behavioral variability in an evolutionary theory of behavior dynamics

McDowell’s evolutionary theory of behavior dynamics (McDowell, 2004) instantiates populations of behaviors (abstractly represented by integers) that evolve under the selection pressure of the environment in the form of positive reinforcement. Each generation gives rise to the next via low‐level Darwinian processes of selection, recombination, and mutation. The emergent patterns can be analyzed and compared to those produced by biological organisms. The purpose of this project was to explore the effects of high mutation rates on behavioral variability in environments that arranged different reinforcer rates and magnitudes. Behavioral variability increased with the rate of mutation. High reinforcer rates and magnitudes reduced these effects; low reinforcer rates and magnitudes augmented them. These results are in agreement with live‐organism research on behavioral variability. Various combinations of mutation rates, reinforcer rates, and reinforcer magnitudes produced similar high‐level outcomes (equifinality). These findings suggest that the independent variables that describe an experimental condition interact; that is, they do not influence behavior independently. These conclusions have implications for the interpretation of high levels of variability, mathematical undermatching, and the matching theory. The last part of the discussion centers on a potential biological counterpart for the rate of mutation, namely spontaneous fluctuations in the brain's default mode network.     

Using Marginal Structural Modeling for Grade Retention Effects

Vandecandelaere, Vansteelandt, De Fraine, and Van Damme (this issue) described marginal structural modeling (MSM) and used it to estimate the effects of a time-varying intervention, retention (holding back) in school grades, on students' math achievement. This commentary supplements Vandecandelaere et al. (this issue) and discusses several topics in retention studies and MSM. First, we discuss the importance of equating time-varying confounders in retention studies. Second, we discuss same-grade and same-age comparisons in retention studies. Third, we discuss one important section in the authors' overview of MSM: why standard methods (e.g., ANCOVA, propensity score analysis) cannot properly adjust for time-varying confounders. Finally, using the grade retention analyses in Vandecandelaere et al. (this issue) as an example, we provide our insights on four aspects of MSM: (a) covariate selection, (b) estimation of weights, (c) evaluation of balance properties, and (d) missing data handling.     

Anxiety-related threat bias in recognition memory: the moderating effect of list composition and semantic-similarity effects

Individuals with high anxiety show bias for threatening information, but it is unclear whether this bias affects memory. Recognition memory studies have shown biases for recognising and rejecting threatening items in anxiety, prompting the need to identify moderating factors of this effect. This study focuses on the role of semantic similarity: the use of many semantically related threatening words could increase familiarity for those items and obscure anxiety-related differences in memory. To test this, two recognition memory experiments varied the proportion of threatening words in lists to manipulate the semantic-similarity effects. When similarity effects were reduced, participants with high trait anxiety were biased to respond “new” to threatening words, whereas when similarity effects were strong there was no effect of anxiety on memory bias. Analysis of the data with the drift diffusion model showed that the bias was due to differences in processing of the threatening stimuli rather than a simple response bias. These data suggest that the semantic similarity of the threatening words significantly affects the presence or absence of anxiety-related threat bias in recognition memory. The results indicate that trait anxiety is associated with a bias to decide that threatening stimuli were not previously studied, but only when semantic-similarity effects are controlled. Implications for theories of anxiety and future studies in this domain are discussed.     

四参数Logistic模型潜在特质参数的Warm加权极大似然估计

本文以四参数Logistic(4-parameter Logistic,4PL)模型为研究对象,根据Warm的加权极大似然估计技巧,提出了4PL模型潜在特质参数的加权极大似然估计方法,并借助模拟研究对加权极大似然估计的性质进行验证。研究结果表明,与通常的极大似然估计和后验期望估计相比,加权极大似然估计的偏差(bias)明显减小,并且具有良好的返真性能。此外,在测试的长度较短和项目的区分度较小的情况下,加权极大似然估计依然保持了良好的统计性质,表现出更加显著的优势。     

Personality,hedonic balance and the quality and quantity of sleep in adulthood

Objective: Sufficient and good-quality sleep is important for individual functioning. This study explored associations between personality and sleep duration and sleep quality in adulthood. The mediating role of hedonic balance and the moderating roles of age and sex were also explored.

Method: A nationally representative sample of Australian adults (n = 14,065; M_age = 44.4 years; 53.1% women) completed self-report measures of personality, sleep, hedonic balance and demographic variables (e.g. health status, employment status) in late 2013.

Results: After controlling for demographic variables, we found that high neuroticism was associated with poorer sleep quality, and both long and short sleep durations (a curvilinear relationship). Small effects were also observed relating high extraversion and low openness to better sleep quality. Hedonic balance mediated all linear and non-linear associations between personality and sleep. Additional moderator analyses showed that high openness was more strongly related to poor sleep quality among men and young adults. High neuroticism was more strongly related to poor sleep quality among men.

Conclusion: Findings indicate that personality is important for sleep in adulthood and that hedonic balance features a prominent role in this association.     

Age Differences in the Variance of Personality Characteristics

In contrast to mean‐level comparisons, age group differences in personality trait variance have received only passing research interest. This may seem surprising because individual differences in personality characteristics are exactly what most of personality psychology is about. Because different proposed mechanisms of personality development may entail either increases or decreases in variance over time, the current study is exploratory in nature. Age differences in variance were tested by comparing the standard deviations of the five‐factor model domain and facet scales across two age groups (20 to 30 years old versus 50 to 60 years old). Samples from three cultures (Estonia, the Czech Republic and Russia) were employed, and two methods (self‐reports and informant‐reports) were used. The results showed modest convergence across samples and methods. Age group differences were significant for 11 of 150 facet‐level comparisons but never consistently for the same facets. No significant age group differences were observed for the five‐factor model domain variance. Therefore, there is little evidence for individual differences in personality characteristics being systematically smaller or larger in older as opposed to younger people. We discuss the implications of these findings for understanding personality development. Copyright © 2015 European Association of Personality Psychology     

The role of workaholism in the job demands-resources model

Background and Objectives: The present study tries to gain more insight in workaholism by investigating its antecedents and consequences using the job demands-resources model. Design: We hypothesized that job demands would be positively related to workaholism, particularly when job resources are low. In addition, we hypothesized that workaholism would be positively related to negative outcomes in three important life domains: health, family, and work. Methods: The research involved 617 Italian workers (employees and self-employed). To test the hypotheses we applied structural equation modeling (SEM) and moderated structural equation modeling (MSEM) using Mplus 6. Results: The results of SEM showed a good model where workload, cognitive demands, emotional demands, and customer-related social stressors were positively related to workaholism and work–family conflict (WFC) (partial mediation). Additionally, workaholism was indirectly related to exhaustion and intentions to change jobs through WFC. Moreover, MSEM analyses confirmed that job resources (job security and opportunities for development) buffered the relationship between job demands and workaholism. Particularly, the interaction effects were statistically significant in five out of eight combinations. Conclusions: These findings suggest that workaholism is a function of a suboptimal work environment and predicts unfavorable employee outcomes. We discuss the theoretical and practical implications of these findings.     

Factorial structure of the perceived stress scale and implications for scoring

IntroductionThe 10-item Perceived Stress Scale (PSS-10) is a brief, widely-used measure of perceived stressful experiences that evaluates the degree to which people perceive their lives as unpredictable, uncontrollable or overloaded.ObjectiveThe present study examined the factor structure of the Greek version of the PSS-10.MethodUsing a representative sample of 320 adults from Cyprus, alternative confirmatory factor analytic models were compared to specifically assess bidimensional versus unidimensional specifications for the scale.ResultsA bifactor model with a general factor which loads on all items and a specific one which loads on positively-worded items that capture the notion of self-efficacy to deal with stressful situations, was found to fit well to the data, while providing evidence of a robust latent factor of general distress. Reliability and construct validity evidence with multiple criterion variables were also examined.ConclusionsAlthough a simple unidimensional specification has not been empirically supported in previous research, bifactor modeling exemplifies the extent of multidimensionality and implies that a single score may be reliably used for practical purposes.