An examination of model fit and measurement invariance of general mental ability and personality measures used in the multilingual context of the Swiss Armed Forces: A Bayesian structural equation modeling approach.

Measurement invariance of psychological test batteries is an essential quality criterion when the test batteries are administered in different cultural and language contexts. The purpose of this study was to examine to what extent measurement model fit and measurement invariance across the two largest language groups in Switzerland (i.e., German and French speakers) can be assumed for selected general mental ability and personality tests used in the Swiss Armed Forces' cadre selection process. For the model fit and invariance testing, we used Bayesian structural equation modeling (BSEM). Because the sizes of the language group samples were unbalanced, we reran the invariance testing with the subsampling procedure as a robustness check. The results showed that at least partial approximate scalar invariance can be assumed for the constructs. However, comparisons in the full sample and subsamples also showed that certain test items function differently across the language groups. The results are discussed regarding the three following issues: First, we critically discuss the applied criterion and alternative effect size measures for assessing the practical importance of non-invariances. Second, we highlight potential remedies and further testing options, that can be applied, once certain items have been detected to function differently. Third, we discuss alternative modeling and invariance testing approaches to BSEM and outline future research avenues.

Longitudinal measurement invariance in urbanization index of Chinese communities across 2000 and 2015: a Bayesian approximate measurement invariance approach.

BACKGROUND: The Urbanicity Scale was developed based on the China Health and Nutrition Survey (CHNS) to measure the urbanization index of communities according to 12 components. The present study was designed to systematically investigate the factorial validity, reliability, and longitudinal measurement invariance (LMI) of the Urbanicity Scale. METHODS: Six waves of CHNS data from 2000 to 2015 were adopted. The factor structure and reliability of the Urbanicity Scale for 301 communities were examined using Bayesian exploratory factor analysis. Metric and scalar LMIs were evaluated using both the conventional exact and a novel approximate LMI approach via Bayesian structural equation modeling across various timeframes. RESULTS: The findings verified the one-factor structure for the Urbanicity Scale, with adequate reliability. LMI was established for the Urbanicity Scale only over a shorter timeframe from 2006 to 2009 but not over a longer timeframe from 2000 to 2015. Partial LMI was found in the factor loadings and item intercepts for the Urbanicity Scale over the 2004 to 2011 period. CONCLUSION: Interpretation of the temporal change in urbanicity was supported only for a shorter (2006 to 2009) but not a longer timeframe (2000 to 2015). Adjustments addressing the partial non-invariance of the measurement parameters are needed for the analysis of temporal changes in urbanicity between 2004 and 2011.

The structural validity of the IKDC and its relationship with quality of life following ACL reconstruction.

OBJECTIVE: The purpose of this study was to (a) examine the structural validity of the International Knee Documentation Committee Subjective Knee Form in light of previously reported dimensionality issues, and (b) examine the relationships between the IKDC and patients' knee-related quality of life 2-9 years after anterior cruciate ligament (ACL) reconstruction. METHODS: A prospective research design was employed, wherein 319 patients (mean age = 29.07, SD = 9.03) completed the IKDC before surgery, 191 patients (mean age = 29.71, SD = 9.36) completed the IKDC at 6 months post-surgery, and 132 patients (mean age = 34.34, SD = 7.89) completed the IKDC and the Anterior Cruciate Ligament Quality of Life Survey (ACL-QOL) at 2-9 years post-surgery. RESULTS: Bayesian structural equation modeling analysis confirmed the two-factor structure (symptom & knee articulation and activity level) represented the most accurate conceptualization of perceived knee function across the three time-points. Moreover, findings revealed that of the two IKDC subscales pre-operatively, activity level was most strongly associated with long-term quality of life at 2-9 years following surgery, whereas 2-9 years post-operatively, symptoms and knee articulation was most strongly associated with long-term quality of life. CONCLUSIONS: The IKDC provides clinicians with a convenient total score to assess patients' perceived knee function, but its unidimensional factor structure is a poor representation of its items and fails to detect discrepancies in patients' post-operative quality of life, such as the relative importance of perceived knee activity level before reconstructive surgery.

The Temporal Ordering of Motivation and Self-Control: A Cross-Lagged Effects Model.

Mechanisms leading to cognitive energy depletion in performance settings such as high-level sports highlight likely associations between individuals' self-control capacity and their motivation. Investigating the temporal ordering of these concepts combining self-determination theory and psychosocial self-control theories, the authors hypothesized that athletes' self-control capacity would be more influenced by their motivation than vice versa and that autonomous and controlled types of motivation would predict self-control capacity positively and negatively, respectively. High-level winter-sport athletes from Norwegian elite sport colleges (N = 321; 16-20 years) consented to participate. Using Bayesian structural equation modeling and 3-wave analyses, findings revealed credible self-control → motivation → self-control cross-lagged effects. Athletes' trait self-control especially initiated the temporal ordering of the least controlled types of motivation (i.e., intrinsic, integrated, and amotivation). Findings indicate that practicing self-control competencies and promoting athletes' autonomous types of motivation are important components in the development toward the elite level. These components will help athletes maintain their persistent goal striving by increasing the value and inherent satisfaction of the development process, avoiding the debilitating effects of self-control depletion and exhaustion.

The health literacy questionnaire among the aged in Changsha, China: confirmatory factor analysis.

BACKGROUND: Health literacy is defined as the cognitive and social skills that determine the motivation and ability of individuals to gain access to, understand and use information in ways that promote and maintain good health. A Health Literacy Questionnaire (HLQ) is a toolkit with good reliability and validity. Accordingly, this study administered HLQ among older adults in China to examine its factor structure, reliability, homogeneity, and discriminant validity for use in understanding better the health literacy of older adults and determining corresponding measures. METHODS: Psychometric properties were examined based on the data collected via face-to-face interviews (N = 343). Tests included the difficulty level, composite scale reliability, confirmatory factor analysis (CFA), and Bayesian structural equation modeling (BSEM). RESULTS: The easiest scale to obtain a high score was "Social support for health" and the hardest, "Navigating the health care system" and "Appraisal of health information." Two one-factor models fitted well with no correlated residuals allowed. After model modification, the CFA fit statistics of the other seven scales were good. All HLQ scales were found to be homogenous, with a composite reliability ranging from 0.74 to 0.85. The nine-factor Bayesian structural equation model fitted the data well (Posterior-Predictive-P value = 0.670; 95% Confidence Interval for the difference between the observed and replicated Chi-square values = - 163.320, 102.750). CONCLUSIONS: The Chinese version of the HLQ has strong construct and content validity and high composite reliability when applied to older adults in Changsha City, China. Therefore, the nine-scale HLQ can now be administered to Chinese older adults, thereby providing a powerful approach to understanding the multidimensional area of health literacy.

Bayesian Factor Analysis as a Variable-Selection Problem: Alternative Priors and Consequences.

Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor-loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, Muthén & Asparouhov proposed a Bayesian structural equation modeling (BSEM) approach to explore the presence of cross loadings in CFA models. We show that the issue of determining factor-loading patterns may be formulated as a Bayesian variable selection problem in which Muthén and Asparouhov's approach can be regarded as a BSEM approach with ridge regression prior (BSEM-RP). We propose another Bayesian approach, denoted herein as the Bayesian structural equation modeling with spike-and-slab prior (BSEM-SSP), which serves as a one-stage alternative to the BSEM-RP. We review the theoretical advantages and disadvantages of both approaches and compare their empirical performance relative to two modification indices-based approaches and exploratory factor analysis with target rotation. A teacher stress scale data set is used to demonstrate our approach.

Anti-old and anti-youth attitudes among older adults: focusing on middle-aged and old age identity.

There is currently a lack of comprehensive scholarly information concerning the attitudes older people hold toward both older adults and the young. Using the social identity theory framework, this study investigated older identity issues including middle-aged identity and old age identity. We conducted an online survey of Japanese older participants (N = 301) and then implemented a Bayesian structural equation modeling to examine whether age and gender predicted middle-aged/old age identity in addition to whether middle-aged/old age identity predicted anti-old/anti-youth attitudes. Results showed the more strongly participants identified with being middle-aged the more positive their attitudes were toward old/young people, while they showed no significant relationship between old age identity and the attitudes. Regarding participant ages, the results found no significant relationship with middle-aged identity but a positive relationship with old age identity. These findings will contribute to psychological research aimed at reducing anti-old/anti-youth attitudes among older adults.11 A part of this study was presented at the 85th Annual Convention of the Japanese Psychological Association.

Estimation of a Structural Equation Modeling of Quality of Life Mediated by Difficulty in Daily Life in Survivors of Breast Cancer.

BACKGROUND: The purpose of this study was to clarify the structural relationship of quality of life (QOL) in survivors of breast cancer, including difficulty in daily life and negative experiences in daily activities, as health-related indicators. METHODS: Participants were survivors of breast cancer for more than 2 years after primary breast cancer surgery and belonged to self-help groups. The assessment used FACT-B (QOL), HADS (anxiety and depression), SOC (sense of coherence), WHODAS 2.0 (difficulties in daily life), and CAOD (negative experiences in daily activities). Bayesian structural equation modeling (BSEM) was performed to analyze the hypothesized model. If the causal model was significant, multiplication of the path coefficient from emotional distress (anxiety and depression) to QOL, and from SOC to emotional distress, was considered a direct effect on QOL, and from SOC to difficulty in daily life, from difficulty in daily life to negative experiences in daily activities, and from negative experiences in daily activities to anxiety and depression were considered indirect effects on QOL. RESULTS: The participants comprised 73 survivors of breast cancer. The goodness of fit of the model in the BSEM was satisfactory. The direct effect was 0.274, and the indirect effect was 0.164. CONCLUSIONS: An additional finding of this study is that coping with difficulty in daily life and negative experiences in daily activities related to QOL may improve QOL.

Factor Structure of the PANAS With Bayesian Structural Equation Modeling in a Chinese Sample.

The Positive and Negative Affect Schedule (PANAS) is the most widely used self-report instrument for assessing affect. However, there are inconsistent findings regarding the factor structure of the PANAS. In this study, we applied Bayesian structural equation modeling (BSEM) to investigate the structure of the PANAS using data from a sample of 893 Chinese middle and high school students. Four models, the orthogonal two-, the oblique two-, the three-, and the bi-factor models were tested with prior specifications including approximately zero cross-loadings and residual covariances. The results indicated that the orthogonal two-factor model specified with informative priors for both cross-loadings and residual correlations has the best model fit. Confirmatory factor analysis with the maximum likelihood estimator (ML-CFA) based on modifications from BSEM analysis showed improved model fit compared to ML-CFA based on frequentist analysis, which is the evidence for the merit of BSEM for addressing misspecifications.

Respective Mediating Effects of Social Position and Work Environment on the Incidence of Common Cardiovascular Risk Factors.

Background Social position and work environment are highly interrelated and their respective contribution to cardiovascular risk is still debated. Methods and Results In a cohort of 20 625 French workers followed for 25 years, discrete-time survival analysis with reciprocal mediating effects, adjusted for sex, age, and parental history of early coronary heart disease, was performed using Bayesian structural equation modeling to simultaneously investigate the extent to which social position mediates the effect of work environment and, inversely, the extent to which work environment mediates the effect of social position on the incidence of common cardiovascular risk factors. Depending on the factor, social position mediates 2% to 53% of the effect of work environment and work environment mediates 9% to 87% of the effect of social position. The mediation by work environment is larger than that by social position for the incidence of obesity, hypertension, dyslipidemia, diabetes, sleep complaints, and depression (mediation ratios 1.32-41.5, 6.67 when modeling the 6 factors together). In contrast, the mediation by social position is larger than that by work environment for the incidence of nonmoderate alcohol consumption, smoking, and leisure-time physical inactivity (mediation ratios 0.16-0.69, 0.26 when modeling the 3 factors together). Conclusions The incidence of behavioral risk factors seems strongly dependent on social position whereas that of clinical risk factors seems closely related to work environment, suggesting that preventive strategies should be based on education and general practice for the former and on work organization and occupational medicine for the latter.

The role of post-loss anxiety in the development of depressive symptoms and complicated grief symptoms: a longitudinal SEM study.

BACKGROUND: Though grief, anxiety, and depression often co-occur, existing evidence mostly focus on any two of them at a time. Our study examined the relationships among the three clusters of symptoms. METHODS: A Chinese community sample of 101 bereaved individuals participated at T1. We utilized Bayesian Structural Equation Modelling (BSEM) to conduct cross-lagged analyses on three-wave panel data (T1 at one-month post-loss, T2 at four-months, and T3 at seven-months). RESULTS: BSEM findings confirmed the presence of distinctive developmental paths for complicated grief (CG), anxiety, and depressive symptoms. Three simplex models showed that anxiety, CG symptoms, and depressive symptoms maintained high consistency. In cross-lagged models, anxiety at T1 was a significant predictor of depressive symptoms (standardized estimate B=0.386*) and CG symptoms (standardized estimate B=0.300*) at T2. The remaining positive directions (0.338*, 0.256*) in the final model suggest the important role of anxiety at early bereavement, while at a later stage, T2 CG contributed to depressive symptoms at T3 (0.356*). LIMITATIONS: In addition to attrition, the overall sample size was limited. Data were based on self-report. Future research with repeated measures and Bayesian informative priors would be more useful to establish relational patterns of symptoms. CONCLUSIONS: In our models, the reduction in anxiety symptoms contributed to the development of depressive and CG symptoms, and these results should be replicated. Theories of mechanisms underlying post-loss anxiety can be explored as a potential means of reducing later symptoms.

A Bayesian Structural Equation Modeling Factor Analysis of the UCLA Posttraumatic Stress Disorder Reaction Index for DSM-5 in a Polyvictimized Sample of Adolescents.

The revised criteria for posttraumatic stress disorder (PTSD) in the fifth edition of the Diagnostic and Statistical Manual necessitated the development of new screening tools for youth, one of the most widely used of which is the UCLA Posttraumatic Stress Disorder Reaction Index for DSM-5 (RI-5). Thus far, the few studies that have investigated the RI-5's factor structure have supported a four-factor model. However, to date this research has been limited to youth with histories of exposure to single-event traumatic stressors, a significant limitation as evidence suggests many trauma-exposed youth report exposure to multiple types of traumatic stressors, or polyvictimization. It is imperative to determine the generalizability of previous factor models to specific populations which they are purported to represent. We investigated whether the RI-5's four-factor model replicated in a sample of 455 polyvictimized justice-involved adolescents. Initial confirmatory factor analysis demonstrated that the four-factor model did not converge. Therefore, we utilized Bayesian Structural Equations Modeling (BSEM) to determine why the previously proposed factor structure did not converge. The BSEM model suggested that the global factor structure was acceptable and did not require addition or subtraction of any factor or cross-factor loadings. However, small and moderate residual covariances resulted in model misspecification, suggesting there may be additional associations not captured by the current DSM-5 model for polyvictimized youth. Future work should continue examining the RI-5's factor structure in order to better understand whether the current results are unique and how measurements assessing DSM-5 PTSD symptom criteria perform in diverse trauma-exposed youth populations.

How Do Spelling, Handwriting Speed, and Handwriting Quality Develop During Primary School? Cross-Classified Growth Curve Analysis of Children's Writing Development.

Aim: Longitudinal studies are rare in the field of writing research, and little is known about the concurrent development of the two transcription skills: spelling and handwriting. This study was designed to provide a comprehensive picture of the development and the longitudinal relations between spelling, handwriting speed, and handwriting quality at the word level. Method: Over a period of 3 years (coh1: Grades 2-4; coh2: Grades 3-5), 117 French-speaking children were assessed on a single-word dictation task. At each testing time, measures of spelling accuracy, handwriting speed, and handwriting quality were collected on 40 words. Words varied in both orthographic and graphic complexity, making it possible to investigate the influence of these levels of complexity on transcription abilities. Results: Linear growth analyses using cross-classified Bayesian structural equation modeling (CC-BSEM) revealed that spelling and speed continued to improve until Grade 5, while handwriting quality reached an early plateau in Grade 2. In the younger cohort, graphic complexity had a significant influence on the pace of development of handwriting speed and on spelling and handwriting quality performance in Grade 2. In the older cohort, a positive relation between spelling and speed and a negative relation between handwriting speed and handwriting quality were found, indicating that fast handwriting is associated with high spelling ability and that fast handwriting is detrimental to handwriting quality. By providing a better understanding of writing development, this study yields innovative findings not only regarding the development of transcription skills but also regarding how spelling, handwriting speed, and handwriting quality can influence each other's performance throughout primary school.

Bayesian and Maximum-Likelihood Modeling and Higher-Level Scores of Interpersonal Problems With Circumplex Structure.

Difficulties in interpersonal behavior are often measured by the circumplex-based Inventory of Interpersonal Problems. Its eight scales can be represented by a three-factor structure with two circumplex factors, Dominance and Love, and a general problem factor, Distress. Bayesian confirmatory factor analysis is well-suited to evaluate the higher-level structure of interpersonal problems because circumplex loading priors allow for data-driven adjustments and a more flexible investigation of the ideal circumplex pattern than conventional maximum likelihood confirmatory factor analysis. Using a non-clinical sample from an online questionnaire study (N = 822), we replicated the three-factor structure of the IIP by maximum likelihood and Bayesian confirmatory factor analysis and found great proximity of the Bayesian loadings to perfect circumplexity. We found additional support for the validity of the three-factor model of the IIP by including external criteria-Agreeableness, Extraversion, and Neuroticism from the Big Five and subclinical grandiose narcissism-in the analysis. We also investigated higher-level scores for Dominance, Love, and Distress using traditional regression factor scores and weighted sum scores. We found excellent reliability (with R tt ≥ 0.90) for Dominance, Love, and Distress for the two scoring methods. We found high congruence of the higher-level scores with the underlying factors and good circumplex properties of the scoring models. The correlational pattern with the external measures was in line with theoretical expectations and similar to the results from the factor analysis. We encourage the use of Bayesian modeling when dealing with circumplex structure and recommend the use of higher-level scores for interpersonal problems as parsimonious, reliable, and valid measures.

A Psychometric Review and Conceptual Replication Study of the Five Facets Mindfulness Questionnaire Latent Structure.

The Five Facets Mindfulness Questionnaire (FFMQ) is a popular tool in mindfulness research. However, its psychometric qualities and its replicability have caused controversy. This study carried out a psychometric review and a conceptual replication of the FFMQ latent structure. The review showed that previous validation studies of the FFMQ used nonoptimal methods. In addition, this conceptual replication study tested the structure of the FFMQ using frequentist and Bayesian techniques. The original structure did not provide a good fit with both techniques, while the proposed alternative provided mixed results. We also found systematic fit improvements in both techniques when the Observe facet was excluded and method factors were included. With these findings, we conclude that the conceptual replication of the FFMQ's structure failed. Alternatively, we propose a new provisional FFMQ model with a set of recommendations regarding its application. Future research proposals on improving techniques and models toward mindfulness assessment are also presented and discussed.

The Role of Optimism and Psychosocial Factors in Athletes Recovery From ACL Injury: A Longitudinal Study.

Despite a growing interest into the role of psychosocial factors during the recovery period following sports injuries, there remains a paucity of longitudinal studies examining the indirect relationships between psychosocial factors, psychological responses, and recovery outcomes. The purpose of this study was to construct and test a conceptual model which examined the indirect relationships between optimism, psychosocial factors, rehabilitation adherence, and perceived knee function up to 12 months post anterior cruciate ligament (ACL) surgery. A prospective, longitudinal, and repeated measures design was employed, wherein 81 injured athletes (M age 26.89, SD = 7.52) completed measures of optimism, psychosocial factors, rehabilitation adherence, and perceived knee function on seven occasions (pre-surgery to 1 year post-surgery). Bayesian structural equation modeling evaluated the hypothesized indirect relationships proposed within the conceptual model. The main findings from this study was empirical support for a time-ordered, conceptual model which demonstrated that pre-surgery optimism had a significant overall indirect effect on perceived knee function at 12 months post-surgery (sum of indirect; αß = 0.08, post. SD = 0.05, CI [0.01, 0.04]), as well as a specific indirect effect through secondary appraisal at 1 month post-surgery, efficacy at 2 months post-surgery, and rehabilitation adherence at 6 months post-surgery (αß = 0.03, post. SD = 0.03, CI [0.00, 0.10]). Collectively, this study provides support for a number of previously hypothesized, but not empirically examined, indirect relationships between optimism, psychosocial factors and recovery outcomes. In doing so, we provide a conceptual model which has the potential to help guide individualized treatment recommendations, as well as identify individuals at risk of compromised recovery outcomes following ACL surgery.

Structural Equation Modeling of Vocabulary Size and Depth Using Conventional and Bayesian Methods.

In classifications of vocabulary knowledge, vocabulary size and depth have often been separately conceptualized (Schmitt, 2014). Although size and depth are known to be substantially correlated, it is not clear whether they are a single construct or two separate components of vocabulary knowledge (Yanagisawa and Webb, 2020). This issue has not been addressed extensively in the literature and can be better examined using structural equation modeling (SEM), with measurement error modeled separately from the construct of interest. The current study reports on conventional and Bayesian SEM approaches (e.g., Muthén and Asparouhov, 2012) to examine the factor structure of the size and depth of second language vocabulary knowledge of Japanese adult learners of English. A total of 255 participants took five vocabulary tests. One test was designed to measure vocabulary size in terms of the number of words known, while the remaining four were designed to measure vocabulary depth in terms of word association, polysemy, and collocation. All tests used a multiple-choice format. The size test was divided into three subtests according to word frequency. Results from conventional and Bayesian SEM show that a correlated two-factor model of size and depth with three and four indicators, respectively, fit better than a single-factor model of size and depth. In the two-factor model, vocabulary size and depth were strongly correlated (r = 0.945 for conventional SEM and 0.943 for Bayesian SEM with cross-loadings), but they were distinct. The implications of these findings are discussed.

Prior Sensitivity in Bayesian Structural Equation Modeling for Sparse Factor Loading Structures.

Bayesian structural equation modeling (BSEM) is a flexible tool for the exploration and estimation of sparse factor loading structures; that is, most cross-loading entries are zero and only a few important cross-loadings are nonzero. The current investigation was focused on the BSEM with small-variance normal distribution priors (BSEM-N) for both variable selection and model estimation. The prior sensitivity in BSEM-N was explored in factor analysis models with sparse loading structures through a simulation study (Study 1) and an empirical example (Study 2). Study 1 examined the prior sensitivity in BSEM-N based on the model fit, population model recovery, true and false positive rates, and parameter estimation. Seven shrinkage priors on cross-loadings and five noninformative/vague priors on other model parameters were examined. Study 2 provided a real data example to illustrate the impact of various priors on model fit and parameter selection and estimation. Results indicated that when the 95% credible intervals of shrinkage priors barely covered the population cross-loading values, it resulted in the best balance between true and false positives. If the goal is to perform variable selection, a sparse cross-loading structure is required, preferably with a minimal number of nontrivial cross-loadings and relatively high primary loading values. To improve parameter estimates, a relatively large prior variance is preferred. When cross-loadings are relatively large, BSEM-N with zero-mean priors is not recommended for the estimation of cross-loadings and factor correlations.

The Role of Self-Control and Motivation on Exhaustion in Youth Athletes: A Longitudinal Perspective.

The depletion of self-control competencies has been explained by an external shift in motivation, and recent research has emphasized that controlled types of motivation and self-control competencies are positively associated with exhaustion in youth athletes. Using the self-determination theory (SDT) and self-control theories, this study examined associations between athletes' motivation, self-control competencies, and exhaustion experiences throughout a competitive season. A total of 321 winter sport youth athletes (173 males, 98 females, and 50 unknown gender; aged 16 to 20 years, M = 17.98, SD = 0.89) participated in this 10-week longitudinal study, including three time points. Using Bayesian structural equation modeling, associations between athletes' reported level of motivation regulations, self-control, and exhaustion throughout their competitive season were examined in two mediation models. Constructs were associated in a conceptual and consistent manner. Simple mediation models showed credible indirect and direct effects of motivation on exhaustion via self-control within amotivation, and intrinsic, integrated, identified, and external regulation analyses. These credible effects were not replicated in the focused mediation model, when controlling for self-control and exhaustion autoregressive effects. However, direction of effects in both models was consistent and congruent. Findings consistently supported the interplay between motivation and exhaustion via self-control in youth athletes over an important competition period of the year. Autonomous and controlled motivation interacted with self-control and, respectively, predicted perceived exhaustion negatively and positively. Thus, autonomous self-control motives are important in preventing negative sport participation development over time. However, simple and focused mediation models showed different results, suggesting a necessity for accurate considerations of analytical methods chosen to investigate longitudinal mediation. Specifically, future studies need to carefully consider the time interval between measurement time points when investigating changes in dynamic psychological constructs, and include autoregressive longitudinal effects in order to predict change in levels of the outcome over time.

Psychometric Evaluation of the Overexcitability Questionnaire-Two Applying Bayesian Structural Equation Modeling (BSEM) and Multiple-Group BSEM-Based Alignment with Approximate Measurement Invariance.

The Overexcitability Questionnaire-Two (OEQ-II) measures the degree and nature of overexcitability, which assists in determining the developmental potential of an individual according to Dabrowski's Theory of Positive Disintegration. Previous validation studies using frequentist confirmatory factor analysis, which postulates exact parameter constraints, led to model rejection and a long series of model modifications. Bayesian structural equation modeling (BSEM) allows the application of zero-mean, small-variance priors for cross-loadings, residual covariances, and differences in measurement parameters across groups, better reflecting substantive theory and leading to better model fit and less overestimation of factor correlations. Our BSEM analysis with a sample of 516 students in higher education yields positive results regarding the factorial validity of the OEQ-II. Likewise, applying BSEM-based alignment with approximate measurement invariance, the absence of non-invariant factor loadings and intercepts across gender is supportive of the psychometric quality of the OEQ-II. Compared to males, females scored significantly higher on emotional and sensual overexcitability, and significantly lower on psychomotor overexcitability.