Exploration of the MCMC Wald test with linear regression

Recently, Asparouhov and Muthén Structural Equation Modeling: A Multidisciplinary Journal, 28, 1-14, (2021a, 2021b) proposed a variant of the Wald test that uses Markov chain Monte Carlo machinery to generate a chi-square test statistic for frequentist inference. Because the test's composition does not rely on analytic expressions for sampling variation and covariation, it potentially provides a way to get honest significance tests in cases where the likelihood-based test statistic's assumptions break down (e.g., in small samples). The goal of this study is to use simulation to compare the new MCM Wald test to its maximum likelihood counterparts, with respect to both their type I error rate and power. Our simulation examined the test statistics across different levels of sample size, effect size, and degrees of freedom (test complexity). An additional goal was to assess the robustness of the MCMC Wald test with nonnormal data. The simulation results uniformly demonstrated that the MCMC Wald test was superior to the maximum likelihood test statistic, especially with small samples (e.g., sample sizes less than 150) and complex models (e.g., models with five or more predictors). This conclusion held for nonnormal data as well. Lastly, we provide a brief application to a real data example.

Daily vitality fluctuations in older adults with depressive symptoms: A multilevel location-scale model

BACKGROUND

Examining the daily experiences of older adults with depression facilitates the development and application of personalized effective treatments for them. In previous clinical research on depression, traditional mean-based approaches have mainly been employed. However, the within-person residual variance as a random effect provides greater insight into the heterogeneity of daily experiences among geriatric samples.

OBJECTIVE

This study aimed to examine the relationship between depression and daily vitality in older adults. Specifically, it focused on the mean and residual variance of daily vitality measured by the Ecological Momentary Assessment (EMA).

METHODS

Data from 64 older adults aged 65 years or more, who participated in community welfare centers or retirees' associations, were used. Daily vitality was examined using EMA surveys for seven consecutive days (four random surveys per day). The data were analyzed using a location-scale model.

RESULTS

The intraclass correlation computed from the empty model for the EMA data was 0.488, indicating significant variances in daily vitality across time between individuals. Older adults with higher levels of depressive symptoms showed low mean levels of daily vitality and a large log-residual variance of daily vitality.

CONCLUSIONS

The findings from the current study suggest that individuals experiencing depression not only exhibit low vitality in their daily lives but also struggle to maintain stable levels of vitality in their lives. These insights could contribute to the facilitation and advancement of personalized interventions tailored for older adults.

Alternative covariance structures in mixed-effects models: Addressing intra- and inter-individual heterogeneity

Mixed-effects models for repeated measures and longitudinal data include random coefficients that are unique to the individual, and thus permit subject-specific growth trajectories, as well as direct study of how the coefficients of a growth function vary as a function of covariates. Although applications of these models often assume homogeneity of the within-subject residual variance that characterizes within-person variation after accounting for systematic change and the variances of the random coefficients of a growth model that quantify individual differences in aspects of change, alternative covariance structures can be considered. These include allowing for serial correlations between the within-subject residuals to account for dependencies in data that remain after fitting a particular growth model or specifying the within-subject residual variance to be a function of covariates or a random subject effect to address between-subject heterogeneity due to unmeasured influences. Further, the variances of the random coefficients can be functions of covariates to relax the assumption that these variances are constant across subjects and to allow for the study of determinants of these sources of variation. In this paper, we consider combinations of these structures that permit flexibility in how mixed-effects models are specified to understand within- and between-subject variation in repeated measures and longitudinal data. Data from three learning studies are analyzed using these different specifications of mixed-effects models.

Intraindividual variability in sleep among athletes: A systematic review of definitions, operationalizations, and key correlates

Via systematic review with narrative synthesis of findings, we aimed to document the ways by which researchers have defined, operationalized, and examined sleep variability among athletes. We identified studies in which scholars examined intraperson variability in sleep among athletes via a search of six databases (Web of Science, Embase, Medline, PsycINFO, CINHAL Plus, and ProQuest Dissertations and Theses Global) using a protocol that included keywords for the target outcome (sleep*), population (athlet* OR sport*), and outcome operationalization (variability OR variation OR "standard deviation" OR fluctuate OR fluctuation OR stability OR instability OR reactivity OR IIV OR intraindividual). We complemented this primary search with citation searching of eligible articles. Assessments of study quality captured eight core elements, namely aims/hypotheses, sample size justification, sample representativeness, number of days sleep assessed, measures of sleep and its correlates, missing data, and inferences and conclusions. From a total of 1209 potentially relevant papers, we identified 16 studies as meeting our eligibility criteria. Concept definitions of variability were notably absent from this work and where available were vague. Quantitative deviations from one's typical level of target sleep metrics reflected the essence by which all but one of the research teams operationalized sleep variability. We assessed the overall quality of empirical work as moderate in nature. We propose a working definition of sleep variability that can inform knowledge generation on the temporal, day-to-day dynamics of sleep functioning that is required for personalized interventions for optimizing sleep health.

Workers' emotional exhaustion and mental well-being over the COVID-19 pandemic: a Dynamic Structural Equation Modeling (DSEM) approach

The COVID-19 pandemic has presented significant challenges to the workforce, particularly concerning emotional and mental well-being. Given the prolonged periods of work-related stress, unexpected organizational changes, and uncertainties about work faced during the pandemic, it becomes imperative to study occupational health constructs under a dynamic methodological perspective, to understand their stable and unstable characteristics better. In this study, drawing on the Dynamic Structural Equation Modeling (DSEM) framework, we used a combination of multilevel AR(1) models, Residual-DSEM (RDSEM), multilevel bivariate VAR(1) models, and multilevel location-scale models to investigate the autoregression, trend, and (residual) cross-lagged relationships between emotional exhaustion (EmEx) and mental well-being (MWB) over the COVID-19 pandemic. Data were collected weekly on 533 workers from Germany (91.18%) and Italy (8.82%) who completed a self-reported battery (total number of observations = 3,946). Consistent with our hypotheses, results were as follows: (a) regarding autoregression, the autoregressive component for both EmEx and MWB was positive and significant, as well as it was their associated between-level variability; (b) regarding trend, over time EmEx significantly increased, while MWB significantly declined, furthermore both changes had a significant between-level variability; (c) regarding the longitudinal bivariate (cross-lagged) relationships, EmEx and MWB negatively and significantly affected each other from week to week, furthermore both cross-lagged relationships showed to have significant between-level variance. Overall, our study pointed attention to the vicious cycle between EmEx and MWB, even after controlling for their autoregressive component and trend, and supported the utility of DSEM in occupational health psychology studies.

Testing for intersectional measurement invariance with the alignment method: Evaluation of the 8-item patient health questionnaire

OBJECTIVE

To demonstrate the use of the alignment method to evaluate whether surveys function similarly (i.e., have evidence of measurement invariance) across culturally diverse intersectional groups. Intersectionality theory recognizes the interconnected nature of social categories such as race, gender, ethnicity, and socioeconomic status.

DATA SOURCES

A total of 30,215 American adult's responses to the eight-item Patient Health Questionnaire depression assessment scale (PHQ-8) from the 2019 National Health Interview Survey (NHIS).

STUDY DESIGN

Using the alignment method, we examined the measurement invariance (equivalence) of the PHQ-8 depression assessment scale across 16 intersectional subgroups defined at the intersection of age (under 52, 52 and older), gender (male, female), race (Black, non-Black), and education (no bachelor's degree, bachelor's degree).

PRINCIPAL FINDINGS

Overall, 24% of the factor loadings and 5% of the item intercepts showed evidence of differential functioning across one or more of the intersectional groups. These levels fall beneath the benchmark of 25% suggested for determining measurement invariance with the alignment method.

CONCLUSIONS

The results of the alignment study suggest that the PHQ-8 functions similarly across the intersectional groups examined, despite some evidence of different factor loadings and item intercepts in some groups (i.e., noninvariance). By examining measurement invariance through an intersectional lens, researchers can investigate how a person's multiple identities and social positions possibly contribute to their response behavior on an assessment scale.

Stressor reflections, sleep, and psychological well-being: A pre-registered experimental test of self-distanced versus self-immersed reflections

Evidence supports the effectiveness of cuing people to analyse negative autobiographical experiences from self-distanced rather than self-immersed perspectives. However, the evidence on which this expectation resides is limited largely to static snapshots of mean levels of cognitive and emotional factors. Via a pre-registered, randomised controlled trial (N = 257), we examined the differential effectiveness of self-distanced relative to self-immersed reflections on mean levels and within-person variability of sleep duration and quality as well as psychological well-being over a 5-day working week. Except for sleep quality, we found that reflecting from a psychologically distanced perspective, overall, was no more effective for mean levels and within-person variability of sleep duration, well-being, and stress-related factors than when the current self is fully immersed in the experiential reality of the event. We consider several substantive and methodological considerations (e.g., dosage, salience of stressor event) that require interrogation in future research via experimental and longitudinal observational methods.

Associations of Wellbeing Levels, Changes, and Within-Person Variability With Late-Life All-Cause Mortality Across 12 Years: Contrasting Hedonic vs. Eudaimonic Wellbeing Among Very Old Adults

Advanced old age has been characterized as a biologically highly vulnerable life phase. Biological, morbidity-, and cognitive impairment-related factors play an important role as mortality predictors among very old adults. However, it is largely unknown whether previous findings confirming the role of different wellbeing domains for mortality translate to survival among the oldest-old individuals. Moreover, the distinction established in the wellbeing literature between hedonic and eudaimonic wellbeing as well as the consideration of within-person variability of potentially relevant mortality predictors has not sufficiently been addressed in prior mortality research. In this study, we examined a broad set of hedonic and eudaimonic wellbeing indicators, including their levels, their changes, as well as their within-person variability, as predictors of all-cause mortality in a sample of very old individuals. We used data from the LateLine study, a 7-year longitudinal study based on a sample of n = 124 individuals who were living alone and who were aged 87–97 years (M = 90.6, SD = 2.9) at baseline. Study participants provided up to 16 measurement occasions (mean number of measurement occasions per individual = 5.50, SD = 4.79) between 2009 and 2016. Dates of death were available for 118 individuals (95.2%) who had deceased between 2009 and 2021. We ran longitudinal multilevel structural equation models and specified between-person level differences, within-person long-term linear change trends, as well as the “detrended” within-person variability in three indicators of hedonic (i.e., life satisfaction and positive and negative affect) and four indicators of eudaimonic wellbeing (i.e., purpose in life, autonomy, environmental mastery, and self-acceptance) as all-cause mortality predictors. Controlling for age, gender, education, and physical condition and testing our sets of hedonic and eudaimonic indictors separately in terms of their mortality impact, solely one eudaimonic wellbeing indicator, namely, autonomy, showed significant effects on survival. Surprisingly, autonomy appeared “paradoxically” related with mortality, with high individual levels and intraindividual highly stable perceptions of autonomy being associated with a shorter residual lifetime. Thus, it seems plausible that accepting dependency and changing perceptions of autonomy over time in accordance with objectively remaining capabilities might become adaptive for survival in very old age.

Catching Up on Multilevel Modeling

This review focuses on the use of multilevel models in psychology and other social sciences. We target readers who are catching up on current best practices and sources of controversy in the specification of multilevel models. We first describe common use cases for clustered, longitudinal, and cross-classified designs, as well as their combinations. Using examples from both clustered and longitudinal designs, we then address issues of centering for observed predictor variables: its use in creating interpretable fixed and random effects of predictors, its relationship to endogeneity problems (correlations between predictors and model error terms), and its translation into multivariate multilevel models (using latent-centering within multilevel structural equation models). Finally, we describe novel extensions—mixed-effects location–scale models—designed for predicting differential amounts of variability.

Between-person and within-person associations of sleep and working-memory in the everyday lives of old and very old adults: initial level, learning, and variability

STUDY OBJECTIVES

Sleep duration affects various aspects of cognitive performance, such as working-memory and learning, among children and adults. However, it remains open, whether similar or even stronger associations exist in old and very old age when changes in sleep and cognitive decrements are common.

METHODS

Using repeated daily-life assessments from a sample of 121 young-old (66-69 years old) and 39 old-old adults (84-90 years old), we assessed links between sleep duration and different aspects of working-memory (initial level, practice-related learning, and residualized variability) between and within persons. Participants reported their sleep durations every morning and performed a numerical working-memory updating task six times a day for seven consecutive days.

RESULTS

Both people who slept longer and those who slept shorter than the sample average showed lower initial performance levels, but a stronger increase of WM over time (i.e. larger learning effects), relative to people with average sleep. Sleep duration did not predict performance variability. Within-person associations were found for people sleeping relatively little on average: For them, working-memory performance was lower on days with shorter than average sleep, yet higher on days with longer than average sleep. Except for lower initial levels of working-memory in old-old adults, no differences between young-old and old-old adults were observed.

CONCLUSION

We conclude that sufficient sleep remains important for working-memory performance in older adults and that it is relevant to include different aspects of working-memory performance, because effects differed for initial performance and learning.

Neuroticism and emotional risk during the COVID-19 pandemic

Large-scale health crises, such as the COVID-19 pandemic, may evoke negative affective responses, which are linked to psychological maladjustment and psychopathology. Here, we shed light on the role of the personality trait neuroticism in predicting who experiences negative affective responses. In a large-scale experience-sampling study (N = 1,609; 38,120 momentary reports), we showed that individuals high in neuroticism experienced more negative affect and higher affective variability in their daily lives. Individuals high in neuroticism also (a) paid more attention to COVID-19-related information and worried more about the consequences of the pandemic (crisis preoccupation), and (b) experienced more negative affect during this preoccupation (affective reactivity). These findings offer new insights into the consequences and dynamics of neuroticism in extreme environmental contexts.

Neuroticism and emotional risk during the COVID-19 pandemic

Large-scale health crises, such as the COVID-19 pandemic, may evoke negative affective responses, which are linked to psychological maladjustment and psychopathology. Here, we shed light on the role of the personality trait neuroticism in predicting who experiences negative affective responses. In a large-scale experience-sampling study (N = 1,609; 38,120 momentary reports), we showed that individuals high in neuroticism experienced more negative affect and higher affective variability in their daily lives. Individuals high in neuroticism also (a) paid more attention to COVID-19-related information and worried more about the consequences of the pandemic (crisis preoccupation), and (b) experienced more negative affect during this preoccupation (affective reactivity). These findings offer new insights into the consequences and dynamics of neuroticism in extreme environmental contexts.