A straightforward approach for coping with unreliability of person means when parsing within-person and between-person effects in longitudinal studies

Daily sampling frequency and sampling duration affect reliability of person-level estimates of physical activity outcomes: Optimizing Ecological Momentary Assessment studies of physical activities

Studies on the interrelationship between physical activity (PA) behaviors and EMA-assessed constructs should use measures with high reliability of both the EMA-assessed constructs and the time-matched accelerometry-assessed PA behavior. The aim of this paper is to evaluate how the reliability of accelerometry-assessed PA outcomes is affected by different EMA sampling schemes. Emulating relevant sampling schemes in EMA studies, multiple random samples of real-world accelerometer data (measured via activPAL worn for ∼7 days) were drawn that varied in the number of daily samples (3, 5, and 7 daily samples) and in the duration of each sample (5 min, 60 min, and 120 min), totaling 9 sampling schemes. The reliability of the resulting PA outcomes was estimated by correlating weekly aggregates of the sampled data with the true parameter values (weekly aggregates of all data). A total of 4231 days were analyzed from 619 participants (mean age 45 ± 16 years; 73.3 % female; 72.7 % Non-Hispanic White). At the lowest sampling duration (5 min), none of the sampling schemes reached the threshold for acceptable reliability (reliabilities ranged from 0.20 to 0.67). Using 120 min sample duration resulted in reliable person-level PA estimates (ranges 0.77 to 0.97) except for the time spent in sedentary behavior (rel = 0.68), and for minimum (rel = 0.66), and maximum (rel = 0.63) PA intensity. These three PA outcomes consistently yielded lower levels of reliability across all sampling schemes. Holding constant the total time covered in a day, sampling schemes that used more frequent samples with shorter duration resulted in greater reliability compared to sampling schemes that used less frequent samples with longer duration. Overall, the results are consistent with sampling theory - reliability increased as more time was covered. However, our results also suggested interactive effects of reliability based on sampling frequency, duration, and PA outcome. Researchers should be aware that the reliability of accelerometer-derived PA outcomes can vary depending on the sampling design of EMA studies.

Correcting for Sampling Error in between-Cluster Effects: An Empirical Bayes Cluster-Mean Approach with Finite Population Corrections

With clustered data, such as where students are nested within schools or employees are nested within organizations, it is often of interest to estimate and compare associations among variables separately for each level. While researchers routinely estimate between-cluster effects using the sample cluster means of a predictor, previous research has shown that such practice leads to biased estimates of coefficients at the between level, and recent research has recommended the use of latent cluster means with the multilevel structural equation modeling framework. However, the latent cluster mean approach may not always be the best choice as it (a) relies on the assumption that the population cluster sizes are close to infinite, (b) requires a relatively large number of clusters, and (c) is currently only implemented in specialized software such as Mplus. In this paper, we show how using empirical Bayes estimates of the cluster means can also lead to consistent estimates of between-level coefficients, and illustrate how the empirical Bayes estimate can incorporate finite population corrections when information on population cluster sizes is available. Through a series of Monte Carlo simulation studies, we show that the empirical Bayes cluster-mean approach performs similarly to the latent cluster mean approach for estimating the between-cluster coefficients in most conditions when the infinite-population assumption holds, and applying the finite population correction provides reasonable point and interval estimates when the population is finite. The performance of EBM can be further improved with restricted maximum likelihood estimation and likelihood-based confidence intervals. We also provide an R function that implements the empirical Bayes cluster-mean approach, and illustrate it using data from the classic High School and Beyond Study.

A trait-like propensity to experience internalizing symptoms is associated with problem alcohol involvement across adulthood, but not adolescence

There are stable between-person differences in an internalizing "trait," or the propensity to experience symptoms of internalizing disorders, such as social anxiety, generalized anxiety disorder, and depression. Trait internalizing may serve as a marker of heightened risk for problem alcohol outcomes (such as heavier drinking, binge drinking, or alcohol dependence). However, prior research on the association between internalizing symptoms and alcohol outcomes has been largely mixed in adolescence, with more consistent support for an association during adulthood. It may be that trait internalizing is only associated with problem alcohol outcomes in adulthood, after individuals have gained experience with alcohol. Some evidence suggested that these effects may be stronger for women than men. We used data from a community sample (n = 790) interviewed during adolescence (ages 14-16) and again at ages 21, 24, 27, 30, 33, and 39. Using generalized estimating equations, we tested the association between trait internalizing and alcohol outcomes during both adolescence and adulthood, and tested whether adult trait internalizing mediated the association between adolescent trait internalizing and adult alcohol outcomes. Trait internalizing in adulthood (but not adolescence) was associated with more frequent alcohol use, binge drinking and symptoms of alcohol use disorders, and mediated the effects of adolescent trait internalizing on alcohol outcomes. We observed no moderation by gender or change in these associations over time. Understanding the developmental pathways of trait internalizing may provide further insights into preventing the emergence of problem alcohol use behavior during adulthood. (PsycInfo Database Record (c) 2020 APA, all rights reserved).