What to do Without a Control Group: You have to go latent, but not all latents are equal

The One-Group Pretest-Posttest Design, where the same group of people is measured before and after some event, can be fraught with statistical problems and issues with causal inference. Still, these designs are common from political science to developmental neuropsychology to economics. In cases with cognitive data, it has long been known that a second test, with no treatment or an ineffective manipulation between testings, leads to increased scores at time 2 without an increase in the underlying latent ability. We investigate several analytic approaches involving both manifest and latent variable modeling to see which methods are able to accurately model manifest score changes with no latent change. Using data from 600 schoolchildren given an intelligence test twice, with no intervention between, we show using manifest test scores, either directly or through univariate latent change score analysis, falsely leads one to believe an underlying increase has occurred. Latent change score models on latent data also show a spurious significant effect on the underlying latent ability. Multigroup Confirmatory Factor Analysis only shows the correct answer when measurement invariance is tested, imposed (if viable), and the means of both time points are tested constricting time 2 to zero. Longitudinal structural equation modeling with measurement invariance correctly shows no change at the latent level when measurement invariance is tested, imposed, and model fit tested. When dealing with the One-Group Pretest-Posttest Design, analyses must occur at the latent level, measurement invariance tested, and change parameters explicitly tested. Otherwise, one may see change where none exists.

The longitudinal association of eating behaviour and ADHD symptoms in school age children: a follow-up study in the RHEA cohort

Previous evidence suggests a link between attention deficit hyperactivity disorder (ADHD) symptoms and disordered eating behaviours; however, the direction of the causal association remains unclear. Building on our previous research, we aimed to examine the longitudinal association between eating behaviours at 4 years, ADHD symptoms at 6 years of age, and the role of body mass index (BMI). We included children from the RHEA mother–child cohort in Greece, followed up at 4 and 6 years (n = 926). Parents completed the Children’s Eating Behaviour Questionnaire (CEBQ) to assess children’s eating behaviour at 4 years and the ADHD Test (ADHDT) and Child Behaviour Checklist for ages 6–18 (CBCL/6–18) to evaluate ADHD symptoms at 4 and 6 years, respectively, as well as measures of BMI. Longitudinal structural equation modeling (SEM) was carried out to evaluate the associations of all variables between 4 and 6 years. Food responsiveness at 4 years was positively associated with hyperactivity at age 6, whereas emotional overeating was negatively associated with hyperactivity. There was no evidence of an association between eating behaviours of preschoolers and BMI at 6 years, or BMI at 4 years and later ADHD symptoms and vice versa. Findings suggest that food responsiveness is an early marker of ADHD symptoms at 6 years of age. In contrast to our hypothesis there was no significant association between ADHD at age 4 and BMI at age 6.

The Symbiotic Bond of Income Equality and Organizational Equilibrium

The corporate sustainability literature postulates that companies are social entities that constantly interact with the society in which they are located. Although this idea is generally accepted, one persistent research gap in this field relates to testing this connection through quantitative empirical studies. In this study, we shed light on the bidirectional relationship between income inequality and organizational equilibrium (i.e., balance in the employment relationship). From data on 2525 companies covering a nine-year period and using longitudinal structural equation modeling, findings demonstrate that equity in the distribution of resources among people in a society positively influences equity in the distribution of resources between employer and employees, and vice versa. A symbiotic union of mutual benefit between society and business is, therefore, developed over time. Theoretical and practical implications of our findings are presented.

Cognitive reserve and working memory in cognitive performance of adults with subjective cognitive complaints: longitudinal structural equation modeling

ABSTRACTObjective:To study the influence of cognitive reserve (CR) on cognitive performance of individuals with subjective cognitive complaints (SCCs) within a period of 36 months.Design:We used a general linear model repeated measures procedure to analyze the differences in performance between three assessments. We used a longitudinal structural equation modeling to analyze the relationship between CR and cognitive performance at baseline and at two follow-up assessments.Setting:Participants with SCCs were recruited and assessed in primary care health centers.Participants:A total of 212 participants older than 50 years with SCCs.Measurements:Cognitive reserve data were collected with an ad hoc questionnaire administered to the subjects in an interview. General cognitive performance (GCP), episodic memory (EM), and working memory (WM) have been evaluated. The Mini-Mental State Examination and the total score of Spanish version of the Cambridge Cognitive Examination evaluated the GCP. Episodic memory was assessed with the Spanish version of the California Verbal Learning. Working memory was evaluated by the counting span task and the listening span task.Results:The satisfactory fit of the proposed model confirmed the direct effects of CR on WM and GCP at baseline, as well as indirect effects on EM and WM at first and second follow-up. Indirect effects of CR on other cognitive constructs via WM were observed over time.Conclusion:The proposed model is useful for measuring the influence of CR on cognitive performance over time. Cognitive response acquired throughout life may influence cognitive performance in old age and prevent cognitive deterioration, thus increasing processing resources via WM.

Differential effects of internalizing behaviors on academic functioning for girls versus boys: An analysis of developmental cascades from elementary to high school

Youth's academic and emotional functioning are closely related, yet little is known about the timing and direction of relationships involving internalizing problems, which are characterized by over control of emotions, anxiety, and depression as well as multiple aspects of academic achievement. This study addresses these gaps using data from the Study of Early Child Care and Youth Development (N = 1,048) to examine the processes by which problems in one domain of functioning lead to problems in another, known as a “cascade effect.” Results of longitudinal structural equation modeling indicate (a) a direct and indirect negative cascade effect from girls’ internalizing problems to their school achievement in high school, (b) a positive contemporaneous association of 9th grade boys’ internalizing problems with their cognitive achievement; and (c) ways in which demographic characteristics and adolescent social and maturational processes account for variation in functioning yet do not alter the processes by which the emotional and academic functioning interact. Results are discussed with regard to identifiying adolescents’ internalizing problems, gender differences in the effects of internalizing problems on academic functioning, timing of evidence-based interventions, and implications for mental health promotion among girls.

Longitudinal Structural Equation Modeling in Lifespan Developmental Analyses

Longitudinal structural equation modeling (LSEM) is used to answer lifespan relevant questions such as (a) what is the effect of one variable on change in and other, (b) what is the average trajectory or growth rate of some psychological variable, and (c) what variability is there in average trajectories and what predicts this variability. The first of these questions is often answered by a LSEM called an autoregressive cross-lagged (ACL) model. The other two questions are most typically answered by an LSEM called a latent growth curve (LGC). These models can be applied to a few time waves (measured over several years) or to many time waves (such as present in diary studies) and can be altered, expanded, or even integrated. However, decisions on what model to use must be driven by the research question. The right tool for the job is not always the most complex. And, more importantly, the right tool must be matched to the best possible research design. Sometimes in lifespan research the right tool is LSEM. However, researchers should prioritize research design as well as careful specification of the processes and mechanisms they are interested in rather than simply choosing the most complicated LSEM they can find.