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Statistical issues in the study of temporal data: daily experiences.

This article reviews statistical issues that arise in temporal data, particularly with respect to daily experience data. Issues related to nonindependence of observations, the nature of data structures, and claims of causality are considered. Through the analysis of data from a single subject, we illustrate concomitant time-series analysis, a general method of examining relationships between two or more series having 50 or more observations. We also discuss detection of and remedies for the problems of trend, cycles, and serial dependency that frequently plague temporal data, and present methods of combining the results of concomitant time series across subjects. Issues that arise in pooling cross-sectional and time-series data and statistical models for addressing these issues are considered for the case in which there are appreciably fewer than 50 observations and a moderate number of subjects. We discuss the possibility of using structural equation modeling to analyze data structures in which there are a large number (e.g., 200) of subjects, but relatively few time points, emphasizing the different causal status of synchronous and lagged effects and the types of models that can be specified for longitudinal data structures. Our conclusion highlights some of the issues raised by temporal data for statistical models, notably the important roles of substantive theory, the question being addressed, the properties of the data, and the assumptions underlying each technique in determining the optimal approach to statistical analysis.

Adaptation, Psychological

Alternative common factor models for multivariate biometric analyses.

In prior research we have shown how linear structural equation models and computer programs (e.g., LISREL) may be simply and directly used to provide alternatives for the traditional biometric twin design. We use structural equations and path models to define biometric group differences, we write traditional common-factor models in the same way, and then we take a detailed look at some alternative multivariate and biometric models. We contrast the biometric-factors covariance structure approach used by Loehlin and Vandenberg (1968), Martin and Eaves (1977), and others with the psychometric-factors approach used by McArdle et al. (1980) and others. We use the multivariate primary mental abilities data on monozygotic (MZ) and dizygotic (DZ) twins from Loehlin and Vandenberg (1968) to detail fundamental differences in model specification and results. We extend both multivariate biometric approaches using exploratory and confirmatory multiple-factor models. These comparisons show that each alternative multivariate methodology has useful features for empirical applications.

Humans

Personality as modifier of the life change-distress relationship. A longitudinal modelling approach.

We present a structural equation model of the way in which personality factors may modify the response to changes in life situation, based on two-wave panel data from a random sample of 296 Dutch adults. Three definitions of vulnerability were studied: high neuroticism (N), low self-esteem (SE), and an external locus of control (LC). The multigroup LISREL analysis led to the following conclusions: First, previous symptom level was strongly related to current symptom level. The strength of this relationship was independent of SE and LC but modified by N. Secondly, the impact of life situation changes on distress level was moderately strong and similar to what others have reported. Thirdly, a marked modifier effect was found for neuroticism; responsiveness significantly increased with N level. For SE and LC we observed reduced responsiveness among low vulnerability subjects, but the differences did not reach statistical significance. The implications of the findings are discussed.

Adult

Occupational stress, social support, and depression.

A model of occupational stress, social support, locus of control, and depression among family physicians was developed. Two hundred and ten family physicians were administered measures of occupational stress, social support, locus of control, and depression. The hypothesized model was evaluated using structural equation models (LISREL). Results indicate that occupational stress exerts a direct effect on depression. This relationship is moderated directly by family social and emotional support and indirectly by the influence of locus of control on family social support. Support from peers was not significantly related to depression. Findings suggest that individuals with a strong sense of personal control also possess beneficial support systems in the presence of stressful situations.

Age Factors

Antecedents and outcomes of work-family conflict: testing a model of the work-family interface.

A comprehensive model of the work-family interface was developed and tested. The proposed model extended prior research by explicitly distinguishing between work interfering with family and family interfering with work. This distinction allowed testing of hypotheses concerning the unique antecedents and outcomes of both forms of work-family conflict and a reciprocal relationship between them. The influence of gender, race, and job type on the generalizability of the model was also examined. Data were obtained through household interviews with a random sample of 631 individuals. The model was tested with structural equation modeling techniques. Results were strongly supportive. In addition, although the model was invariant across gender and race, there were differences across blue- and white-collar workers. Implications for future research on the work-family interface are discussed.

Adaptation, Psychological

Unraveling 'F' factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic aging.

BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the shared biological mechanisms underlying this multimorbidity remain poorly defined. This study aimed to establish an integrative clinical-genetic framework to elucidate the common frailty factor, the 'F' factor, that captures the systemic vulnerability linking cardiometabolic multimorbidity (CMM) and musculoskeletal aging. METHODS: Utilizing the prospective China Health and Retirement Longitudinal Study (CHARLS) cohort, we developed and validated novel Frailty-Integrated Indices for CMM risk prediction, evaluated with machine learning models interpreted via SHapley Additive exPlanations (SHAP). Independently, we applied genomic structural equation modeling (Genomic-SEM) to integrate genome-wide association data from six traits-coronary artery disease, type 2 diabetes, hypertension, bone mineral density, frailty, and telomere length-to model a shared latent genetic factor ('F' factor). This was followed by multivariate GWAS, fine-mapping, transcriptome-wide association study (TWAS), gene-based analysis, and functional annotation to prioritize causal genes, pathways, and cell types. RESULTS: Clinically, several Frailty-Integrated Indices significantly improved CMM risk prediction, with the optimal model achieving an AUC of 0.727. Genetically, we modeled a significant shared latent genetic factor ('F' factor), pinpointing novel risk loci and implicating key genes such as APOE and SLC22A3. These genes were enriched in pathways including cellular senescence and cholesterol metabolism and showed specific expression patterns in developmental brain stages and across multi-organ endothelial cells. CONCLUSION: Our findings provide converging evidence for Musculoskeletal‑Heart crosstalk of metabolic aging and inferred the 'F' factor as a genetic correlate of a transdiagnostic state, which links genetic predisposition to metabolic dysregulation, and systemic functional decline. This work provides a multi-level biological characterization of multimorbidity liability, informing early-risk detection and preventive strategies for complex aging-related comorbidities.

Humans

Replications of a dual failure model for boys' depressed mood.

A structural equation model for depressed mood was examined for three samples of boys (N = 317) from at-risk families. It was assumed that rejection by normal peers and academic failure were significant covariates for preadolescent boys' depressed mood. The model accounted for from 51% to 68% of the variance in the criterion construct. The confirmatory factor analyses showed an adequate fit of the measurement model to the data sets for each of the three samples. The hypothesized negative path coefficients from the good peer relations construct to the child depressed mood construct were significant for all three samples. The path from the academic skills construct to the child depressed mood construct, however, was highly variable and significant for only two of the samples. Multigroup comparisons were carried out to determine the degree to which the factor loadings and the structural relations between constructs were invariant across the three samples.

Achievement

A general multivariate approach to linear modeling in human genetics.

The general linear structural equation model is applied to problems in human genetics where there may be more than one measured phenotype per individual. A modeling convention, termed conditional associations, is developed to extend the general linear model so that it can handle the unique problems in human genetic models that arise from the pairing up of individuals or families under assortment between mates and the assortative placement of adoptees. Formulas are presented to generate expected covariance matrices for assortment or assortative placement on many variables simultaneously. It is demonstrated that all linear models in human genetics can be reduced in form to two fundamental equations. An algorithm is presented that will allow the application of these two equations to linear modeling in human genetics.

Adoption

Self-rated health and associated factors among men of different ages.

The connections of certain clinico-physiological indicators of health state, chronic diseases, felt symptoms, and psychic well-being with self-rated health were studied among men of different ages as a part of the more extensive research project Jyväskylä Studies on Functional Aging. Study population was selected by using systematic random sampling among men aged 31 to 35, 51 to 55 and 71 to 75 years in the city of Jyväskylä. Log-linear and logit models as well as regression and structural equation models within the framework of LISREL were used as methods of analysis. The associations between general self-rated health and the explanative variables were different in different age groups: In the youngest age group self-rated health was best explained by symptoms and index of physical fitness; among the middle-aged by symptoms and psychic well-being; and among the oldest by chronic diseases. The results suggest that self-rated health belongs to the important indicators of health, and more attention should be paid to it both in research and in medical practice.

Adult

Coupling of spectroscopy and nitrogen-oxygen isotopes unveils the mechanisms of dissolved organic matter and nitrate pollution in lakes within the agro-pastoral transition zone.

Lakes in arid and semi-arid regions are subjected to severe ecological stress, such as organic pollution, eutrophication, and salinization, due to climate change and human activities. This study investigates Chagannur Lake, a typical arid-region lake that is representative and ecologically sensitive in Northern China's agro-pastoral ecotone, to uncover its pollution characteristics and mechanisms. We employed fluorescence spectroscopy and stable isotope analysis to trace dissolved organic matter (DOM) and nitrate sources. The DOM composition was dominated by microbial metabolic byproducts and protein-like substances, suggesting that microbial processes are key to organic matter transformation. Source apportionment revealed that pollutants primarily originated from livestock and poultry manure (37.6 %), agricultural fertilizers (35.6 %), and soil erosion (24.7 %), with agricultural fertilizers contributing most significantly in the Gogstai River (63.3 %). A structural equation model (SEM) coupling spectral and mass spectrometric data revealed that microbial transformation significantly impairs the lake's self-purification capacity, thereby promoting pollutant accumulation (path coefficient = 0.91,*p < 0.05). Moreover, microbial processes link endogenous and exogenous pollution, a mechanism effectively traced by isotopic and fluorescence indices (path coefficient = 0.55, &#x204e;&#x204e;p < 0.01). These findings enhance the understanding of pollution sources and transformation mechanisms in arid-region lakes and offer foundational theoretical support for policymakers engaged in pollution control strategies.

Lakes

Characteristics of aggressors against women: testing a model using a national sample of college students.

Structural equation modeling was used to study the characteristics of college men (N = 2,652) who aggressed against women either sexually, nonsexually, or both. According to the model, hostile childhood experiences affect involvement in delinquency, leading to aggression through two paths: (a) hostile attitudes and personality, which result in coerciveness both in sexual and nonsexual interactions, and (b) sexual promiscuity, which, especially in interaction with hostility, produces sexual aggression. In addition, sexual and nonsexual coercion were hypothesized to share a common underlying factor. Although its development was guided by integrating previous theory and research, the initial model was refined in half of the sample and later replicated in the second half. Overall, it fitted the data very well in both halves and in a separate replication with a sample for whom data were available about sexual but not about nonsexual aggression.

Adolescent

Glymphatic dysfunction mediates inflammation-driven vascular burden and cognitive decline in cerebral small vessel disease.

BACKGROUND: Cerebral small vessel disease (CSVD) is increasingly recognized as a disorder involving microvascular dysfunction, impaired perivascular clearance, and inflammatory processes. However, how systemic inflammatory burden, neurovascular coupling (NVC), glymphatic MRI markers, vascular lesion burden, and cognition are interrelated remains unclear. MATERIALS AND METHODS: In this prospective study, 155 patients with CSVD and 70 healthy controls (HCs) underwent multimodal MRI. NVC was quantified using the cerebral blood flow/fractional amplitude of low-frequency fluctuations ratio. Glymphatic function was assessed via the diffusion tensor image analysis along the perivascular space (ALPS) index, choroid plexus volume (CPV), and perivascular space (PVS) fractions. Structural equation modeling (SEM) was employed to evaluate the direct and indirect effects of inflammatory markers on vascular burden and cognitive performance. RESULTS: Patients with CSVD exhibited significantly diminished NVC (specifically in the right median cingulate and left frontal gyri) and impaired glymphatic function (lower ALPS-index; higher CPV and PVS fractions) compared to HCs. SEM revealed that inflammatory biomarkers exerted both a direct effect on vascular burden and a substantial indirect effect (accounting for 66.3% of the total effect) mediated through two pathways: a single-mediation path via glymphatic function (42.8%) and a serial-mediation path via NVC and glymphatic function (23.5%). Increased vascular burden was significantly associated with poorer cognitive performance. CONCLUSION: Inflammation drives CSVD progression and cognitive decline primarily through the disruption of NVC and glymphatic clearance mechanisms. These findings highlight glymphatic dysfunction as a critical mediator of inflammation-related structural brain damage.

Humans

Methodological issues in adherence to cancer control regimens.

A six-factor model provides a heuristic framework for understanding adherence behavior: (1) effective provider communication; (2) rapport with provider; (3) client's beliefs and attitudes; (4) client's social climate and norms; (5) behavioral intentions; and (6) supports for and barriers to adherence. Four classes of methodological issues are discussed. Recruitment may be affected by the sociodemographics of the target population, biomedical variables, population size and location, and patient sources utilized. Interventions can be structured to maximize enrollment, participation and long-term retention, and adherence to the regimen promoted with behavioral methodology. Measurement of adherence optimally includes multiple measures at multiple time points, a well-defined focus and unit of adherence, well-constructed response options, and multiple sources of information. Sample size calculations and interpretation of clinical trial results are affected by adherence rates. Multivariate analytic techniques, such as structural equation modeling, make it possible to specify models depicting hypothesized structural relationships between different theoretical constructs and to evaluate the plausibility of these models.

Adaptation, Psychological

Multi-omics revealed the effects of rumen to blood path on early lactation performance in transition dairy cows.

BACKGROUND: The transition period is vitally important to the life cycle of dairy cows. However, the function of the microbiota during both pre- and post-partum and their relationship with ruminal, plasma, and milk metabolites still require systematic investigation. To address this, the 7 highest- and 7 lowest-performing animals among a cohort of 100 dairy cows were selected based on their postpartum energy-corrected milk yield. Rumen fluid and plasma samples were collected during both pre- and post-partum periods, whereas milk samples were obtained postpartum. Shotgun metagenomics of rumen contents in addition to metabolomics of rumen, plasma, and milk samples were performed to evaluate the associations between ruminal microbes and early lactation performance in transition dairy cows. RESULTS: Compared with prepartum cows, postpartum high-yield cows had greater concentrations of ruminal volatile fatty acids and plasma total bile acid. Moreover, plasma urea nitrogen and most amino acids, peptides, and their derivatives in plasma and milk were increased in postpartum high-yield cows, relative to postpartum low-yield cows. Metagenomic analysis revealed that the relative abundances of several species within the Prevotella, Succinimonas, Succinatimonas, and Methanosphaera increased, while other bacteria belong to Alistipes and Bacteroides, and archaeal Methanobrevibacter species decreased in postpartum cows, particularly in postpartum high-yield cows. Co-occurrence network and correlation analysis suggested that Prevotella and Succinatimonas were negatively correlated to Alistipes, Bacteroides, and Methanobrevibacter, potentially contributing to the nutritionally efficient phenotype of postpartum high-yield cows. A metabolic pathway analysis of our metagenomic data revealed that postpartum high-yield cows possessed more microbial genes involved in starch utilization and amino acid synthesis, while a wide range of microbial genes involved in cellulose utilization, acetogenesis, and amino acid degradation were found in prepartum cows with low-yield in postpartum. A structural equation model analysis showed that the increased relative abundances of Prevotella tf.2-5 and Succinatimonas CAG_777 were related to greater concentrations of plasma chenodeoxycholic acid glycine conjugate, milk 5-Methoxytryptophan, and energy-corrected milk yield. Finally, pan-genomic analysis confirmed that Alistipes, Bacteroides, and Methanobrevibacter possess genetic conservation of both hydrogenases and dehydrogenases, which may contribute to energy loss in the rumen via hydrogen dissipation. CONCLUSION: In summary, our findings provide a fundamental understanding of how microbiome-dependent mechanisms contribute to early lactation performance in dairy cows during the transition period. The increased abundance of Prevotella, Succinimonas, and Succinatimonas in postpartum cows suggest that they are important microbes during the transition period and may help in coping with metabolic challenges, while improving nutrient utilization efficiency during this period. Our study underscores the importance of the ruminal microbiome during the transition period and highlights the need for rumen-based nutritional intervention strategies to improve production efficiency in ruminants. Video Abstract.

Animals

Prenatal maternal stress and prematurity: a prospective study of socioeconomically disadvantaged women.

Developed and tested a biopsychosocial model of birthweight and gestational age at delivery using structural equation modeling procedures. The model tested the effects of medical risk and prenatal stress on these indicators of prematurity after controlling for whether a woman had ever given birth (parity). Subjects were 130 women of low socioeconomic status interviewed throughout pregnancy in conjunction with prenatal care visits to a public clinic. The majority of women were Latino or African-American. Half were interviewed in Spanish. Lower birthweight was predicted by earlier delivery and by prenatal stress. Earlier delivery was predicted by medical risk and by prenatal stress. Parity was not related to time of delivery or to birthweight. Implications of results for the development of biopsychosocial research on pregnancy and on stress are discussed.

Adolescent

Modeling age using cognitive, psychosocial and physiological variables: the Boston Normative Aging Study.

A structural equation model is computed for 36 variables from eight domains of data using 100 healthy male subjects whose age varies between 30 and 80 years. Chronological age is required to be an exogenous variable while cognitive function variables are required to be an ultimate endogenous or outcome set. The model suggests that the direct effect of age on cognition is substantially reduced when social, life style, physiological, and brain state variables are allowed to become intervening variables. The study also finds that there is an association between cognitive function and psychosocial measures relating to general psychiatric symptomatology and social support systems.

Adult

Robustness of a model of exercise.

A recent longitudinal study of exercise behavior was published in this journal. A structural equation model derived from the theory of reasoned action was evaluated and found to fit the data well. This paper presents further analysis of the data to determine the robustness of the results to modifications of the original model.

Computer Simulation

Structural modeling of mixed longitudinal and cross-sectional data.

In this paper we describe some mathematical and statistical models for dealing with changes over age. We concentrate specifically on the use of a structural equation modeling (SEM) approach (using computer programs like LISREL) to deal with issues of: (1) group differences in regression parameters, (2) differences in longitudinal and cross-sectional results, (3) differences due to longitudinal attrition, and (4) mixtures of these problems. To illustrate these ideas we use data from a previous study of hypertension and intellectual abilities (from Schultz, Elias, Robbins, Streeten, and Blakeman, 1986).

Adult