Experts provide an alternative source of information to classical data collection methods such as surveys. They can provide additional insight into problems, supplement existing data, or provide insights when classical data collection is troublesome. In this paper, we explore the (dis)similarities between expert judgments and data collected by traditional data collection methods regarding the development of posttraumatic stress symptoms (PTSSs) in children with burn injuries. By means of an elicitation procedure, the experts’ domain expertise is formalized and represented in the (...) form of probability distributions. The method is used to obtain beliefs from 14 experts, including nurses and psychologists. Those beliefs are contrasted with questionnaire data collected on the same issue. The individual and aggregated expert judgments are contrasted with the questionnaire data by means of Kullback–Leibler divergences. The aggregated judgments of the group that mainly includes psychologists resemble the questionnaire data more than almost all of the individual expert judgments. (shrink)

The objective of this study was to examine the association between resilience and trajectories of college students’ negative and positive affect during the COVID-19 pandemic. A total of 391 college students recruited from China completed a daily online negative and positive affect scale for 1 week, and their resilience was also measured. Profiles of brief trajectories of negative and positive affect over time were identified using the latent growth mixture model, and the effect of resilience on these trajectories (...) was further explored. Two latent profiles of negative affect were found: a constant high negative affect profile and a slowly decreasing low negative affect profile, while three latent profiles of positive affect were identified: a slowly increasing high positive affect profile, a rapidly decreasing medium positive affect profile, and a constant medium positive affect profile. The optimism dimension of resilience predicted the membership in the various profiles significantly, whereas the prediction of tenacity and strength dimensions of resilience was not significant. Activities that promote resilience, especially optimism, should be included to improve the daily emotions of college students during COVID-19. (shrink)

Based on the data of four periods of CLHLS, the latent variable growth model was applied to 2344 older adults who completed four follow-up surveys, to study the trajectory of leisure activities and cognitive ability and explore the relationship between leisure activities and cognitive ability of older adults. The results showed that: leisure activities and cognitive ability of older adults showed a non-linear downward trend; leisure activities significantly and positively predicted the cognitive ability of older adults at every (...) time point; the initial level of leisure activity positively predicted the initial level of cognitive ability but negatively predicted the rate of cognitive decline; In addition, cognitive activities had a greater effect on cognitive ability than non-exercise physical activities; the rate of decline of leisure activities also significantly and positively predicted the rate of decline of cognitive ability; cross-lagged regression analysis further suggested the overall positive predictive effect of leisure activity on cognitive ability; overall, education level had a significant contribution to cognitive ability, and the higher the education level, the slower the decline of cognitive ability; and smoking could promote cognitive ability in older adults and no significant effect was found between alcohol drinking and cognitive ability. Accordingly, the government should encourage older adults to do more leisure activities, especially the cognitive activity, to effectively prevent cognitive decline. (shrink)

This study examines whether and how the qualities of newcomers’ interpersonal relationships [i.e., leader-member exchange (LMX) and coworker exchange (CWX)] relate to their initial performance and how changes in the qualities of these relationships relate to the changes in performance. To test a latent growth model, we collected data from 230 newcomers at six time points over a 6-week period. The results showed that LMX quality is positively related to initial newcomer performance; however, changes in LMX quality are (...) not statistically significantly related to changes in newcomer performance. In contrast, an increase in CWX quality is positively related to newcomer performance improvement, but the initial quality of CWX does not predict newcomer performance. Furthermore, newcomers’ psychological entitlement moderates the relationship between LMX quality and newcomer performance; newcomers’ conscientiousness moderates the relationship between increases in CWX quality and improvements in newcomer performance. The findings increase our understanding of the newcomer exchange relationship-performance link over time and suggest that future newcomer socialization research explore the initial level of and the changes in these relationships simultaneously. (shrink)

The purpose of this study is to assess the relationship between involvement in three aspects of congregational life and spiritual growth. In addition, an effort is made to see if spiritual growth may, in turn, affect health. A latent variable model was developed to test the following hypotheses: individuals who attend worship services more often, attend Bible study and prayer group meetings more frequently, and individuals who receive more spiritual support from fellow church members will be more (...) likely to report they have experienced spiritual growth; people who experience more spiritual growth will be more likely to derive a deeper sense of meaning in life; and individuals who have developed a deeper sense of meaning in life will enjoy better health. Data from the U.S. Congregational Life Survey suggests that spiritual support has the stronger relationship with spiritual growth than either worship service attendance or involvement in formal church groups. The findings further reveal that greater spiritual growth is associated with a deeper sense of meaning in life and meaning, in turn, is associated with better health. (shrink)

Growth mixture models are regularly applied in the behavioral and social sciences to identify unknown heterogeneous subpopulations that follow distinct developmental trajectories. Marcoulides and Trinchera recently proposed a mixture modeling approach that examines the presence of multiple latent classes by algorithmically grouping or clustering individuals who follow the same estimated growth trajectory based on an evaluation of individual case residuals. The purpose of this article was to conduct a simulation study that examines the performance of this new (...) approach for determining the number of classes in growth mixture models. The performance of the approach to correctly identify the number of classes is examined under a variety of longitudinal data design conditions. The findings demonstrated that the new approach was a very dependable indicator of classes across all the design conditions considered. (shrink)

This study draws the attention towards the importance of reducing weight discrimination against children for their educational success, as an issue of social justice. We investigate the consequences of early-onset obesity identifying the mediating mechanisms in the relationship between childhood obesity and academic achievement. To do so, we employ the Early Childhood Longitudinal Study-Kindergarten Cohort in the US and apply a parallel process latent growth model with a combination of quasi-experiments and econometrics. The results of this study suggest (...) that teachers may serve as a significant source of weight bias, especially for girls. (shrink)

ObjectiveFatigue after burns is often attributed to the hyperinflammatory and hypermetabolic response, while it may be best understood from a bio-psychological perspective, also involving the neuro-endocrine system. This longitudinal multi-center study examined the course of fatigue up to 18 months postburn. The contribution of bio-psychological factors, including burn severity, pain, and acute PTSD symptoms, to the course and persistence of fatigue was studied in a multifactorial model.MethodsParticipants were 247 adult burn survivors. Fatigue symptoms were assessed with the Multidimensional Fatigue Inventory (...) during the acute phase and subsequently at 3, 6, 12, and 18 months postburn, and were compared to population norms. Age, gender, burn severity, acute PTSD symptoms and pain were assessed as potential predictors of fatigue over time in a latent growth model.ResultsAt 18 months postburn, 46% of the burn survivors reported fatigue, including 18% with severe fatigue. In the acute phase, higher levels of fatigue were related to multiple surgeries, presence of pain, and higher levels of acute PTSD symptoms. Fatigue gradually decreased over time with minor individual differences in rate of decrease. At 18 months, pain and acute PTSD symptoms remained significant predictors of fatigue levels.ConclusionsProtracted fatigue after burns was found in almost one out of five burn survivors and was associated with both pain and acute PTSD symptoms. Early detection of PTSD symptoms and early psychological interventions aimed at reducing PTSD symptoms and pain may be warranted to reduce later fatigue symptoms. (shrink)

Based on Vallerand’s dualistic model of passion, this study theorizes and empirically examines the temporal dynamics of two types of entrepreneurial passion in female entrepreneurs, harmonious entrepreneurial passion and obsessive entrepreneurial passion, and examines the mechanisms by which entrepreneurial effort0 and fear of failure influence the temporal dynamics of entrepreneurial passion. Using data collected from a three-wave, lagged survey of female entrepreneurs, we employed Mplus to build a latent growth model for entrepreneurial passion and built a cross-lag model (...) of the relationship between entrepreneurial passion, entrepreneurial effort, and fear of failure. We found that female entrepreneurs’ HmEP and ObEP present different temporal dynamics. Furthermore, the temporal dynamics of HmEP are achieved through changes in entrepreneurial effort, whereas the temporal dynamics of ObEP are achieved through changes in current entrepreneurial effort and fear of failure in the next stage. Therefore, due to traditional gender stereotypes and varying motivations to engage in entrepreneurship, the two entrepreneurial passions have different dynamic evolution processes. Our results underscore the importance of effort and fear of failure in stimulating the dynamics of female entrepreneurial passion. (shrink)

Members of the transforming growth factor beta (TGFβ) family are pleiotropic cytokines with key roles in tissue morphogenesis and growth. TGFβ1, TGFβ2 and TGFβ3 are abundant in mammalian reproductive tissues, where development and cyclic remodelling continue in post‐natal and adult life. Potential roles for TGFβ have been identified in gonad and secondary sex organ development, spermatogenesis and ovarian function, immunoregulation of pregnancy, embryo implantation and placental development. However, better tools must now be employed to map more precisely essential (...) functions and the regulatory networks governing their activity. Gene ablation and transgenic models are expected to provide novel insights into distinct physiological activities for each TGFβ isoform in normal reproductive function and reproductive pathologies. It is also necessary to consider the mechanisms controlling TGFβ activation from latent precursor forms, and receptor and binding protein expression. Smad intracellular signalling circuitry and modulation by environmental stimuli through cross‐talk with other signal transduction pathways will further constrain TGFβ action. This review examines existing evidence for TGFβ1, TGFβ2 and TGFβ3 regulation of male and female reproductive biology, and highlights prospects for future research. BioEssays 24:904–914, 2002. © 2002 Wiley Periodicals, Inc. (shrink)

Organizational operations have been modified by using the rise of digital innovation, which has increased consumer interaction, accelerated efficiency, and stimulated overall growth. But obstacles like converting organizational adoption charges and a quickly evolving era would possibly make it more difficult to generalize effects across of different sectors and ancient intervals. To overcome these constraints, a thorough examination of the impact of digital innovation on organizational growth is carried out in this study. This study investigates the connection among (...) Digital infrastructure (DI), Digital Innovation practices (DIP), Adoption of advanced digital technologies (ADT), Leadership support (LS), Organizational growth (OG), and Employee digital capabilities (EDS) utilizing Structural Equation Modeling (SEM) and CFA test. SEM is used to evaluate the causal pathways between constructs and the connections between latent variables and their indicators. CFA is a method used to validate the dimension model by examining the relationships between observed indicators and their underlying constructs. A systematic questionnaire with a Likert scale rating was used to collect data from 600 populations. The measurement model assessed the validity and reliability of latent constructs, while the structural model analyzed the relationship between constructs based on the proposed hypotheses. The structural model revealed that DI, LS, and ADT are positively connected to the DTP, and OG, between digital innovations on organizational growth. (β = 0.58,0.54,0.60 and 0.62,p < 0.05), providing well support for hypotheses 1, 2, 4, and 5. The SEM and CFA confirm the robustness of these relationships. The findings underscore the critical role of digital infrastructure and leadership in driving effective digital practices and fostering growth. (shrink)

This article deals with optimal control applied to vaccination and treatment strategies for an SIRS epidemic model with logistic growth and delay. The delay is incorporated into the model in order to modeled the latent period or incubation period. The existence for the optimal control pair is also proved. Pontryagin’s maximum principle with delay is used to characterize these optimal controls. The optimality system is derived and then solved numerically using an algorithm based on the forward and backward (...) difference approximation. (shrink)

Language development is not completed when children enter primary school. As the comprehension of connectives (such as although, despite) is important for understanding and producing academic texts and, thus, relevant for school success, we investigated its development and influential factors across primary school age on the basis of a newly developed and validated test instrument. Drawing on a German sample of N = 627 children (57.6 % language minority learners) in Grades 2 to 4, results of growth curve models (...) showed students’ initial level of the comprehension of connectives to be negatively related to its growth rate. Additional analyses revealed this association to be due mainly to parental socioeconomic status (SES) rather than children’s language background. Particularly, parental SES and children’s receptive grammar impacted initial level as well as growth rate of connective comprehension. Our results indicate the need for early and continuous sensitization of children for the register of academic language especially in the group of children from low socioeconomic background. (shrink)

Different types of tasks exist, including tasks for research purposes or exams assessing knowledge. According to expectation-value theory, tests are related to different levels of effort and importance within a test taker. Test-taking effort and importance in students decreased over the course of high-stakes tests or low-stakes-tests in research on test-taking motivation. However, whether test-order changes affect effort, importance, and response processes of education students have seldomly been experimentally examined. We aimed to examine changes in effort and importance resulting from (...) variations in test battery order and their relations to response processes. We employed an experimental design assessing N = 320 education students’ test-taking effort and importance three times as well as their performance on cognitive ability tasks and a mock exam. Further relevant covariates were assessed once such as expectancies, test anxiety, and concentration. We randomly varied the order of the cognitive ability test and mock exam. The assumption of intraindividual changes in education students’ effort and importance over the course of test taking was tested by one latent growth curve that separated data for each condition. In contrast to previous studies, responses and test response times were included in diffusion models for examining education students’ response processes within the test-taking context. The results indicated intraindividual changes in education students’ effort or importance depending on test order but similar mock-exam response processes. In particular effort did not decrease, when the cognitive ability test came first and the mock exam subsequently but significantly decreased, when the mock exam came first and the cognitive ability test subsequently. Diffusion modeling suggested differences in response processes on cognitive ability tasks suggesting higher motivational levels when the cognitive ability test came first than vice versa. The response processes on the mock exam tasks did not relate to condition. (shrink)

With the advent of Complex dynamic systems theory in the field of second language question, the need for suitable CDST compatible methods for the investigation of temporal change in L2 affective variables has been felt more than before. One of the innovative methods for this purpose is latent growth curve modeling, which has recently drawn the attention of SLA scholars. However, the application of this method is still a burgeoning demand in SLA. In response to this demand, the (...) present study provides a review of the conceptualization, significance, and technical features of the implementation of LGCM. In doing so, this review suggests a number of practices via which LGCM has been introduced in SLA. Additionally, some practical implications are provided for SLA researchers to enhance their literacy of LGCM. Finally, future research suggestions for the progress of the use of this method in SLA are discussed. (shrink)

The focus of this study was on adolescent mental health. More specifically, the relationship between strength-based parenting (SBP) and subjective wellbeing (SWB) during adolescence, as assessed by a sample of adolescents, was examined at three time points over 14 months (N = 202, Mage = 12.97, SDage =.91, 48% female). SBP was positively related to life satisfaction and positive affect at each of the three time points, and was negatively related to negative affect. SBP and SWB both declined significantly over (...) time. When examining the causal relationships between SBP and SWB, two different statistical models were applied: latent growth-curve models (LGM) and random-intercept cross-lagged panel models (RI-CLPM). The LGM revealed a strong positive relationship between changes in SBP and SWB. Specifically, this model showed that SBP at one time point predicted adolescent SWB at future time points. However, when the more stringent statistical test was completed through RI-CLPMs, no cross-lagged paths reached significance. Thus, while parenting is a significant predictor of wellbeing for pre-teens and teens in real time, it is not predictive of wellbeing at future time points. Parents, thus, cannot assume that their current levels of SBP are ‘banked’ by their children to support future wellbeing. Instead, SBP needs to be an ongoing, contemporary parenting practice. Furthermore, the fact that perceptions of SBP decline in this age bracket suggest that SBP interventions may be helpful in supporting adolescent mental health. (shrink)

Mediation analysis relies on an untestable assumption of the no omitted confounders, which posits that an omitted variable that confounds the relationships between the antecedent, mediator, and outcome variables cannot exist. One common model in alcohol addiction studies is a nonrandomized latent growth curve mediation model, where the antecedent variable is not randomized, the two covarying mediators are latent intercept and slope modeling longitudinal effect of the repeated measures mediator, and an outcome variable that measures alcohol use. (...) An important gap in the literature is lack of sensitivity analysis techniques to assess the effect of the violation of the no omitted confounder assumption in a nonrandomized LGCMM. We extend a sensitivity analysis technique, termed correlated augmented mediation sensitivity analysis, to a nonrandomized LGCMM. We address several unresolved issues in conducting CAMSA for the nonrandomized LGCMM and present: analytical results showing how confounder correlations model a confounding bias, algorithms to address admissible values for confounder correlations, accessible R code within an SEM framework to conduct our proposed sensitivity analysis, and an empirical example. We conclude that conducting sensitivity analysis to ascertain robustness of the mediation analysis is critical. (shrink)

This study aimed to investigate the longitudinal associations between children’s sleep duration and problems, behavioral adjustment [externalizing behaviors and internalizing behaviors ], and maternal depressive symptoms in preschoolers over a period of 3 years. For this purpose, latent growth modeling was conducted using 2012 to 2014 data from the National Panel Study on Korean Children, while controlling for family contextual factors and child temperament. First, children who slept longer at four were concurrently associated with lower levels of EB, (...) while more SPs were associated with higher levels of EB and IB, concurrently. Second, greater decreases in SPs were associated with greater decline in EB and IB. Higher levels of MDS at four were associated with higher levels of child EB, IB, and SPs, concurrently. However, no longitudinal associations were found between the rates of change in MDS and children’s sleep and adjustment. Finally, the magnitude of the associations among the variables was greater overall in the SPs models than in the SD models. These findings suggest that addressing sleep problems, rather than sleep duration, seem to be more important in predicting and preventing young children’s adjustment problems and also that more attention should be paid to MDS during preschool years as much as during the postpartum period for better child adjustment outcomes. (shrink)

The present longitudinal study used the traditional cross-lagged panel model and autoregressive latent trajectory model with structured residuals to examine the relationships between perceived interparental conflict, negative thinking, and depression symptoms in Chinese children. Changes in these three variables over time were also examined, as well as the trait and state aspects of the relationships between them. A sample of 516 third-grade primary students completed questionnaires about IPC, NT, and depression three times over a period of 1 year, at (...) 6-month intervals. The CLPM findings indicated that, assuming that stability of each variable across time was controlled, Chinese children’s perception of IPC significantly affected their level of depression through the mediating path of NT. After taking trait factors into account, among all the significant autoregressive and cross-lagged paths originally found in the CLPM, only one third remained significant in the ALT-SR model. More specifically, the ALT-SR model, revealed a driving effect of children’s NT on perceived IPC and depression symptoms. The CLPM model although elucidated the interplay among three variables, the ALT-SR model showed little evidence of their interrelated growth across time. Taken together, these results indicate that children’s perceived IPC in the long term are a stable trait, with few state-level fluctuations, and is not a significant within-person predictor of subsequent children’s internalization problems. These perceptions appear to contribute more to children’s general psychological tendency than do changes over time. The research is the first to test the reciprocal relationships between Chinese children’s perceived IPC, NT, and depression symptoms. The findings demonstrate that previously proposed theories about the bidirectional relation between IPC and children’s social adjustment, to some extent, may reflect a correlation at a trait level. Put another way, it is IPC’s central tendency to be sensitive in the long term as a stable trait that is associated with their children’s general tendency to show well adjustment. The study contributes to our understanding of that extend previous results and have implications for complementary theoretical and practical interventions. The complementary techniques of CLPM and ALT-SR models offer different insights into children’s internalization problems, and hold promise for supporting the building of more comprehensive children’s developmental theories that acknowledge the interconnectedness of different domains of mental health. (shrink)

Currently, the coronavirus disease 2019 pandemic experienced by the international community has increased the usage frequency of borderless, highly personalized social media platforms of all age groups. Analyzing and modeling texts sent through social media online can reveal the characteristics of the psychological dynamic state and living conditions of social media users during the pandemic more extensively and comprehensively. This study selects the Sina Weibo platform, which is highly popular in China and analyzes the subjective well-being of Weibo users during (...) the COVID-19 pandemic in combination with the machine learning classification algorithm. The study first invokes the SWB classification model to classify the SWB level of original texts released by 1,322 Weibo active users during the COVID-19 pandemic and then combines the latent growth curve model and the latent growth mixture model to investigate the developmental trend and heterogeneity characteristics of the SWB of Weibo users after the COVID-19 outbreak. The results present a downward trend and then an upward trend of the SWB of Weibo users during the pandemic as a whole. There was a significant correlation between the initial state and the development rate of the SWB after the COVID-19 outbreak. LGMM results show that there were two heterogeneous classes of the SWB after the COVID-19 outbreak, and the development rate of the SWB of the two classes was significantly different. The larger class showed a slow growth, while the smaller class showed a rapid growth. Furthermore, the slope means across the two classes were significantly different. Therefore, the individuals with a higher growth rate of SWB exhibited stronger adaptability to the changes in their living environments. These results could help to formulate effective interventions on the mental health level of the public after the public health emergency outbreak. (shrink)

This study characterizes a large sample of adults with attention-deficit/hyperactivity disorder and healthy controls regarding their task performance and neurophysiology; cross-sectionally and longitudinally. Self-reported symptoms, behavioral measures, and event-related potentials from a classical cued Go/NoGo task were used to outline the symptom burden, executive function deficits and neurophysiological features, and the associations between these domains. The study participants were assessed five or three times over two years. We describe cross-sectional and longitudinal group differences, and associations between symptom burden, and behavioral (...) and event-related potential components variables by latent growth curve models, including random slopes and intercepts. The ADHD group showed increased reaction time variability, increased commission and omission errors, and attenuated cueP3, CNV, N2d, and P3d amplitudes. We observed a decrease in self-reported symptoms in the ADHD group over the two years. The behavioral measures did not change over time, whereas the cueP3, P3d, and N2d amplitude attenuated in both groups. There was no evidence for a robust association between symptom burden and behavioral or ERP measures. The changes in the ERP components with stable task performance, potentially indicate more efficient neuronal processing over the two years. Whether the lack of association between symptom burden and behavioral or ERP measures might be due to the low reliability of the ADHD assessment criteria, or the inappropriateness of the objective measures cannot be inferred. (shrink)

The present study contains an affect-based intervention intended to support exercise trainers in positively influencing their course participants’ affective responses to their exercise courses. We argue that positive affective responses are associated with habit formation, thereby being a promising approach for avoiding high drop-out rates in exercise courses. First, the present study aimed to investigate whether the intervention for exercise trainers could increase affective attitudes, and exercise instigation habit strength, and influence the development of weekly measured affective responses and automaticity (...) among adult participants of exercise courses. Second, it examined the relationship between the development of affective responses and exercise instigation habit strength. Ten exercise trainers of weekly sports and exercise courses at a German university received either an affect-based intervention or a control intervention. 132 of their course participants answered the Self-Report Habit Index for exercise instigation habit strength and items to measure affective attitude in the initial and final assessment. Moreover, they were assessed for a duration of 10 weeks during which, each time after attending the course, they reported their affective response to exercise as well as their automaticity in arriving at the decision to exercise. In the repeated measures ANOVA, there was a significant main effect of time for exercise instigation habit strength. Overall, habit strength was higher in the final than in the initial assessment. However, there were no significant differences between the two conditions in all study variables. In the latent growth curve model, the trajectory of the latent growth curve of valence was a significant predictor of the final exercise instigation habit strength. While the applied affect-based intervention was not successful in enhancing positive affective responses to exercise, the results indicate that positive affective responses may contribute to strengthening exercise instigation habits. Future studies should examine the effectiveness of interventions in long-term study designs. (shrink)

The aim of this article is to show how a tumor can modify energy substrates fluxes in the brain to support its own growth. To address this question we use a modeling approach to explain brain nutrient kinetics. In particular we set up a system of 17 equations for oxygen, lactate, glucose concentrations and cells number in the brain. We prove the existence and uniqueness of nonnegative solutions and give bounds on the solutions. We also provide numerical simulations.

IntroductionThe COVID-19 outbreak and related lockdowns brought substantial changes in people’s lives and led to concerns about possible increases of addictive behaviors at the initial stages of the pandemic. To examine these concerns, the aim of the present study was to assess longitudinal changes in addictive and problematic behaviors over time during the COVID-19 pandemic.MethodsThree waves of data collection took place in different stages of the COVID-19 outbreak in Hungary in a general population, from the first wave of lockdowns to (...) the second and third waves of restrictions. Latent growth curve models were calculated to assess the potential changes in addictive and problematic behaviors over time.ResultsLatent growth curve models showed that the sample varied in their initial scores, but there were no significant changes over time in any of the examined behaviors, except for compulsive sexual behavior disorder, which demonstrated a small but significant increase. However, the rate of this change was negligible. Overall, there were no noteworthy changes over time regarding any of the examined addictive and problematic behaviors.ConclusionContrary to initial concerns, no substantial changes over time were observed regarding the examined addictive behaviors during the COVID-19 pandemic and related lockdowns. These findings indicate that those who had no previous problem with these addictive behaviors, might have not developed a problem, and those who had problem with either of the behaviors previously, might have not experienced a significant increase in their symptoms. (shrink)

This study on the cambium of Pinus sylvestris L. examines the intrusive growth of fusiform cambial initials and its possible contribution to the tangential and radial expansions of the cambial cylinder. The location and extent of intrusive growth of the fusiform initials were determined by microscopic observations and by mathematical modeling. In order to meet the required circumferential expansion of the cambial cylinder, the fusiform initials grow in groups by means of a symplastic rather than intrusive growth, (...) leaving no room for the assumption that intrusive growth of the initials takes place between radial walls and has a direct role in the increase of the cambial circumference. Therefore, it is postulated that the fusiform initials grow intrusively between the tangential walls of the neighboring initials and their immediate derivatives and not between the radial walls of the adjacent initials as per common belief. (shrink)

Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

Lucio Baccaro and Jonas Pontusson make a significant contribution to comparative political economy with their approach to analyzing growth in advanced economies, which focuses on the demand side of the economy and distributive conflict. In contrast to Baccaro and Pontusson, however, we view their approach as reinforcing recent developments in varieties of capitalism rather than undermining them. We also believe that the type of modern macroeconomics used by Carlin and Soskice is better placed than their post-Keynesian framework to analyze (...) growth models, and that their approach is not inconsistent with it. Modern macroeconomic models incorporate, as they do not, a role for the state—including monetary and fiscal policy—and provide a coherent framework within which to analyze both the supply and demand sides of the economy; they also enable us to understand the interactions between economies and hence the role of growth models in global imbalances. (shrink)

Researchers routinely face the problem of inferring causal relationships from large amounts of data, sometimes involving hundreds of variables. Often, it is the causal relationships between "latent" (unmeasured) variables that are of primary interest. The problem is how causal relationships between unmeasured variables can be inferred from measured data. For example, naval manpower researchers have been asked to infer the causal relations among psychological traits such as job satisfaction and job challenge from a data base in which neither trait (...) is measured directly, but in which answers to interview questions are plausibly associated with each trait. By combining background knowledge with an algorithm that searches for causal structure among the unobserved variables, we have created a tool that can reliably extract useful causal information about latent variables from large data bases. In what follows we describe the class of causal models to which our.. (shrink)

Growth modelling is of interest to scientists in various disciplines. In our article, we will collect 17 models designed for growth modelling, appraise these models and contribute to the discussion of their applicability. The merit of the paper lies in studying the convergence properties of nonlinear regression in selected models. Our studies will be performed mainly concerning the quality of the obtained estimates, which are closely related to the intrinsic curvature of the model according to Bates (...) and Watts. This curvature determines the size of the linearization domains. Only if the initial solution is in this domain, then the convergence of the estimate in nonlinear regression is guaranteed. The primary goal is to design a methodology for selecting a growth model. We will demonstrate fruitfulness of our methodology on the weight measurements of 10 calves under 25 months of age from cowsheds in the village Záluží in the Czech Republic. Estimated parameters of growth curves, sizes of linearization domain, calculated residues and coefficients of determination indices will be the subject of discussion. (shrink)

Effective feature representation is the key to success of machine learning applications. Recently, many feature learning models have been proposed. Among these models, the Gaussian process latent variable model for nonlinear feature learning has received much attention because of its superior performance. However, most of the existing GPLVMs are mainly designed for classification and regression tasks, thus cannot be used in data clustering task. To address this issue and extend the application scope, this paper proposes a novel GPLVM for (...) clustering. Specifically, by combining GPLVM with the subspace clustering method, our C-GPLVM can obtain more representative latent variable for clustering. Moreover, it can directly predict the new samples by introducing a back constraint in the model, thus being more suitable for big data learning tasks such as analysis of chaotic time series and so on. In the experiment, we compare it with the related GPLVMs and clustering algorithms. The experimental results show that the proposed model not only inherits the feature learning ability of GPLVM but also has superior clustering accuracy. (shrink)

Cluster growth models are utilized for a wide range of scientific and engineering applications, including modeling epidemics and the dynamics of liquid propagation in porous media. Invasion percolation is a stochastic branching process in which a network of sites is getting occupied that leads to the formation of clusters. The occupation of sites is governed by their resistance distribution; the invasion annexes the sites with the least resistance. An iterative cluster growth model is considered for computing the expected (...) size and perimeter of the growing cluster. A necessary ingredient of the model is the description of the mean perimeter as the function of the cluster size. We propose such a relationship for the site square lattice. The proposed model exhibits the expected phase transition of percolation models, i.e., it diverges at the percolation threshold p c. We describe an application for the porosimetry percolation model. The calculations of the cluster growth model compare well with simulation results. (shrink)

PurposeThis study aimed to examine the long-term association between social activity, physical function decline and cognitive function, as well as verify the long-term mediating effect of physical function decline on the relationship between social activity and cognitive function.MethodsData from the Korean Longitudinal Study of Aging that was collected over 10 years was analyzed. The sample included 10,240 adults aged 45–93 years. Multivariate latent growth modeling was applied to verify the long-term effect of social activity and physical function on (...) cognitive function.ResultsThe results revealed that social activity had a positive impact on cognitive function and negative impact on physical function decline after controlling for age and education level. Additionally, physical function decline negatively influenced cognitive function. Finally, social activity indirectly affected cognitive function through physical function decline.ConclusionThe contribution of this study was to test the long-term effect social activity on physical and cognitive function. (shrink)

We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause, if such exists; (2) return information about the causal relations among the latent factors so identified. We prove the procedure is point-wise consistent assuming (a) the causal relations can be represented by a directed acyclic graph (DAG) satisfying the Markov Assumption and the Faithfulness Assumption; (b) unrecorded variables are not caused by (...) recorded variables; and (c) dependencies are linear. We compare the procedure with standard approaches over a variety of simulated structures and sample sizes, and illustrate its practical value with brief studies of social science data sets. Finally, we consider generalizations for non-linear systems. Keywords: latent variable models, causality, graphical models.. (shrink)

Bayesian approaches for estimating multilevel latent variable models can be beneficial in small samples. Prior distributions can be used to overcome small sample problems, for example, when priors that increase the accuracy of estimation are chosen. This article discusses two different but not mutually exclusive approaches for specifying priors. Both approaches aim at stabilizing estimators in such a way that the Mean Squared Error of the estimator of the between-group slope will be small. In the first approach, the MSE (...) is decreased by specifying a slightly informative prior for the group-level variance of the predictor variable, whereas in the second approach, the decrease is achieved directly by using a slightly informative prior for the slope. Mathematical and graphical inspections suggest that both approaches can be effective for reducing the MSE in small samples, thus rendering them attractive in these situations. The article also discusses how these approaches can be implemented in Mplus. (shrink)

In this paper, we analyse the simplest possible three-dimensional model of endogenous growth to account for the relationship between financial intermediation and economic growth. In our setting, households maximize an interim utility function and firms maximize profit. Households can save money only through banks which offer firms investment loans. We show that under very general assumptions, investments realized by firms depend not only on savings accumulated by banks but also on financial intermediation technology ϕ(θ). Using mathematical methods of (...) dynamical systems, we found stationary states of the system and study their stability. (shrink)

We consider the use of interventions for resolving a problem of unidentified statistical models. The leading examples are from latent variable modelling, an influential statistical tool in the social sciences. We first explain the problem of statistical identifiability and contrast it with the identifiability of causal models. We then draw a parallel between the latent variable models and Bayesian networks with hidden nodes. This allows us to clarify the use of interventions for dealing with unidentified statistical models. (...) We end by discussing the philosophical and methodological import of our result. (shrink)