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General pedagogical knowledge (GPK) is regarded as a central component of the competence that teachers acquire during university teacher education. However, existing research on GPK typically uses only one or two measurement points to assess development and identify influencing factors. The present study draws on an annual survey of pre-service teachers' GPK over 5 measurement points during the course of university teacher education (i.e. over the standard five-year study period). Latent growth curve models were used to assess knowledge development and explore potential influences. Knowledge development was best described as an increasing trend that flattens out over time. While students' initial knowledge levels differed, their knowledge increase showed little interindividual variance. Initial knowledge level was related to the use of learning opportunities at the beginning of the study programme, but no significant association was identified between knowledge growth and increased learning opportunities over time. Moreover, initial knowledge level was predicted by the grade point average achieved in secondary school examinations but not by intrinsic motivation. Overall, the findings indicate that university teacher education effectively promotes GPK, with the entry phase being of particular significance. [ABSTRACT FROM AUTHOR]

Preferred retirement age (PRA) is one key dimension when studying retirement decision-making. However, little is known concerning how PRA develops over the late career years. This study used a person-centered approach to longitudinally investigate trajectories of PRA and how they differ in self-rated health, perceived work ability, and effort–reward imbalance (ERI) at baseline levels and over 6 years. The study used data from four waves (2010, 2012, 2014, and 2016) of the Swedish Longitudinal Occupational Survey of Health. The sample consisted of 1,510 individuals aged 50–55 in 2010, who answered to the questionnaire for those in paid work (including self-employment) at the baseline and at least one of the following waves. Results from the latent class growth curve modeling show both within- and between-person variability in PRA over the 6-year span. We found four distinct trajectories, which differed both at the baseline levels and in the patterns of change in PRA: "C1: normative, relatively stable PRA" (42% of all participants); "C2: considerably early, increasing PRA" (6% of the participants); "C3: late, relatively stable PRA" (4% of the participants); and "C4: early, increasing PRA" (49% of the participants). Participants revealed a clear preference for retirement before the age of 65. Trajectories comprising earlier PRA showed poorer self-rated health, poorer work ability, and higher levels of ERI at the baseline and over time. The findings reinforce the importance of healthy work environments that promote work ability and facilitate a balance between efforts and rewards for encouraging longer working lives. [ABSTRACT FROM AUTHOR]

Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ( n = 36 ) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was 2.1 % ± 2 % compared to 1.1 % ± 1 % ( p = 0.002 ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or 1.4 % ± 1 % ( p = 0.01 ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( p = 0.05 ) and PKD2 mutation ( p = 0.04 ) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate. [ABSTRACT FROM AUTHOR]

In this study, Nernst growth model equations are used to explain the anodic biofilm (ABF) modeling, linear sweep voltammetry (LSV) at various growth stages of biofilm, and polarization curve modeling for its electron generation behavior in a miniaturized single-chambered microbial fuel cell (SMFC). Kinetic constants of various growth model equations were determined using non-linear regression analysis. Maximum specific growth rate (μmax) at anodic surface is observed 0.016 h−1 at a glucose concentration of 12 g L−1, whereas retardation in μmax is observed 14 g L−1 or more in SMFC. LSV results showed maximum current density of 6720.56 mA m−2. Anode performance in SMFC is examined through polarization curve resulting maximum open-circuit voltage (OCV), minimum charge transfer loss, and ohmic loss for NWG (NiWO4 impregnated on rGO), NiWO4, rGO, and plain CC (carbon cloth) anode. These results demonstrate significant enhancement in performance of MFC to lead towards model-based process controlling for significant scale-up in future. [ABSTRACT FROM AUTHOR]

Statistical modeling with growth data is the most efficient way to get more objective results and also understand growth. Schnute growth model is a large-scale model that includes many nonlinear growth models, it offers optimum parameter estimates compared to other growth models, especially regardless of whether the growth curve has an asymptotic feature. In recent years, in the literature studies, there are approaches in the theoretical and applicational fields in which the equations are modified to make sense of growth equations. The purpose of modifying the equations is to convert growth parameters into meaningful parameters such as maximum value, A; rapid specific rate of growth and lag time A. In this study, it is demonstrated that by which mathematical operations the parameters of the Schnute growth model are converted to significant parameters and a new modified Schnute growth model is presented to the literature. [ABSTRACT FROM AUTHOR]

Penalized structural equation models (PSEM) is a new powerful estimation technique that can be used to tackle a variety of difficult structural estimation problems that can not be handled with previously developed methods. In this paper we describe the PSEM framework and illustrate the quality of the method with simulation studies. Maximum-likelihood and weighted least squares PSEM estimation is discussed for SEM models with continuous and categorical variables. We show that traditional EFA, multiple group alignment (MGA), and Bayesian SEM (BSEM) are examples of PSEM. The PSEM framework also extends standard SEM models with the possibility to structurally align various model parameters. Exploratory latent growth models, also referred to as Tuckerized curve models, can also be estimated in the PSEM framework and are illustrated here with simulation studies and an empirical example. [ABSTRACT FROM AUTHOR]

Latent class analysis (LCA) refers to techniques for identifying groups in data based on a parametric model. Examples include mixture models, LCA with ordinal indicators, and latent class growth analysis. Despite its popularity, there is limited guidance with respect to decisions that must be made when conducting and reporting LCA. Moreover, there is a lack of user-friendly open-source implementations. Based on contemporary academic discourse, this paper introduces recommendations for LCA which are summarized in the SMART-LCA checklist: Standards for More Accuracy in Reporting of different Types of Latent Class Analysis. The free open-source R-package package tidySEM implements the practices recommended here. It is easy for beginners to adopt thanks to user-friendly wrapper functions, and yet remains relevant for expert users as its models are integrated within the OpenMx structural equation modeling framework and remain fully customizable. The Appendices and tidySEM package vignettes include tutorial examples of common applications of LCA. [ABSTRACT FROM AUTHOR]

Epidemiological studies suggest that maternal diet quality during pregnancy may influence the risk of neurodevelopmental disorders in offspring. Here, we investigated associations between maternal intake of dietary fiber and attention-deficit/hyperactivity disorder (ADHD) symptoms in early childhood. We used longitudinal data of up to 21,852 mother-father-child trios (49.2% female offspring) from MoBa (the Norwegian Mother, Father, and Child Cohort Study). The relationships between maternal fiber intake during pregnancy and offspring ADHD symptoms at ages 3, 5, and 8 years were examined using 1) multivariate regression (overall levels of ADHD symptoms), 2) latent class analysis (subclasses of ADHD symptoms by sex at each age), and 3) latent growth curves (longitudinal change in offspring ADHD symptoms). Covariates were ADHD polygenic scores in child and parents, total energy intake and energy-adjusted sugar intake, parental ages at birth of the child, and sociodemographic factors. Higher maternal prenatal fiber intake was associated with lower offspring ADHD symptom scores at all ages (B age3 = −0.14 [95% CI, −0.18 to −0.10]; B age5 = −0.14 [95% CI, −0.19 to −0.09]; B age8 = −0.14 [95% CI, −0.20 to −0.09]). Of the derived low/middle/high subclasses of ADHD symptoms, fiber was associated with lower risk of belonging to the middle subclass for boys and girls and to the high subclass for girls only (middle: odds ratio boys 0.91 [95% CI, 0.86 to 0.97]/odds ratio girls 0.86 [95% CI, 0.81 to 0.91]; high: odds ratio girls 0.82 [95% CI, 0.72 to 0.94]). Maternal fiber intake and rate of change in child ADHD symptoms across ages were not associated. Low prenatal maternal fiber intake may increase symptom levels of ADHD in offspring during childhood, independently of genetic predisposition to ADHD, unhealthy dietary exposures, and sociodemographic factors. [ABSTRACT FROM AUTHOR]

In this study, twelve drugs used to treat Parkinson's disease were analyzed. To simplify calculations and data analysis, a computer-based computing technique along with the algorithm has been employed. The M-polynomial and their degree-based topological indices derived from the M-polynomial were calculated using MATLAB coding. Linear, quadratic, cubic, logarithmic, inverse, power, compound, s-curve, growth, and exponential regression model analyses were utilized to create QSPR models between the topological indices and eight the Physicochemical properties of the drugs to determine their effectiveness. Confidence intervals at a 95% level were computed for both the slope and intercept of the linear regression models. Also, based on the maximum $ R^{2} $ R 2 , optimal equations for estimating the Boiling point, Enthalpy of vaporization, Molar refractivity, Polarizability, and Molar volume using different indices have been determined, and linear, quadratic, and cubic equations have been specified. Calculated feature values are strongly correlated with actual values, indicating reliable predictive capabilities of the indices. For statistical analysis and to determine if there is a significant difference between the averages of the two groups, we used either an independent T-test or Welch's T-test. The results show that the p-value is less than 0.05, which indicates that the mean difference between the samples is statistically significant. [ABSTRACT FROM AUTHOR]

Introduction: Humanistic psychologists have conceptualized a tendency among humans to experience continual open‐ended psychological growth. This study aims to measure the rate at which one grows psychologically using a novel growth curve modeling approach that addresses previous limitations. We also examine the effects of nine potential contributors to growth identified from the literature. Method: Throughout the freshman year, 556 college students responded six times. Increments of growth were added up to create cumulative growth, which was then fit to a growth curve model to produce an estimate of the growth rate. The growth rate was then regressed on the Time 1 predictors to examine their unique effects. Results: Models fit well. Five predictors significantly predicted the growth rate after controlling for the average of other predictors. When all predictors were entered simultaneously, three predictors (hope, meaning, and personal growth initiative) showed significant unique effects. The growth rate predicted well‐being and satisfaction at Time 6. Conclusion: We successfully measured the rate of psychological growth and examined its antecedents. Follow‐up analyses suggested that the predictors not showing unique effects may indirectly predict growth rates via the proximal role of the three significant predictors, an idea that awaits future corroboration using within‐individual designs. [ABSTRACT FROM AUTHOR]

Today, adult individuals must be able to continuously learn and adapt to the rapid changes occurring in society. However, little is known about the individual characteristics, particularly personality traits, that make adults more likely to engage in learning activities. Moreover, few studies have longitudinally and objectively investigated the influence of personality on engagement in lifelong learning throughout working age. This study therefore used longitudinal data (15 years) to examine which personality traits predicted level and long-term changes in learning activities among 1329 Swedish adults aged 30–60. The results from growth curve modelling showed that over the follow-up period, novelty seeking and self-transcendence were both positively related to overall level of engagement in learning activities, although not to rate of change. Regarding specific activities, novelty seeking was related to higher levels of engagement in attending courses, taking on new education, and making occupational changes, while harm avoidance was negatively related to the likelihood of changing occupation. The results of this study underscore the importance of considering personality in relation to engagement in lifelong learning activities. Insights from this study can potentially increase the likelihood of finding methods to promote lifelong learning, which can be beneficial for educators, policymakers, and companies. [ABSTRACT FROM AUTHOR]

With the onset of the COVID-19 pandemic, parents had to reorganize their family routines under many external stressors (e.g., limited external childcare), which could have negatively affected their relationship satisfaction. This study aimed to examine the changes in relationship satisfaction of young parents from pre-pandemic times up to the second wave of the COVID-19 pandemic in Germany in December 2020 and whether these changes were different for mothers and fathers. Additionally, the role of perceived pandemic-related stress and changes in family routines was investigated. Data from 564 participants from DREAMCORONA, a sub-study of the prospective longitudinal cohort study "Dresden Study on Parenting, Work, and Mental Health" (DREAM), were analyzed. Relationship satisfaction was assessed at three measurement points (T0: pre-pandemic, i.e., August 2018–March 2020; T1: May–June 2020; T2: October–December 2020). To estimate changes in relationship satisfaction over time, Latent Growth Curve Models were calculated. Changes in family routines (i.e., changes in the division of housework and childcare from T0 to T1 as well as the availability of external childcare facilities at T1) and perceived pandemic-related stress at T1 were used as predictors. The models were adjusted for education and number of children per household. There was no significant change in relationship satisfaction over time, with no differences between mothers and fathers. The multi-group model revealed that changes in the division of housework and childcare predicted changes in relationship satisfaction in mothers, but not in fathers. For mothers, doing more housework than before the pandemic was negatively associated with changes in their relationship satisfaction over time. Additionally, reporting that their partner did more childcare than before the pandemic was positively associated with the relationship satisfaction of mothers. Our results indicate no general negative prospective association between the COVID-19 pandemic and parental relationship satisfaction over time. Nevertheless, our findings highlight the importance of the division of housework and childcare for mothers' relationship satisfaction and how pandemic-related changes in family routines alter this association. [ABSTRACT FROM AUTHOR]

Proximate determinants theory considers infertility rates a risk factor for lower fertility rates, but the assumption that people who perceive infertility will have fewer children has not been tested. This study investigates the association of self-perceived infertility with the number of children people have had after 11 years. Infertility implies reduced chances of conception (rather than sterility), but people do not always consistently perceive infertility over time. If people who think they are infertile at one time can later report no infertility, then does self-perceived infertility necessarily lead to having fewer children? We answer this question by analyzing 11 waves of the German family panel (pairfam) data using negative binomial growth curve models for eight core demographic subgroups created by combinations of gender (men/women), parity (0/1+children), and initial age groups (25–27 and 35–37). Those who repeatedly perceived themselves to be infertile (three times or more) had fewer children than those who perceived themselves to be infertile once or twice in only four of eight gender by initial parity by age groups. Only in four groups did people who perceived themselves to be infertile once or twice have fewer children than those who never perceived themselves to be infertile in both the unadjusted and adjusted models. Thus, self-perceived infertility does not necessarily result in fewer children. Rather, the association depends upon life course context and gender. [ABSTRACT FROM AUTHOR]

Aim: The aim of the present study was to compare the Preece–Baines 1 (PB1) model fit between longitudinal and cross‐sectional data in male soccer players and to adjust the height growth curve by maturity status. Methods: A final sample of 57 male Portuguese soccer players from professional soccer academies was included. Longitudinal height records were measured between 8 and 17 times in each subject from 2–8 years to 14–17 years. Additionally, longitudinal height records were used as cross‐sectional data along with 1087 cross‐sectional height records taken from 602 Portuguese soccer players. Skeletal age was estimated by Tanner‐Whitehouse III method from a left hand–wrist radiograph. Age at peak height velocity (PHV) was estimated by PB1 model for longitudinal and cross‐sectional data and by maturity status. Results: No significant differences were found between all the longitudinal estimates of 57 players and the random cross‐sectional samples for, S1 parameter and for growth velocity at PHV, at TO, and for age at PHV. The age at PHV in early, on‐time, and late maturers were 12.26, 12.9, and 13.58 years, respectively. Conclusion: PB1 adjusted the height growth of Portuguese male soccer players from cross‐sectional data, obtaining an estimate PHV very similar to that found from longitudinal data. A maturity time difference of ≈0.6 years was found between the age at PHV of on‐time, early, and on‐time and late maturity state. [ABSTRACT FROM AUTHOR]

Understanding the energy requirement and prey consumption of Arctic predators is crucial to assess their vulnerability to climate change. The bowhead whale (Balaena mysticetus) is the largest predator of the Arctic, with Disko Bay in Greenland constituting a major feeding ground for a segment (predominantly larger juveniles and adult non-lactating females) of the Eastern Canada-West Greenland population. We used unmanned aerial vehicle photogrammetry to measure the body size and condition of bowhead whales in Disko Bay during the spring (March 26–June 1, 2022), from which we quantified their energy requirements and prey consumption. Measurements of body length, width and height were used to estimate the body volume and condition of juveniles (50 measurements from 39 individuals) and adults (232 measurements from 154 individuals). The body condition of adults increased at a rate of 0.112 percentage points day−1, or 44.1–87.8 L of blubber day−1 (for lengths 13.0–17.0 m). Using published data from harvested whales, the estimated blubber mass gain was 37.1–73.9 kg day−1, which equals an energy deposition rate of 1.01–2.01 GJ day−1. Body maintenance costs were predicted from allometric models, while activity costs and the heat increment of feeding were derived from published archival tag data. Reported length-at-age curves were used to estimate somatic growth costs. The energy requirements for juveniles and adults were 0.621–0.778 GJ day−1 (for lengths 11.0–12.9 m) and 3.662–7.826 GJ day−1 (for lengths 13.0–17.0 m), respectively, which equals a prey consumption rate of 17–22 kg of prey day−1 (0.1% of body mass) and 102–218 kg day−1 (0.3% of body mass). [ABSTRACT FROM AUTHOR]

Teachers are key guidance figures in the lives of high-ability students. By building and maintaining close relationships with their students, teachers may heavily affect the socioemotional development of high-ability students. This study investigated how the teacher-student relationship quality affected the development of high-ability students' academic engagement. Additionally, we examined if the teacher-student relationship quality was more important for the engagement of at-risk high-ability students (i.e. students with a low SES background or students with a diagnosed learning disability or developmental disorder). A sample of 403 Flemish high-ability students (IQ = 120) reported on their behavioral and emotional (dis)engagement using scales developed by Skinner and colleagues (2009) and their relationship with their teachers using the People in My Life questionnaire (Cook et al. 1995). Multilevel growth curve analyses showed that positive and negative teacher-student relationships both contributed to the development of high-ability students' behavioral and emotional (dis)engagement. Analyses also revealed that negative relationships had a stronger effect on the behavioral disengagement of low SES students. The emotional (dis)engagement of students with a diagnosed learning disability or developmental disorder was less affected by a negative teacher-student relationship. Results highlight the key position of the teacher in creating an engaging environment for highability students. [ABSTRACT FROM AUTHOR]

Growth curve models are often used to describe a developmental course of a longitudinal response. This paper extends such models to assess multiphasic patterns of developmental trajectories for multivariate response variables. The multiphasic patterns are identified using a bivariate bent-cable model in the context of multivariate growth models. The approach allows for the simultaneous estimation of parameters of multiphasic changes in each response, and also takes into account the correlations among outcomes and random effects for repeated observations over time. The proposed methods are demonstrated using real data from an AIDS clinical study. [ABSTRACT FROM AUTHOR]

Panel survey data from Uganda, as well as data from the 2014 Uganda Population and Housing Census have been analyzed. The Growth Curve model with rank restrictions on parameters was used to estimate the small area means. The aim of the analysis was to assess change over time in household living standards (welfare), i.e., to investigate whether households display growth in living standards? whether households grow at the same rates? and whether households in different geographical areas of the country grow at the same rates? Using a GMANOVA-MANOVA model with rank restrictions on parameters, it was established that growth in household standards of living in Uganda varied across small areas. Sub-regions (small areas) with the highest standards of living in Uganda at the endline were Central Urban region, Kampala Urban region and South Western Urban region, while the sub-regions with the lowest standards of living at the endline were North East Rural region, North East Urban region and Eastern Rural region. The sub-regions with the highest growth rates in standards of living were Mid West Urban region, Mid North Rural region, and South Western Urban region. The sub-regions with the highest decline in standards of living were East Central Rural region, East Rural region and West Nile Urban region. [ABSTRACT FROM AUTHOR]

Lumpy skin disease virus is a member of the genus Capripoxvirus within the Poxviridae family that infects cattle and causes considerable economic losses. Providing a suitable cell culture for virus propagation is essential goal to be used for virus isolation and vaccine production. The present work deals with a novel cell culture, the ovine lamb heart (OLH), to investigate its benefit for LSDV propagation in comparison with the use of African green monkey kidney cells and Madin-Darby bovine kidney cell cultures. Ten serial passages of The Lumpy skin disease virus in each cell culture revealed a similar cytopathic effect recorded in the peak virus titer (6.0, 5.5, and 5.0 Log10 TCID50/ml in OLH, Vero, and MDBK cell cultures, respectively) by the 6th day post-cell infection at the time of harvest of the highest titer by studying the virus growth curve in each cell culture. The virus neutralization test (VNT) and direct fluorescent antibody technique (FAT) using specific anti-LSDV sera confirmed the presence of all used cell cultures. Therefore, it was concluded that OLH cell culture is suitable for the propagation of LSDV, and more research is needed to evaluate its use for vaccine preparation. [ABSTRACT FROM AUTHOR]

Sub-optimal learning outcomes have been observed, often attributed to monotonous educational processes that struggle to retain students' focus and stimulate active participation. This study investigates the potential influence of Augmented Reality (AR) on student motivation, utilizing a time series analysis approach. The primary objectives include assessing the impact of AR on student learning outcomes and identifying the most suitable model for elucidating this relationship. The central research question is: can the implementation of AR enhance student motivation in elementary education? A time series design with a quantitative methodology was employed, involving a cohort of 29 fourth-grade students in Indonesia. Data collection was conducted through a Likert scale questionnaire. Four trend models were tested: the Linear Trend Model, Quadratic Trend Model, Growth Curve Model, and S-Curve Trend Model. The analysis of the collected data, tabulated and analyzed based on the established time series, suggests a positive correlation between AR technology implementation and student motivation. An upward trend in learning motivation was observed following the consistent application of AR technology in educational activities. Among the tested models, the Quadratic Trend Model demonstrated the least error estimate, with MAPE at 1.39, MAD at 1.08, and MSD at 1.44, suggesting it as the most suitable for further analysis related to the predictive power of student learning motivation in this context. This study advocates for the utilization of AR technology as an alternative method in classroom learning activities. The integration of learning content with game-like elements within a realistic world was observed to elicit student interest and enthusiasm. This approach is particularly recommended for educators seeking to enhance their students' learning motivation. [ABSTRACT FROM AUTHOR]

Measuring weight during cattle growth is essential for determining their status and adjusting the feed amount. Cattle must be weighed on a scale, which is laborious and stressful and could hinder growth. Therefore, automatically predicting cattle weight could reduce stress on cattle and farm laborers. This study proposes a prediction system to measure the change in weight automatically during growth using three regression models, using environmental factors, feed intake, and weight during the period. The Bayesian inference and likelihood estimation principles estimate parameters that determine the models: the weighted regression model (WRM), Gaussian process regression model (GPRM), and Gaussian process panel model (GPPM). A posterior distribution was derived using these parameters, and a weight prediction system was implemented. An experiment was conducted using image data to evaluate model performance. The GPRM with the squared exponential kernel had the best predictive power. Next, GPRMs with polynomial and rational quadratic kernels, the linear model, and WRM had the next-best predictive power. Finally, the GPRM with the linear kernel, the linear model, and the latent growth curve model, and types of GPPM had the next-best predictive power. GPRM and WRM are statistical probability models that apply predictions to the entire cattle population. These models are expected to be useful for predicting cattle growth on farms at a population level. However, GPPM is a statistical probability model designed for measuring the weight of individual cattle. This model is anticipated to be more efficient when predicting the weight of individual cattle on farms. [ABSTRACT FROM AUTHOR]

Functional data analysis has emerged as a powerful tool in response to the ever‐increasing resources and efforts devoted to collecting information about response curves or anything that varies over a continuum. However, limited progress has been made with regard to linking the covariance structures of response curves to external covariates, as most functional models assume a common covariance structure. We propose a new functional regression model with covariate‐dependent mean and covariance structures. Particularly, by allowing variances of random scores to be covariate‐dependent, we identify eigenfunctions for each individual from the set of eigenfunctions that govern the variation patterns across all individuals, resulting in high interpretability and prediction power. We further propose a new penalized quasi‐likelihood procedure that combines regularization and B‐spline smoothing for model selection and estimation and establish the convergence rate and asymptotic normality of the proposed estimators. The utility of the developed method is demonstrated via simulations, as well as an analysis of the Avon Longitudinal Study of Parents and Children concerning parental effects on the growth curves of their offspring, which yields biologically interesting results. [ABSTRACT FROM AUTHOR]

Entropy is widely used in ecological and environmental studies, where data often present complex interactions. Difficulties arise in linking entropy to available covariates or data dependence structures, thus, all existing entropy estimators assume independence. To overcome this limit, we take a Bayesian model-based approach which focuses on estimating the probabilities that compose the index, accounting for any data dependence and correlation. An estimate of entropy can be constructed from the model fitted values, returning an observation-specific measure of entropy rather than an overall index. This way, the latent heterogeneity of the system can be represented by a curve in time or a surface in space, according to the characteristics of the survey study at hand. An empirical study illustrates the flexibility and interpretability of our results over temporally and spatially correlated data. An application is presented about the biodiversity of spatially structured rainforest tree data. [ABSTRACT FROM AUTHOR]

To date, research on the transition to parenthood and associated changes in relationship satisfaction (RS) has focused predominantly on mothers with their firstborn. This study targeted fathers to investigate their trajectories of RS with a particular focus on emerging differences between first- and second-time fathers. It furthermore considered various predictors such as the role of age, education, income, duration of relationship, marital status, child's biological sex, and child temperament. Data from a total of 606 fathers from the prospective longitudinal cohort study DREAM were analyzed. The analyses included assessments of four measurement time points (T1: prepartum; T2–T4: postpartum) over a period of more than 2 years. Latent growth curve modeling was applied with RS as the dependent variable and number of children as one of eight predictors of growth over time. First-time fathers showed higher initial RS, however experienced a steeper decline in the transition to parenthood than second-time fathers. At 8 weeks postpartum, first-time fathers still reported higher RS than second-time fathers. While RS continued to decline for first-time fathers up until 14 months postpartum, second-time fathers experienced an increase in RS. At 14 months and 2 years postpartum, second-time fathers showed higher RS scores than first-time fathers. Similar to first-time mothers, first-time fathers seem to experience a stronger RS decline during the transition to parenthood than second-time fathers, suggesting that especially couples becoming parents for the first time should be prepared for expected changes in their relationship. [ABSTRACT FROM AUTHOR]

Natural mortality rates (M) are poorly quantified and commonly identified as a key source of uncertainty in fish stock assessments. Increasingly, stock assessments account for size- and age-dependence in M instead of using a constant M for all sizes and ages, as has traditionally been the default assumption. Empirical studies show that M is approximately inversely proportional to body length in fish populations, and this generalization has been used together with a von Bertalanffy growth curve to derive an age-dependent M. Here we extend this approach to the three commonly used growth functions of the Richards family (i.e., Logistic, von Bertalanffy, and Gompertz growth models). These models allow flexible production of various growth curves with a sigmoid shape and an upper asymptote, making them useful for displaying diverse growth curves for various long-lived fishes. The influences of growth parameters on predicted M were investigated, and the outcomes were compared among the three growth models. Age-dependent M for blue sharks (Prionace glauca) were estimated as an example. [ABSTRACT FROM AUTHOR]

This study investigates the associations between students' developmental changes in academic self-efficacy, academic initiative, and grade point average (GPA) during a three-year upper secondary education. The sample consisted of 1453 students aged 16–19 (60.6% girls; baseline mean age = 17.00, SD =.91; 56.1% high perceived family wealth; and 74.9% Norwegian-born). To explore how changes in academic self-efficacy, academic initiative, and GPA were related, we investigated a theoretical parallel process latent growth curve model. The results implied that, during upper secondary school, academic self-efficacy declined, while academic initiative and GPA remained stable. We found possible ceiling effects within and between several of the study's constructs. The main finding was support for a positive feedback loop between the developmental trajectories of academic self-efficacy, academic initiative, and GPA. The present study adds new insight that should be taken into consideration when promoting positive educational development during late secondary school. Academic self-efficacy declines during upper secondary school, while academic initiative and grade point average remains stable. Parallel process latent growth curve model analysis. Possible ceiling effects within and between several of the study's factors. Positive associations between the trajectories of academic self-efficacy, academic initiative, and grade point average. [ABSTRACT FROM AUTHOR]

This article aims to evaluate the childcare appointments by health professionals working at the Family Health Strategy in municipalities in the State of Paraíba, compare the performance by health team type (The Mais Médicos Program or conventional), and analyze the association of client satisfaction with the developed actions. This cross-sectional study evaluated the structural conditions of health units, the work process of health professionals, and client satisfaction, observing childcare appointments in 22 health teams. Poor employment relationships and professionals' knowledge about child growth curves were highlighted in the structure. In the 175 appointments observed, we detected neglect in completing the Child Health Booklet (CHB), obtaining data on food consumption, and guidance practices. Only 36% of the appointments were classified with adequate duration. There was greater satisfaction for appointments developed in health teams of the Mais Médicos Program, with longer duration and better performance in guidance practices. The implementation of childcare appointments reveals significant gaps that can influence maternal satisfaction. [ABSTRACT FROM AUTHOR]

This study documents a cost-effective strategy for managing Malayan sun bears (Helarctos malayanus) in the captive, focusing on their weight at the National Wildlife Rescue Centre (NWRC), Perak, Malaysia. The weight and development of captive bears' average aged of two months were assessed using data collected over 18 months. Asymptotic bear weight was estimated using the von Bertalanffy equation. The growth curves significantly differed between male and female bears, with males growing much larger than females from early to later growth stages. This study has determined three types of age classes of bears, where the age of adult Malayan sun bears are fully grown at 11 years and six months for males and eight years and nine months for females. Sub-adult bears ranged between one and six years old for males and one and four years for females, while cubs ranged from zero to one year old. Furthermore, the ideal weight for captive Malayan sun bears by age was also successfully determined. Such information is important for the management of this species in captivity. Ensuring the correct weight and age stage, among other criteria, could be useful for successfully releasing rehabilitated sun bears into their natural habitats. [ABSTRACT FROM AUTHOR]

The LAI is a key parameter used to describe the exchange of material and energy between soil, vegetation and the atmosphere. It has become an important driving datum in the study of carbon and water cycle mechanism models at many regional scales. In order to obtain high temporal resolution and high spatial resolution LAI products, this study proposed a method to combine the high temporal resolution of MODIS LAI products with the high spatial resolution of Sentinel-2 data. The method first used the LACC algorithm to smooth the LAI time-series data and extracted the normalized growth curve of the MODIS LAI of forest and used this curve to simulate the annual variation of the LAI. Secondly, it estimated the LAI at the period of full leaf spread based on the traditional remote sensing statistical model and Sentinel-2 remote sensing data as the maximum value of the forest LAI in the study area and used it to control the LAI growth curve. Finally, the time-series LAI data set was created by multiplying the maximum LAI by the normalized forest LAI growth curve. The results indicate that: (1) the remote sensing statistical estimation model of LAI was developed using the atmospherically resistant vegetation index ARVI ( R 2 = 0.494); (2) the MODIS LAI normalized growth curve keeps a good level of agreement with the actual variation. This study provides a simple and efficient method for obtaining effective time-series forest LAI data for the scope of small- and medium-sized areas. [ABSTRACT FROM AUTHOR]

In this article, we compare two ways of modelling measures of fetal growth. The goal is to impute the missing information for certain ultrasound measurements that are observed at different times and with different numbers of observations. To analyze the effect that other variables have, such as environmental exposure to certain substances or diet, on fetal growth based on these data, we need to handle the information measured at the same instant of time for all the individuals under study, preferably in three time windows of pregnancy (first trimester, week 12; second trimester, week 20; third trimester, week 34). For this, data at these chosen times, in case they are not available, must be imputed from the available information using an appropriate statistical model. One option is to use a linear model, specifically a generalized least squares model that is fitted to the features shown in the data. The other option is to use diffusion processes, estimating their parameters based on the available information. In both options, missing data can be estimated with the unconditional fitted model, conditional on the previous available measurement, or conditional to the closest measurement. [ABSTRACT FROM AUTHOR]

Three non-linear growth models (logistic, Gompertz and von Bertalanffy) were used to describe and estimate growth parameters of 10-week age-body weight relationship of mixed-sex Egyptian indigenous geese. The estimated asymptotic weight (A), scaling parameter (B), maturity index (K), inflection weight (Wi) and time (Ti) were respectively 3254.00 g, 13.15, 0.48 g/day, 1627 g and 5.37 weeks; 3895.00 g, 3.33, 0.25, 1431.99 g and 4.81 weeks; and 4559.00 g, 0.72, 0.17, 1350.81 g and 4.53 weeks for the logistic, Gompertz and von Bertalanffy growth function. The application of four goodness-of-fit criteria [coefficient of determination (R2), root mean square error (RMSE), Akaike's information criterion (AIC) and Bayesian information criterion (BIC)] revealed that von Bertalanffy was the best fitting model describing age-body weight relationship of Egyptian native geese. This was premised on the fact that the von Bertanlanffy model had the highest R2 (0.896) and lowest RMSE (327.05), AIC (8806.50) and BIC (5747.86) compared with the Gompertz (R2: 0.897; RMSE: 328.70; AIC: 8813.05; BIC: 5754.40) and logistic (R2: 0.891; RMSE: 338.90; AIC: 8841.71; BIC: 5783.07) models. The information provided in this study could be exploited for planning appropriate management practices and further genetic studies on improvement of Egyptian native goose for increased body weight. [ABSTRACT FROM AUTHOR]

An update of the age and growth for juveniles of the short fin mako shark (I. oxyrinchus) from the Mexican Pacific is presented, based on the analysis of growth band counts from dorsal vertebrae of 198 individuals [110 females, 74–231 cm of total length (TL) and 88 males, 72–231 cm TL) caught during 2008–2018. New available information on vertebral growth band periodicity (biannual deposition in juveniles) and the convenience of using vertebrae form the dorsal region over the cervical region to count growth bands, as well as a multimodel approach, were used. The von Bertalanffy (VB) growth model, Gompertz, logistic and two parameters of VB (2‐VB) were fitted to the length‐at‐age. Only ages ≤6 years were used for the fitting of the models and their performance was compared with the small‐sample bias‐corrected form of the Akaike information criterion (AICc), their differences (∆i) and weights (wi). Following a multimodel inference approach, the model averaged asymptotic length (L¯inf), length‐at‐age 0 (L¯0) and their unconditional standard error (SE¯), were estimated for each sex scenario using the three‐parameter version of each model. The precision of growth band counts was acceptable for the different methods used and by two different readers. The centrum edge analysis (CEA) and marginal increment analysis (MIA) did not support the hypothesis of biannual band pair formation for juveniles, likewise for adults the periodicity could not be verified due to the small sample of large animals. Age was estimated assuming the formation of two pairs of growth bands per year during the first 5 years and one pair of bands per year afterwards considering direct validation information. The estimated ages in years ranged from 0–14 for females and 0–6 for males. The Kimura likelihood ratio test showed no differences in the growth curves of juveniles by sex (P > 0.05). According to the AICc, the 2‐VB model better fitted the length‐at‐age data for combined sexes (Linf = 386.4 cm, k = 0.12 years−1, L0 = 70 cm). The model averaged L¯inf and L¯0 were 378.3 cm (SE¯=64.5) and 69.5 cm (SE¯=6.3), respectively. The growth parameters determined for juveniles of I. oxyrinchus are similar to those estimated in other regions, showing relatively fast growth rate as previously reported, medium longevity in comparison to other shark species and natural mortality close to that reported in the last stock assessment for the North Pacific Ocean. These life‐history parameters should be considered to evaluate the population in the region and to develop better fishery management and conservation measures. [ABSTRACT FROM AUTHOR]

In our modern world, energy keeps the global economy running, and economic growth concerns are profoundly interrelated with environmental quality issues. Interestingly, scientists engage with empirical research to identify the impacts and causalities at the interface of economic activities, energy supply, and demand. The importance of the present study lies in a discussion of all contemporary research efforts bridging two strands of empirical literature in environmental economics: developments in energy growth nexus discussion and the environmental Kuznets curve. Furthermore, it highlights the inclusion of untested explanatory variables and the impacts on environmental degradation levels. In the context of the EKC hypothesis, the most popular indicators are greenhouse gas emissions (GHGs) and carbon dioxide emissions in conceptualizing environmental degradation. A review of relevant empirical studies disclosed additional research opportunities that can consider currently untested and less visible proxies of economic growth. For both strands in the literature, results differ based on the group of countries investigated, the econometric models adopted, the format of data, e.g., time series or panel analyses, the time frames due to data availability, and the proxies used to conceptualize energy, environmental degradation, and economic growth. Practical implications indicate that environmental degradation can be avoided or significantly limited within sustainable economic growth to reduce carbon dioxide emissions and increase the use of renewables in the energy mix. Furthermore, one particular implication is the concept of energy efficiency to reduce relevant demand to produce the same outcome or task. [ABSTRACT FROM AUTHOR]

To handle the nonnormal data issue, Browne proposed an unbiased distribution free (DF) estimator ( Γ ^ DF U ) and an asymptotically distribution free estimator ( Γ ^ ADF ) of the covariance matrix of sample variances/covariances Γ to calculate robust test statistics and robust standard errors. However, Γ ^ DF U is ignored in methodological and substantive research, and has not been extended to models with mean structures. To improve robust standard errors and the model fit statistic for nonnormal data with mean structures (e.g., growth curve models), we propose an unbiased distribution free estimator with mean structures considered. In growth curve models, we apply Γ ^ DF U to four robust statistics that have relatively simple forms and denote them as T S B U , T MVA U , T MVA 2 U , and T COR 1 U. We compare their performance with 7 robust test statistics that employ Γ ^ ADF . We find that with the same model fit statistic, Γ ^ DF U generally leads to smaller Anderson-Darling distances from the theoretical distribution than Γ ^ ADF , except T MVA 2 U in some skewed cases. Additionally, the p-values from T MVA 2 U are distributed closest to the theoretical distribution Uniform (0 , 1) among the 12 examined statistics. In terms of Type I error rates, T MVA 2 U and T MVA 2 are the most stable statistics. Additionally, Γ ^ DF U provides smaller relative biases of the robust SE estimates than Γ ^ ADF . Hence, we suggest using Γ ^ DF U in both model fit statistics and robust SE calculation. Among the model fit statistics using Γ ^ DF U , we suggest T MVA 2 U. [ABSTRACT FROM AUTHOR]

This study aimed to characterize Matabele goats based on their qualitative and quantitative traits, to facilitate their genetic improvement and conservation. Data were collected from 120 goats over 12 months, comprising 20 males and 100 females using a stratified random sampling approach. Body weight and various body measurements were recorded. Five growth curve estimation models were employed to describe the growth pattern of Matabele goats. Descriptive statistics were computed for both qualitative and quantitative traits. Ttests were conducted to assess the impact of sex on morphometric measurements in different age groups. The results revealed an average body weight of 20.93 kg, with significant sex-related differences (p < 0.05) observed across all quantitative traits. Most goats displayed horned and bearded characteristics, while black and white coat colours were predominant. Among the growth curve models, the Gompertz model exhibited the highest R2 value (0.992). Notably, the study found relatively low average morphometric measurements and body weight for Matabele goats, emphasizing the urgent need for genetic improvement efforts and the development of comprehensive breeding standards for this breed. [ABSTRACT FROM AUTHOR]

A phenomenological model of planktonic microbial cultures, reported in previous papers, suggests that the whole growth progress seems planned by the microbial population since a pre-growth latency phase, during which the population level remains at its starting level. This model is in line with recent suggestions about the behavior of complex systems, as long as it allows for the gathering of the growth trends of a number of real batch cultures in a single master plot of reduced variables, in spite of their metabolic and physiological differences. One important issue of the model concerns the origin of the time scale for the microbes that can differ from that for the observer. The present paper reports some consequences of the model in view of its potential use in predictive microbiology and proposes an extension to the steady and decay phases of the culture evolution suggesting that, consistent with the assumptions about the growth phase, the decay occurs by a scan of the cell generation steps. This view leads to the conclusion that the steady phase between growth and decay trends actually corresponds to the loss of the oldest cell generations, which represents minor fractions of the microbial population. Such early decay is almost undetectable in a log scale, looking like a steady phase. To account for cases that show a broad maximum instead of an intermediate steady trend, a single continuous function, still related to the model, can describe the whole growth and decay trend of the microbial culture. [ABSTRACT FROM AUTHOR]

Today, Progress Testing is an established and accepted form of assessing applied knowledge in undergraduate medical curricula. This work aims to test the performance of Italian medical and dental schools and above all the growth of knowledge in the different years analyzed. At this end, we studied longitudinal data from progress testing at Italian Dental University Schools. The contribution of this work is a new perspective on the analysis of progress testing through the use of a growth curve. In particular, from a methodological point of view, we aimed to demonstrate that the PLS-PM approach can be successfully used to estimate growth curves. The results of this first analysis confirm a thesis already present in the literature, according to which a substantial amount of variation can be attributed to different rates in the growth of knowledge across medical schools. [ABSTRACT FROM AUTHOR]

This article demonstrates how to perform univariate repeated measures ANOVA (U-RM-ANOVA) as a special case of structural equation models (SEMs). In the literature, sphericity is usually defined in terms of variances of pairwise differences of within-subject conditions. This article illustrates the original definition by Huynh and Feldt (1970) in terms of (co)variances of contrasts using SEM and demonstrates how to impose, test, and relax sphericity, and how to test main/interaction effects with and without the assumption of sphericity in SEM. We perform two simulation studies. The first study compares Mauchly's sphericity test with an SEM based test and shows that the two approaches have a very similar Type 1 error and power. The second study compares U-RM-ANOVA with SEM for different degrees of departure from sphericity and shows that U-RM-ANOVA and SEM have similar statistical properties in terms of Type 1 error, power, as well as similar bias and efficiency of effect size estimates of main and interaction effects. We furthermore show how to implement sphericity in latent variable models and provide software to perform the proposed tests and analyses. [ABSTRACT FROM AUTHOR]

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Factors associated with dynamic changes in the objectively measured physical activity have not been well understood. We aimed to 1) evaluate the longitudinal change in the physical activity trajectory according to sex which is associated with age and to 2) determine the factors associated with the dynamic change in physical activity-related variables across a wide age range among Japanese adults. This longitudinal prospective study included 689 Japanese adults (3914 measurements) aged 26–85 years, whose physical activity data in at least two surveys were available. Physical activity-related variables, such as intensity (inactive, light [LPA; 1.5 to 2.9 metabolic equivalents (METs)], moderate-to-vigorous [MVPA; ≥3.0 METs]), total energy expenditure (TEE), physical activity level (PAL), and step count, were evaluated using a validated triaxial accelerometer. Statistical analysis involved the latent growth curve models and random-effect panel data multivariate regression analysis. During a mean follow-up period of 6.8 years, physical activity was assessed an average of 5.1 times in men and 5.9 times in women. The profiles for the inactive time, LPA (only men), MVPA, step count, PAL, and TEE showed clear curvature, indicating an accelerated rate of change around the age of 70. In contrast, other variables exhibited minimal or no curvature over the age span. The MVPA trajectory was positively associated with alcohol consumption, hand grips, leg power, and trunk flexibility and negatively associated with age, local area, body mass index (BMI), comorbidity score, and heart rate over time. Our results indicated that the physical activity trajectory revealed clear curvature, accelerated rate of change around the age of 70, and determined physical health and fitness and BMI as dynamic factors associated with physical activity changes. These findings may be useful to help support populations to achieve and maintain the recommended level of physical activity. [ABSTRACT FROM AUTHOR]

Traditionally, the von Bertalanffy model has been used as the only standard in the study of fish growth, considering it a priori as the only model that fits the length-age data of the species; a consideration that generates uncertainties in the values of the growth parameters that are estimated, since it is known that other growth models could also fit the length-age data. In this sense, in the Middle Orinoco region, a study of Brachyplatystoma rousseauxii growth was previously done using the traditional von Bertalanffy model, and the results were subsequently used to evaluate the population; hence the objective of the present work was to validate the results of the previous work, fitting the same length-age data to the growth models of the U Richards family, and selecting the best fit using the Akaike Information Criterion (AIC). As demonstrated in the first paper, the traditional von Bertalanffy model fitted the back-calculated length-age data, but only 35;4 %; while the majority (64,6 %) fitted the U von Bertalanffy, U Logistic, and U Gompertz models, with no superiority of any of them in the fit. The growth parameters estimated from na average model were somewhat from those obtained in the previous work, and therefore necessary to re-evaluate the resource to know its level of exploitation in the Middle Orinoco. [ABSTRACT FROM AUTHOR]

• Children's mastery motivation (MM) increased dramatically from 18 to 54 months. • The slope of MM varied from toddlerhood to preschool age, with the most increase from 42 to 54 months. • Maternal warmth at 18 months was positively related to initial levels of MM. • Maternal assertive physical control was negatively related to initial levels of MM. • Maternal assertive physical control predicted the slope of MM over time. The goal of this study was to investigate the development of young children's goal-directed behaviors in challenging settings––an important behavioral component of mastery motivation – and to examine the relations of maternal warmth and control to its trajectory from toddlerhood to preschool age. A behavioral component of mastery motivation was observed during children's (N = 251, 140 boys) increasingly challenging cognitive tasks at 18, 30, 42, and 54 months of age. Maternal warmth and assertive physical control were observed in both the challenging cognitive task and a challenging social task (i.e., clean-up task) at 18 months. A latent basis growth curve was identified, which suggested that this aspect of children's mastery motivation increased at different speeds from 18 to 54 months. Specifically, it increased 25% of the overall change between 18 and 30 months, increased only 2% between 30 to 42 months, and then increased by 73% from 42 to 54 months. Maternal high warmth and low assertive physical control during the challenging cognitive task were related to a higher initial intercept but a slower increasing slope of this aspect of mastery motivation over time. In a somewhat similar manner, in the challenging social task, maternal high warmth and low maternal assertive physical control were at least marginally related to a high initial intercept, but the two maternal behaviors were unrelated to the slope. This study is one of the first to identify the longitudinal developmental trajectory of this behavioral component of mastery motivation in very young children, and the results point to the importance of reducing maternal assertive physical control across contexts to foster the early development of mastery motivation. [ABSTRACT FROM AUTHOR]

The interface evolution characteristics and deformation mechanisms of Cu/Al multilayers are investigated via systematic molecular dynamics simulations. It is found that both the yield strength and ductility increase slightly with increasing strain rate, and the stress-strain curves exhibit two main yield points for all strain rate loadings. The first yield point correlates with the decomposition of perfect misfit dislocations on the interface and the propagation of partial dislocations inside the Al layer, and the second yield point relates with the dislocation transmission from the Al layer into the Cu layer. The lower the loading strain rate, the more severe the fluctuations on the stress-strain curve. However, the strain rates do not change the evolution way of dislocation networks. The calculated evolution curves of dislocation numbers indicate that the dislocation density inside the Cu layer is lower than that inside the Al layer. The interface region displays a serrated structure without voids or cracks, and the higher the loading strain rate, the more serious the interface roughening deformation. The main deformation mechanisms, respectively, are the formation of a lamellar twin structure in the Cu layer and dislocation slip in the Al layer, and the interface roughening is mainly dominated by the formation of a lamellar twin structure. Furthermore, the deformation mechanisms do not depend on the strain rate applied in this paper. In addition, we also discuss the growth curve of interface thickness which is divided into three stages. [ABSTRACT FROM AUTHOR]

Trust is crucial to the public's compliance with policies and rules released by governments, particularly in times of the coronavirus disease 2019 (COVID-19) pandemic. However, it remains unclear whether and to what extent late adolescents' interpersonal and institutional trust fluctuated from the pre-COVID-19 pandemic to the lasting phase of the COVID-19 pandemic. The present study uses three-wave longitudinal data from the Youth Got Talent (YGT) project to address this gap (n = 1,423; 43% boys; Mage= 17.85, SD = 1.95). Latent basis growth curve models showed that interpersonal trust remained relatively stable over time. In contrast, institutional trust temporarily increased from pre-COVID-19 pandemic (Fall 2019) to the initial phase of the COVID-19 pandemic (Spring 2020) and subsequently, decreased during the lasting phase of the COVID-19 pandemic (Fall 2020). These results enhance our understanding of trust among late adolescents and have implications for policies aiming to manage the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

The study investigates the mediating role of population growth in the nexus between electricity access and sustainable growth of frontier economies. The study spans the period 2000–2020 for a panel of 25 frontier economies. Predicated on a modified environmental Kuznets curve (EKC) model, the technique of analysis is the panel quantile regression across the three major threshold levels of 25th, 50th and 75th percentiles. Also, higher threshold levels such as 90th, 95th and 97.5th percentiles were investigated. Prior to the estimations, various preliminary tests, including the panel unit root tests, were conducted to confirm the data stability conditions of the variables. The study found that access to electricity engenders sustainable growth in these frontier economies only up to the 95th percentile. However, exchange rate is said to endanger the sustainable growth path of these economies and these economies should not tolerate any idea of currency devaluation. More so, these economies should be made competitive to avoid currency depreciation. Interestingly, the role of population growth can be described as being a dividend rather than a burden but became imperceptible at the 95th percentile. Hence, efforts should be made to make increasing population remain qualitative for growth to remain sustainable. [ABSTRACT FROM AUTHOR]

The present study examined the effect of children's enrollment in U.S. dual-language immersion (DLI) programs in first grade on English development across five years, using the Early Childhood Longitudinal Study, Kindergarten Class of 2011 (ECLS-K:2011) database. Propensity score matching was used to create comparable groups of DLI and non-DLI students based on students' kindergarten reading performance and a series of student-, family-, and school-level characteristics. Growth curve models demonstrate that first-grade DLI enrollment had a positive effect on children's English reading growth from Grade 1 to 5. Children who enrolled in DLI experienced greater improvements by Grade 5. We also found that first-grade teacher judgment was related to children's initial reading performance but not their reading growth. Implications related to DLI programs, teacher practices, and bilingual educational policies are discussed. [ABSTRACT FROM AUTHOR]

This study explores how primary school children develop their metacognitive knowledge and vocabulary knowledge and how both types of knowledge are dynamically correlated from 1st to 4th grade. The longitudinal sample included 426 first-grade students (M = 6.6 years, SD =.51; 50.2% boys, 49.7% girls) from five public primary schools in China. A set of tests on metacognitive knowledge and vocabulary knowledge were administered four times over four years. The one-on-one-basis metacognitive knowledge test was based on students' explanations about cognitive activities; the vocabulary knowledge test focused on students' breadth and depth of vocabulary knowledge. Latent growth curve modelling was used to study developmental change. Results showed that participants' metacognitive knowledge and vocabulary knowledge improved from 1st to 4th grade but not in a cumulative fashion. Participants' level of metacognitive knowledge was strongly associated with their vocabulary knowledge throughout the selected school years. The development of vocabulary knowledge breadth lagged behind vocabulary knowledge depth during the study period. These findings shed light on primary school students' development of metacognitive knowledge and vocabulary knowledge. [ABSTRACT FROM AUTHOR]