The modal verbs of necessity and obligation, a testing ground of grammatical change, have been shown to exhibit change and variation in world Englishes. Previous studies have primarily concentrated ...on English as a native language (ENL) and English as a second language (ESL) varieties. The present study extends this line of research and explores variation in modal verbs of necessity and obligation in English use as a Lingua Franca (ELF). Descriptive statistics indicate that ELF resembles American English and also shares similarities with ESL varieties. In addition, ELF further exhibits divergence from both ENL and ESL varieties that arises in multilingual interactions. The multivariate analysis of this study employs mixed-effects logistic regression on the use of must and have to. Integrating social and linguistic factors, this analysis exploits metadata gathered from the VOICE corpus, which has thus far been underused. The results of the inferential statistics indicate that the same sociolinguistic factors that influence the variation in ENL and ESL varieties also shape ELF grammar. These findings not only bring ELF closer to other English varieties but also demonstrate the advantage of studying ELF from a variationist sociolinguistic perspective.
For students with intensive learning needs for whom standard, validated interventions do not effectively promote academic growth, data-based instruction (DBI) is suggested as an effective, ...fine-grained approach to individualization. Key to DBI's success is making instructional changes based on individual students' progress monitoring data. The purpose of this study was to evaluate the effects of such instructional changes on student early writing outcomes. We applied a piecewise linear-linear mixed-effects (PLME) model to determine student writing growth trajectories before and after teachers introduced instructional changes. Using data from 46 elementary school students with intensive writing intervention needs, results showed that a PLME model with two segmented slopes-before and after the change-best explained students' observed change in writing scores. Results also showed that a higher level of initial writing skills was associated with higher levels of intercepts and additional growth gains after the instructional change, whereas the type of instructional change was not associated with predicted writing trajectories. We discuss the implications of positive effects of teachers' individualized timely decisions to change instruction using progress monitoring data as well as unexpected findings and study limitations such as small sample size and inconsistency in results.
Educational Impact and Implications StatementWhen individualizing instruction for students with the most intensive academic intervention needs, especially in writing, it is recommended that teachers use student progress data to evaluate the effectiveness of instruction. Teachers are encouraged to change their instruction if the data indicates that students are not progressing as expected. We examined whether the instructional changes made by elementary special education teachers while implementing data-based instruction (DBI) improved the early writing outcomes of struggling beginning writers. When teachers made appropriate decisions to change instruction for those students who were experiencing slower-than-expected writing progress within DBI, the students showed facilitated writing growth following these instructional changes.
Each year, millions of hatchery‐reared sea‐run brown trout Salmo trutta L. (the sea trout) juveniles are released into the natural environment in the Atlantic region. The aim of this work was to ...investigate the growth responses of sea trout to changing temperature conditions and to compare the growth plasticity between wild and hatchery‐reared fish. Scales were collected from sea trout in a selected river flowing into the southern Baltic Sea. We analyzed the scale increment widths as a proxy of somatic growth and investigated the interannual variabilities and differences in growth between fish groups (wild and hatchery‐reared). We used mixed‐effects Bayesian modeling and ascribed the variances in growth to different sources. Furthermore, we developed indices of interannual (2003–2015) growth variation in the marine and freshwater phases of the life cycle of the fish and analyzed the relationships between trout growth and temperature. Temperature positively affects fish growth, regardless of the origin of the fish. We observed stronger relationships between fish growth and temperature conditions in the marine phase than in the freshwater phase. Additionally, wild sea trout are characterized by stronger responses to temperature variability and higher phenotypic plasticity of growth than those of the hatchery‐reared individuals. Therefore, wild sea trout might be better suited to changing environmental conditions than hatchery‐reared sea trout. This knowledge identifies possible threats in management actions for sea trout with an emphasis on ongoing climate change.
Water temperature positively affects fish growth, regardless of the origin of the fish. Wild sea trout are characterized by stronger responses to temperature variability and higher phenotypic plasticity of growth than those of the hatchery‐reared individuals.
In robust parameter design for blocked experiments, the correlation of response observations within each block and model parameter uncertainty often impact acquiring ideal operating conditions. In ...this paper, a Bayesian mixed regression-based multi-response surface modeling and optimization method is suggested to address the above issues. Firstly, the mixed effects model is incorporated into the Bayesian framework, and posterior distributions of the model parameters are derived using Bayes' theorem. Secondly, the hybrid Monte Carlo algorithm is employed to calculate the model parameters. Thirdly, the expected quality loss function satisfying the specification is constructed to lessen the impact of outliers on the results of optimization, and the optimal factor settings are obtained by the hybrid genetic algorithm. In addition, the posterior probability is used to assess the conformance of the optimization results. Finally, a simulated study and real-world example of the additive manufacturing process are used to illustrate the viability of the proposed method. Compared with the current techniques, the proposed method can reduce the impact of model uncertainty on the modeling and optimization results, leading to more conformant and robust optimization results.
•The correlation of observations within block and model parameter uncertainty are considered.•The priors of covariance of random effect and standard deviation of random error are extended to non-conjugate priors.•Compared with MCMC, the HMC algorithm improves efficiency.•In the blocked experiment, both quality loss and the conformance of optimization results are simultaneously considered.•On the application side, the problem of quality design for multiple 3D printers printing simultaneously is solved.
Abstract
Cognitive functioning in older age profoundly impacts quality of life and health. While most research on cognition in older age has focused on mean levels, intraindividual variability (IIV) ...around this may have risk factors and outcomes independent of the mean value. Investigating risk factors associated with IIV has typically involved deriving a summary statistic for each person from residual error around a fitted mean. However, this ignores uncertainty in the estimates, prohibits exploring associations with time-varying factors, and is biased by floor/ceiling effects. To address this, we propose a mixed-effects location scale beta-binomial model for estimating average probability and IIV in a word recall test in the English Longitudinal Study of Ageing. After adjusting for mean performance, an analysis of 9,873 individuals across 7 (mean = 3.4) waves (2002–2015) found IIV to be greater at older ages, with lower education, in females, with more difficulties in activities of daily living, in later birth cohorts, and when interviewers recorded issues potentially affecting test performance. Our study introduces a novel method for identifying groups with greater IIV in bounded discrete outcomes. Our findings have implications for daily functioning and care, and further work is needed to identify the impact for future health outcomes.
Animal movement behaviours are shaped by diverse factors, including resource availability and human impacts on the landscape. We generated home range estimates and daily movement rate estimates for ...149 giraffe (
spp
) from all four species across Africa to evaluate the effects of environmental productivity and anthropogenic disturbance on space use. Using the continuous time movement modelling framework and a novel application of mixed effects meta-regression, we summarized overall giraffe space use and tested for the effects of resource availability and human impact on 95% autocorrelated kernel density estimate (AKDE) size and daily movement. The mean 95% AKDE was 359.9 km
and the mean daily movement was 14.2 km, both with marginally significant differences across species. We found significant negative effects of resource availability, and significant positive effects of resource heterogeneity and protected area overlap on 95% AKDE size. There were significant negative effects of overall anthropogenic disturbance and positive effects of the heterogeneity of anthropogenic disturbance on daily movements and 95% AKDE size. Our results provide unique insights into the interactive effects of resource availability and anthropogenic development on the movements of a large-bodied browser and highlight the potential impacts of rapidly changing landscapes on animal space-use patterns.
Understanding the heterogeneity between ambient concentration and personal exposure is crucial in studies regarding the health risks of air pollution exposure. We performed a panel study with 4–19 ...(average = 10) repeated personal monitoring in 16 adult subjects (ages 18–30) for three consecutive weeks during the winter and summer of 2011–2012 in the Chinese megacity of Guangzhou. Also, we conducted simultaneous ambient measurements at eight districts (including five urban sites, two suburban locations, and one rural site) of Guangzhou. Significant seasonal variations were shown in personal PM2.5 exposure for most of the analyzed components (p < 0.05), with higher levels in winter than in summer. Average personal exposures exhibited a pattern of central urban > suburban > rural areas for PM2.5 mass and most of the constituents (e.g., carbonaceous aerosols, ions). We applied mixed-effects models to estimate within- and between-subject variance components and determinants of personal PM2.5 exposure after adjusting for potential confounders. The within-subject variance component dominated the total variability (63.7–95.6%) for most of the investigated PM2.5 components. Ambient PM2.5 mass and its components were the dominant predictors and contributors of the corresponding personal exposures (0.11 <Rc2 < 0.97; p < 0.05). The results indicate that season and district type affect personal PM2.5 exposure and its components, contributing to 4.9–51.6% and 8.0–77.8% of the variability. Time indoors and outdoors were also factors affecting personal exposure. The study findings revealed ambient concentrations at a fixed monitoring station underestimated residents’ true exposure levels. In conclusion, the current study emphasizes the need for incorporating spatio-temporal activity patterns complementing evenly-distributed air quality monitoring networks to increase the estimation power in epidemiological analysis linking true personal exposure to health effects.
•Repeated personal monitoring is required in epidemiological study design for assessing the health effects of PM2.5 exposure.•Within-subject variance dominated the total variability of most exposure data.•Average ambient concentrations from multiple monitoring sites serve as better surrogates for young adults exposures.•Ambient concentrations, season, district type, and time indoors were factors influencing personal exposures.
Advances in analysis of longitudinal data Gibbons, Robert D; Hedeker, Donald; DuToit, Stephen
Annual review of clinical psychology,
01/2010, Volume:
6
Journal Article
Peer reviewed
Open access
In this review, we explore recent developments in the area of linear and nonlinear generalized mixed-effects regression models and various alternatives, including generalized estimating equations for ...analysis of longitudinal data. Methods are described for continuous and normally distributed as well as categorical (binary, ordinal, nominal) and count (Poisson) variables. Extensions of the model to three and four levels of clustering, multivariate outcomes, and incorporation of design weights are also described. Linear and nonlinear models are illustrated using an example involving a study of the relationship between mood and smoking.
•Small mammals impact seeds of economically valuable trees.•Small mammals have low impact on seeds of less valuable trees.•The most preferred seed was Pinus strobus, the least preferred Betula ...papyrifera.•Silvicultural practices did not directly influence seed selection by small mammals.
Small mammals play a critical role in forest ecosystems as both seed predators and dispersers; they have been shown to affect tree species composition within forests and may significantly reduce recruitment rates of certain tree species, many of which are commercially valuable. Thus, understanding small mammal seed preference is essential for both animal ecologists and foresters. Although extensive research on small mammal seed choice has been conducted both in North America and Europe, limited knowledge is available on: (1) the effects of silvicultural practices on seed choice; (2) seed selection – as most studies focus on seed use; and (3) certain understudied seed-small mammals interactions – e.g. few studies have concurrently examined both coniferous and deciduous seeds from North American mixed forests, and the seed selection of some small mammal species is not well-known (e.g. Napaeozapus). To contribute to filling these gaps, our study focused on the following objectives: (1) to quantify seed selection of seven forest seed species by small mammal species within the mixed forests of the eastern US; (2) to evaluate the influence of silvicultural practices on seed choice; (3) to explore relationships between seed choice and environmental factors such as weather and microhabitat.
We conducted a series of cafeteria-style experiments in the field and in the laboratory; 2459 seed choice events, mostly by four small mammal species (Peromyscus maniculatus, Myodes gapperi, Napaeozapus insignis, and Tamiasciurus hudsonicus) were analyzed using multinomial mixed-effect models, allowing us to determine the probability of selection for each seed species. We identified a consistently high-preference seed (Pinus strobus) and one low-preference seed (Betula papyrifera). All other species (Acer rubrum, Picea rubens, Tsuga canadensis, Quercus rubra, and to some extent, Abies balsamea) had intermediate preference levels. Indeed, selection varied also by small mammal species (e.g. Acer rubrum was the top choice for Myodes gapperi in the field).
Further, we found that the silvicultural practices examined here (even-aged management, two-stage shelterwood, and unmanaged) did not directly influence seed choice, whereas illumination (night- and day-time light levels), rain, and temperature did, and the magnitude of the effects varied by small mammal species. Our results show that in mixed forests, small mammals may impact seeds of economically valuable trees (e.g. Pinus strobus and Acer rubrum), whereas they may ignore seeds of less valuable trees (e.g. Betula papyrifera and Abies balsamea). We recommend that forest managers consider small mammal communities when developing forest regeneration plans.
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