Community rules and speaker behavior: Individual adherence to group constraints on (ING)

2015 ◽  
Vol 27 (3) ◽  
pp. 377-406 ◽  
Author(s):  
Jon Forrest
Keyword(s):  
North Carolina ◽  
Statistical Models ◽  
Mixed Effects ◽  
Internal Constraints ◽  
Internal Factors ◽  
Log Odds ◽  
Constraint Hierarchy ◽  
Over Time

AbstractThis paper investigates the degree to which individual speakers follow the morphosyntactic hierarchy governing grammatical constraints on (ING) in the Southern U.S. city of Raleigh, North Carolina. (ING) was used as the variable of study for its well-studied internal constraints and comparability to previous studies on the internal constraints oft/ddeletion. A lexical category constraint hierarchy for the community was determined via multivariate mixed-effects statistical models, and each speaker's (ING) pattern was compared to this hierarchy. Results show maintenance in grammatical constraints even when taking phonological factors into account, unlike some work ont/ddeletion. Uniformity exists across speakers with respect to the ordering of internal constraints despite the overall decline in rates of –inover time, but constraint weights (expressed as log odds) vary significantly from speaker to speaker, with no correlates to social or internal factors. These results have consequences for representation of individuals in terms of an aggregate pattern, questioning the consistency of factor weight values at the speaker level despite consistent ordering of constraints.

scholarly journals The power of modelling pulsatile profiles

2021 ◽  
Author(s):  
Michiel J. van Esdonk ◽  
Jasper Stevens
Keyword(s):  
Growth Hormone ◽  
Statistical Power ◽  
Quantitative Description ◽  
Mixed Effects ◽  
Post Dose ◽  
Deconvolution Analysis ◽  
Linear Mixed Effects ◽  
Non Linear ◽  
Over Time ◽  
Modelling Approach

AbstractThe quantitative description of individual observations in non-linear mixed effects models over time is complicated when the studied biomarker has a pulsatile release (e.g. insulin, growth hormone, luteinizing hormone). Unfortunately, standard non-linear mixed effects population pharmacodynamic models such as turnover and precursor response models (with or without a cosinor component) are unable to quantify these complex secretion profiles over time. In this study, the statistical power of standard statistical methodology such as 6 post-dose measurements or the area under the curve from 0 to 12 h post-dose on simulated dense concentration–time profiles of growth hormone was compared to a deconvolution-analysis-informed modelling approach in different simulated scenarios. The statistical power of the deconvolution-analysis-informed approach was determined with a Monte-Carlo Mapped Power analysis. Due to the high level of intra- and inter-individual variability in growth hormone concentrations over time, regardless of the simulated effect size, only the deconvolution-analysis informed approach reached a statistical power of more than 80% with a sample size of less than 200 subjects per cohort. Furthermore, the use of this deconvolution-analysis-informed modelling approach improved the description of the observations on an individual level and enabled the quantification of a drug effect to be used for subsequent clinical trial simulations.

Neighbourhood places, collective efficacy and crime: A longitudinal perspective

Urban Studies ◽  
2021 ◽  
pp. 004209802110088
Author(s):  
Renee Zahnow ◽  
Jonathan Corcoran ◽  
Anthony Kimpton ◽  
Rebecca Wickes
Keyword(s):  
Land Use ◽  
Social Control ◽  
Social Interactions ◽  
Collective Efficacy ◽  
Social Cohesion ◽  
Mixed Effects ◽  
Land Use Classification ◽  
Social Survey ◽  
Panel Models ◽  
Over Time

Neighbourhood places like shops, cafes and parks support a variety of social interactions ranging from the ephemeral to the intimate. Repeated interactions at neighbourhood places over time lay the foundation for the development of social cohesion and collective efficacy. In this study, we examine the proposition that changes in the presence or arrangement of neighbourhood places can destabilise social cohesion and collective efficacy, which has implications for crime. Using spatially integrated crime, social survey and parcel-level land-use classification data, we estimate mixed effects panel models predicting changes in theft and nuisance crimes across 147 Australian neighbourhoods. The findings are consistent with neighbourhood social control and crime opportunity theories. Neighbourhood development – indicated by fewer vacant properties and fewer industrial and agricultural sites – is associated with higher collective efficacy and less crime over time. Conversely, introducing more restaurants, transit stations and cinemas is associated with higher theft and nuisance over time regardless of neighbourhood collective efficacy. We argue that the addition of socially conducive places can leave neighbourhoods vulnerable to crime until new patterns of sociability emerge and collective efficacy develops.

scholarly journals A joint modeling approach for longitudinal microbiome data improves ability to detect microbiome associations with disease

2020 ◽  
Vol 16 (12) ◽  
pp. e1008473
Author(s):  
Pamela N. Luna ◽  
Jonathan M. Mansbach ◽  
Chad A. Shaw
Keyword(s):  
Joint Modeling ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Time Dependent ◽  
Time To Event ◽  
Modeling Framework ◽  
Microbial Composition ◽  
Disease Outcomes ◽  
Microbiome Data ◽  
Over Time

Changes in the composition of the microbiome over time are associated with myriad human illnesses. Unfortunately, the lack of analytic techniques has hindered researchers’ ability to quantify the association between longitudinal microbial composition and time-to-event outcomes. Prior methodological work developed the joint model for longitudinal and time-to-event data to incorporate time-dependent biomarker covariates into the hazard regression approach to disease outcomes. The original implementation of this joint modeling approach employed a linear mixed effects model to represent the time-dependent covariates. However, when the distribution of the time-dependent covariate is non-Gaussian, as is the case with microbial abundances, researchers require different statistical methodology. We present a joint modeling framework that uses a negative binomial mixed effects model to determine longitudinal taxon abundances. We incorporate these modeled microbial abundances into a hazard function with a parameterization that not only accounts for the proportional nature of microbiome data, but also generates biologically interpretable results. Herein we demonstrate the performance improvements of our approach over existing alternatives via simulation as well as a previously published longitudinal dataset studying the microbiome during pregnancy. The results demonstrate that our joint modeling framework for longitudinal microbiome count data provides a powerful methodology to uncover associations between changes in microbial abundances over time and the onset of disease. This method offers the potential to equip researchers with a deeper understanding of the associations between longitudinal microbial composition changes and disease outcomes. This new approach could potentially lead to new diagnostic biomarkers or inform clinical interventions to help prevent or treat disease.

scholarly journals Probability of pregnancy before ninety days postpartum in water buffaloes

2021 ◽  
Vol 30 (1) ◽  
pp. 29-34
Author(s):  
Hector Nava-Trujillo ◽  
Robert Valeris-Chacin ◽  
Adriana Morgado-Osorio ◽  
Javier Hernández ◽  
Janeth Caamaño ◽  
...  
Keyword(s):  
Mixed Model ◽  
Linear Mixed Model ◽  
Water Buffalo ◽  
Mixed Effects ◽  
Short Photoperiod ◽  
Water Buffaloes ◽  
Negative Effect ◽  
Log Odds ◽  
First 90 Days ◽  
Long Photoperiod

This study aimed to determine the effect of parity and season of calving on the probability of water buffalo cows becoming pregnant before 90 days postpartum. A retrospective analysis of reproductive records of 1,465 water buffaloes with 3,181 pregnancies was carried out. Buffaloes were grouped according to parity in one, two, or three and more calvings. Season of calving was created with the following values: long photoperiod (March-August) and short photoperiod (September-February) and predicted probabilities from the mixed-effects logistic regression model were calculated, and a generalized linear mixed model was fitted with random intercepts to calculate the log odds of becoming pregnant ≤90 days postpartum. The probability of pregnancy ≤90 days postpartum was 0.3645, and this was lower in primiparous (0.2717) in comparison with two-calved (0.3863) and three or more calving buffaloes (0.5166). Probability of pregnancy ≤90 days postpartum increased 1.77 odds by each increase in parity. The probability of becoming pregnant ≤90 days postpartum was higher in water buffaloes calving during the short photoperiod season (0.4239 vs. 0.2474, P>0.000), and water buffaloes calving during the long photoperiod season only had 0.2645 odds to become pregnant than those calving during the short photoperiod season. The negative effect of long photoperiod was observed indifferently of parity. In conclusion, primiparity and the long photoperiod affect water buffalo cow's reproductive performance, decreasing pregnancy probability during the first 90 days postpartum.

The Hub

2019 ◽  
pp. 141-181
Author(s):  
James N. Stanford
Keyword(s):  
Social Class ◽  
New England ◽  
Social Factors ◽  
Mixed Effects ◽  
Regression Modeling ◽  
Linear Mixed Effects ◽  
Eastern Massachusetts ◽  
Over Time

This is the first of two chapters (Chapters 6 and 7) that analyze fieldwork results in eastern Massachusetts. This chapter analyzes the eastern Massachusetts “Hub” region as a whole, providing a statistical overview of speakers interviewed in the Dartmouth-based fieldwork in this area. It examines the results in terms of major traditional Eastern New England dialect features, including Linear Mixed Effects regression modeling in terms of phonetic environments and social factors like age, gender, social class, and ethnicity. The chapter also plots these dialect features in terms of speakers’ birth year and other factors, showing how these features are changing over time.

scholarly journals PSVI-24 Evolution and risk factors of pulmonary lesions evaluated with thoracic ultrasonography in pre-weaned beef calves at arrival at the rearing facilities

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 208-209
Author(s):  
Carolina Tejero ◽  
Maria Devant ◽  
Joan Pujols ◽  
Sonia Marti
Keyword(s):  
Risk Factors ◽  
Respiratory Disease ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Beef Calves ◽  
Pulmonary Lesions ◽  
Current Health ◽  
D 12 ◽  
Over Time ◽  
Transport Type

Abstract Bovine respiratory disease (BRD) is one of the main health problems in in pre-weaning calves at rearing farms. The aim of this study was to evaluate the evolution of pulmonary lesions using a thoracic ultrasonography and its association with predictable risk factors. Thoracic ultrasonography was performed in 811 calves (45–56 kg of BW and 3–4 wk of age) on 5 different rearing facilities at arrival and from d 12 to d 27 after arrival. Thoracic ultrasonography score was classified based on Adams and Buczinski (2016). Weight (light vs heavy), breed (dairy vs crossbred), source (national vs international), season, and number of calves arriving at the facility were recorded and used to evaluate risk factors. Data were analyzed using mixed effects models. At arrival 31% of the calvespresented pulmonary lesions, 21% were mild and 10% severe. After 12–27 d the number of calves without lesion decreased (P < 0.001; 70.3 ± 3.93% vs 34.0 ± 3.93%), number of severe lesions increased (P < 0.001; 8.9% ± 4.78% vs 40.1% ± 4.78%), however mild lesions were constant over time. Percentage of severe pulmonary lesions were greater (P < 0.001) when calves arrived in fall than spring, summer and winter; when calf source (P < 0.001) was international than national; and when their breeds (P < 0.001) were crossbred than dairy. A tendency (P = 0.09) was observed with the increase of severe pulmonary lesions with an increase of animals received by batch. At arrival, calves already had pulmonary lesions that increased in severity over time, therefore current health protocols do not mitigate BRD and more attention should be taken on risk factors such as breed, transport type and season.

Polling place changes and political participation: evidence from North Carolina presidential elections, 2008–2016

2020 ◽  
pp. 1-18
Author(s):  
Joshua D. Clinton ◽  
Nick Eubank ◽  
Adriane Fresh ◽  
Michael E. Shepherd
Keyword(s):  
North Carolina ◽  
Political Participation ◽  
Voter Turnout ◽  
Presidential Elections ◽  
Search Costs ◽  
Change Over Time ◽  
Early Voting ◽  
Location Change ◽  
Over Time

Abstract How do changes in Election Day polling place locations affect voter turnout? We study the behavior of more than 2 million eligible voters across three closely-contested presidential elections (2008–2016) in the swing state of North Carolina. Leveraging within-voter variation in polling place location change over time, we demonstrate that polling place changes reduce Election Day voting on average statewide. However, this effect is almost completely offset by substitution into early voting, suggesting that voters, on average, respond to a change in their polling place by choosing to vote early. While there is heterogeneity in these effects by the distance of the polling place change and the race of the affected voter, the fully offsetting substitution into early voting still obtains. We theorize this is because voters whose polling places change location receive notification mailers, offsetting search costs and priming them to think about the election before election day, driving early voting.

scholarly journals Mobility Impairment in Patients New to Dialysis

2020 ◽  
Vol 51 (9) ◽  
pp. 705-714
Author(s):  
Ranjani N. Moorthi ◽  
William F. Fadel ◽  
Alissa Cranor ◽  
Judy Hindi ◽  
Keith G. Avin ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Risk Factors ◽  
Gait Speed ◽  
Handgrip Strength ◽  
Health Utility ◽  
Mixed Effects ◽  
Mobility Impairment ◽  
Lower Health ◽  
Over Time

Background: Impaired mobility is associated with functional dependence, frailty, and mortality in prevalent patients undergoing dialysis. We investigated risk factors for mobility impairment, (poor gait speed) in patients incident to dialysis, and changes in gait speed over time in a 2-year longitudinal study. Methods: One hundred eighty-three patients enrolled within 6 months of dialysis initiation were followed up 6, 12, and 24 months later. Grip strength, health-related quality of life, and comorbidities were assessed at baseline. Outcomes were (a) baseline gait speed and (b) change in gait speed over time. Gait speed was assessed by 4-meter walk. Multivariate linear regression was used to identify risk factors for low gait speed at baseline. For longitudinal analyses, linear mixed effects modeling with gait speed modeled over time was used as the outcome. Results: Participants were 54.7 ± 12.8 years old, 52.5% men, 73.9% black with mean dialysis vintage of 100.1 ± 46.9 days and median gait speed 0.78 (0.64–0.094) m/s. Lower health utility and grip strength, diabetic nephropathy, and walking aids were associated with lower baseline gait speed. Loss of 0.1 m/s gait speed occurred in 24% of subjects at 1 year. In multivariate mixed effects models, only age, walking aid use, lower health utility, and lower handgrip strength were significantly associated with gait speed loss. Conclusions: In our cohort of incident dialysis patients, overall gait speed is very low and 54.2% of the subjects continue to lose gait speed over 2 years. Older age, lower handgrip strength, and quality of life are risk factors for slowness. Patients at highest risk of poor gait speed can be identified at dialysis initiation to allow targeted implementation of therapeutic options.

scholarly journals Modelling Cyclists’ Multi-Exposure to Air and Noise Pollution with Low-Cost Sensors—The Case of Paris

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 422
Author(s):  
Jérémy Gelb ◽  
Philippe Apparicio
Keyword(s):  
Statistical Models ◽  
Noise Exposure ◽  
Generalized Additive Model ◽  
Low Cost ◽  
Additive Model ◽  
Noise Pollution ◽  
Ventilation Rate ◽  
Mixed Effects ◽  
Mobile Data ◽  
Mobile Data Collection

Cyclists are particularly exposed to air and noise pollution because of their higher ventilation rate and their proximity to traffic. However, few studies have investigated their multi-exposure and have taken into account its real complexity in building statistical models (nonlinearity, pseudo replication, autocorrelation, etc.). We propose here to model cyclists’ exposure to air and noise pollution simultaneously in Paris (France). Specifically, the purpose of this study is to develop a methodology based on an extensive mobile data collection using low-cost sensors to determine which factors of the urban micro-scale environment contribute to cyclists’ multi-exposure and to what extent. To this end, we developed a conceptual framework to define cyclists’ multi-exposure and applied it to a multivariate generalized additive model with mixed effects and temporal autocorrelation. The results show that it is possible to reduce cyclists’ multi-exposure by adapting the planning and development practices of cycling infrastructure, and that this reduction can be substantial for noise exposure.

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