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We used a method of spatial epidemiology that applies generalized additive models (GAMs) to assess the spatial variation of disease in a region while simultaneously adjusting for other geographically distributed individual-level factors [ 17, 18] such as maternal education, age, and smoking.
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Gaussian applied generalized least squares method to radar data processing in the early nineteenth century.
We applied generalized linear models and use versus availability analyses to examine specific hypotheses regarding the potential drivers of rural residential development.
Recent research has developed spatio-temporal approaches that apply Generalized Additive Models (GAM) to combine spatial, temporal, and other (e.g., demographic) features for prediction.
We applied generalized multilevel path models to investigate multivariate causal hypotheses that environmental effects on population stability of a macrophyte species - Potamogeton maackianus - are mediated by physiological and morphological traits variability.
We applied generalized linear regression models with HR and HRV as response variables and chest activity, time of day, season, distance traveled, and distance to human settlements from GPS positions recorded every 30 min as potential explanatory variables.
This study applied generalized additive modeling (GAM) on data from Colorado's QRIS in order to identify thresholds on several components of Colorado's QRIS, including the Early Childhood Environment Rating Scale-Revised (ECERS-R), classroom ratios, and staff credentials.
Using a time-series study design, we applied generalized additive model to assess the short-term association of 10-μg/m3 increase in PM10 with daily YLL and mortality, adjusting for long-term trend and seasonality, mean temperature, relative humidity, public holiday, and day of the week.
In this paper, we apply generalized'surrogate problem' methodology that is based on an on-line control scheme which transforms the problem into a'surrogate' continuous optimization problem and proceeds to solve the latter using standard gradient-based approaches while simultaneously updating both actual and surrogate system states.
We measured the number of tadpoles consumed by predators over time, and applied generalized linear model (GLM) analyses for each predator-prey combination, including both "time" and "predator ID" as sources of variation in our models.
To account for the facts that some applicants made a tender for several concessions, and several concession units had multiple applicants, we applied Generalized Estimating Equations (GEE) to account for the respective correlation structure in the models for the area-based fees offered by the applicants, and for the probability of the applicants for winning the solicited concession unit [25].
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