Search results for "regression"

Investigation of superspreading COVID-19 outbreak events in meat and poultry processing plants in Germany: A cross-sectional study.

2020

Since May 2020, several COVID-19 outbreaks have occurred in the German meat industry despite various protective measures, and temperature and ventilation conditions were considered as possible high-risk factors. This cross-sectional study examined meat and poultry plants to examine possible risk factors. Companies completed a self-administered questionnaire on the work environment and protective measures taken to prevent SARS-CoV-2 infection. Multivariable logistic regression analysis adjusted for the possibility to distance at least 1.5 meters, break rules, and employment status was performed to identify risk factors associated with COVID-19 cases. Twenty-two meat and poultry plants with 1…

Relationship between erythemal UV and broadband solar irradiation at high altitude in Northwestern Argentina

2018

An analysis of the broadband solar irradiation, IT, and the erythemal UV irradiation, IUVER, has been performed using the measurements made from 2013 to 2015 at three sites located at altitudes over 1000 m a.s.l. In Northwestern Argentina (Salta, El Rosal, and Tolar Grande). The main objective of this paper is to determine a relationship between IT and IUVER, which would allow to estimate IUVER from IT in places with few IUVER measurements available, and especially in those where is important to establish adequate photoprotection measures given their dense population and location at high altitude. The relationship between the daily values of IUVER and IT has been fitted to a linear regressi…

Measurement and analysis of broadband UVB solar radiation in Spain.

2012

Measurements of broadband UVB irradiance (290-315 nm) at 14 locations in Spain for the period 2000-2009 have been used to generate instantaneous, hourly and daily values of irradiance (W m(-2)) and radiant exposure (kJ m(-2)). These measurements, and its statistical indices, have been analyzed. For the UVB irradiance, the values corresponding to July (maximum) and December (minimum) have been analyzed as representative of the year during the whole period for all locations. For the UVB radiant exposure, the temporal evolution of daily values has been evaluated for all locations to estimate an average yearly behavior. The accumulated radiant exposure for an average year has also been studied …

Control of matrix interferences by the multiple linear regression model in the determination of arsenic, antimony and tin in lead pellets by inductiv…

2002

A multiple linear regression technique was used to evaluate the matrix interferences in the determination of hydride-forming elements in lead shotgun pellets by inductively coupled plasma atomic emission spectrometry. The determination of arsenic, antimony, and tin in SRM C2416 (Bullet Lead) by ICP-AES failed to obtain the certified concentrations at the 95% level of confidence using the t-test. However, it proved possible, by using the multiple linear regression technique, to correct the concentrations of all three elements to a statistically acceptable level. This method of correction is based on the multiple regression line obtained from the analysis of 19 synthetic mixtures of matrix el…

Very early phonological and language skills: estimating individual risk of reading disability

2007

Background: Analyses from the JyvaskylaLongitudinal Study of Dyslexia project show that the key childhood predictors (phonological awareness, short-term memory, rapid naming, expressive vocabu- lary, pseudoword repetition, and letter naming) of dyslexia differentiate the group with reading disability (n ¼ 46) and the group without reading problems (n ¼ 152) at the end of the 2nd grade. These measures were employed at the ages of 3.5, 4.5 and 5.5 years and information regarding the familial risk of dyslexia was used to find the most sensitive indices of an individual child's risk for reading disabil- ity. Methods: Age-specific and across-age logistic regression models were constructed to pro…

Antibiotic use and associated factors in a large sample of hospitalised older people

2019

Objectives: The aims of this study were to assess (i) the prevalence of antibiotic use, (ii) factors associated with their use and (iii) the association with in-hospital mortality in a large sample of hospitalised older people in Italy.Methods: Data were obtained from the 2010-2017 REPOSI register held in more than 100 internal medicine and geriatric wards in Italy. Patients aged >= 65 years with at least one antibiotic prescription during their hospitalisation were selected. Multivariable logistic regression models were used to determine factors associated with antibiotic use.Results: A total of 5442 older patients were included in the analysis, of whom 2786 (51.2%) were prescribed anti…

The student talent in a random effects Quantile Regression Model for university performance

2013

This paper is a development of a previous work on performance of Italian university students. A Quantile Regression was carried out on a proposed performance indicator, based on a transformation of the median of the marks weighted by credits. Results suggested to investigate the role of students peculiar features on their performance, measured by the transformation of the weighted marks. Therefore, a random intercept Quantile Regression model is fitted on real data concerning graduates over the legal university duration set in Italy, enrolled in 2002 in two Degree Courses of the University of Palermo. Results show that the student performance seems to be influenced by the student's aptitude…

Fitting linear models and generalized linear models with large data sets in R

2009

We present an estimating algorithm to fit linear and generalized linear models not involving the QR decomposition. Some new R functions are presented and discussed. For large data sets, comparisons with respect to the well-known lm() and glm(), as well as to biglm() and bigglm() from the package biglm, show that the proposed functions speed up computation while preserving numerical stability and accuracy

L'aspetto clinico-psicologico

2010

A kernel regression approach to cloud and shadow detection in multitemporal images

2013

Earth observation satellites will provide in the next years time series with enough revisit time allowing a better surface monitoring. In this work, we propose a cloud screening and a cloud shadow detection method based on detecting abrupt changes in the temporal domain. It is considered that the time series follows smooth variations and abrupt changes in certain spectral features will be mainly due to the presence of clouds or cloud shadows. The method is based on linear and nonlinear regression analysis; in particular we focus on the regularized least squares and kernel regression methods. Experiments are carried out using Landsat 5 TM time series acquired over Albacete (Spain), and compa…