Search results for "regression model"
showing 10 items of 53 documents
Effects of Digital Elevation Model resolution on evaluation of landslide susceptibility with a logistic regression model.
2013
The use of statistical methods together with the GIS technologies is currently one of the most efficient tools in the assessment of landslide susceptibility. The correlation between the physical phenomenon and its triggering factors depends on several factors, including the resolution at which the elevation data are represented in a Digital Elevation Model (DEM). The resolution becomes increasingly important as the use of DEM data is extended for spatial prediction of terrain attributes such as slope, aspect, plan and profile curvature, etc., which are considered as triggering factors of the landslides. Many methods exist in scientific literature to capture and model the correlation between…
Modeling Return to Education in Heterogeneous Populations: An Application to Italy
2019
The Mincer human capital earnings function is a regression model that relates individual’s earnings to schooling and experience. It has been used to explain individual behavior with respect to educational choices and to indicate productivity on a large number of countries and across many different demographic groups. However, recent empirical studies have shown that often the population of interest embed latent homogeneous subpopulations, with different returns to education across subpopulations, rendering a single Mincer’s regression inadequate. Moreover, whatever (concomitant) information is available about the nature of such a heterogeneity, it should be incorporated in an appropriate ma…
The Influence of Student Abilities and High School on Student Growth: A Case Study of Chinese National College Entrance Exam
2019
Enabled by available educational data and data mining techniques, educational data analysis has become a hot topic. Current researches mainly focus on the prediction of problems and performance rather than revealing the underlying causal relationships. Based on a unique exam data, we extracted the abilities of examinee from HSEE (High School Entrance Exam) based on the knowledge of educational experts, then we measured student growth from middle school to high school in total score and subject scores. We studied the impact of high school ranking and student abilities of HSEE on student growth by multiple linear regression model, in which high school ranking is divided into 5 levels, Level 1…
Sparse relative risk survival modelling
2016
Cancer survival is thought to closed linked to the genimic constitution of the tumour. Discovering such signatures will be useful in the diagnosis of the patient and may be used for treatment decisions and perhaps even the development of new treatments. However, genomic data are typically noisy and high-dimensional, often outstripping the number included in the study. Regularized survival models have been proposed to deal with such scenary. These methods typically induce sparsity by means of a coincidental match of the geometry of the convex likelihood and (near) non-convex regularizer.
Using Differential Geometry for Sparse High-Dimensional Risk Regression Models
2023
With the introduction of high-throughput technologies in clinical and epidemiological studies, the need for inferential tools that are able to deal with fat data-structures, i.e., relatively small number of observations compared to the number of features, is becoming more prominent. In this paper we propose an extension of the dgLARS method to high-dimensional risk regression models. The main idea of the proposed method is to use the differential geometric structure of the partial likelihood function in order to select the optimal subset of covariates.
Emotional Intelligence, Empathy, Self-Esteem, and Life Satisfaction in Spanish Adolescents: Regression vs. QCA Models
2020
Adolescence is a complex period, in which the individual is subject to profound emotional, physical, and psychological changes. Healthy development during adolescence is crucial for future positive development; self-esteem and life satisfaction are fundamental. The importance of sociodemographic variables (sex and age), empathy, and emotional intelligence (EI) on self-esteem and life satisfaction was studied, comparing complementary methodologies, regression models, and fuzzy-set qualitative comparative analysis (fsQCA) models. This is a cross-sectional design in a convenience sample of 991 adolescents (528 females, 53.3%; aged between 12 and 19 years; M = 14.01, SD = 1.40) from Spanish sch…
Prospective external validation of a predictive score for postoperative pulmonary complications.
2015
Abstract Background: No externally validated risk score for postoperative pulmonary complications (PPCs) is currently available. The authors tested the generalizability of the Assess Respiratory Risk in Surgical Patients in Catalonia risk score for PPCs in a large European cohort (Prospective Evaluation of a RIsk Score for postoperative pulmonary COmPlications in Europe). Methods: Sixty-three centers recruited 5,859 surgical patients receiving general, neuraxial, or plexus block anesthesia. The Assess Respiratory Risk in Surgical Patients in Catalonia factors (age, preoperative arterial oxygen saturation in air, acute respiratory infection during the previous month, preoperative anemia, upp…
Comparison between statistical and fuzzy approaches for improving diagnostic decision making in patients with chronic nasal symptoms
2014
This paper compares a fuzzy model, expressed in rule-form, with a well known statistical approach (i.e. logistic regression model) for diagnostic decision making in patients with chronic nasal symptoms. The analyses were carried out using a database obtained from a questionnaire administered to 1359 patients with nasal symptoms containing personal data, clinical data and skin prick test (SPT) results. Both the fuzzy model and the logistic regression model developed were validated using a data set obtained from another medical institution. The accuracy of the two models in identifying patients with positive or negative SPT was similar. This study is a preliminary step to the creation of a so…
Wiener-Granger Causality in Network Physiology with Applications to Cardiovascular Control and Neuroscience
2016
Since the operative definition given by C. W. J. Granger of an idea expressed by N. Wiener, the Wiener–Granger causality (WGC) has been one of the most relevant concepts exploited by modern time series analysis. Indeed, in networks formed by multiple components, working according to the notion of segregation and interacting with each other according to the principle of integration, inferring causality has opened a window on the effective connectivity of the network and has linked experimental evidences to functions and mechanisms. This tutorial reviews predictability improvement, information-based and frequency domain methods for inferring WGC among physiological processes from multivariate…
Organizational innovation for SME'S: a model for Latvia
2020
Small and medium-sized enterprises (SMEs) can be a significant source of innovation in small economies. SMEs face challenges of limited capacity, personnel and resources for long-term investments. Additionally, they might not see and understand the benefits of innovation. Implementation of organizational innovation (OI) could give such enterprises an opportunity to improve competitiveness and develop other types of innovation. The purpose of this study is to develop a model, explaining OI through such factors as organizational culture (OC) and knowledge management (KM) in SMEs via an empirical study across various industries. Surveying 600 SMEs in Latvia, the authors explore the contributio…