Maestría Estadística Aplicada

URI permanente para esta colecciónhttp://hdl.handle.net/11634/13159

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Aproximación espacial sobre la pobreza monetaria en Bogotá: una aplicación desde la estimación en áreas pequeñas
(Universidad Santo Tomás, 2024-12-13) Durán Gil, Carlos Alberto; Téllez Piñérez, Cristian; Ortiz Rico, Andrés Felipe; Universidad Santo Tomás
The incidence of monetary poverty is a fundamental indicator in assessing the socioeconomic conditions of the population, and its monitoring is part of the Agenda for the Sustainable Development Goals (SDG). In response to the growing need for detailed information for monitoring purposes, this work develops a methodology focused on small area estimation (SAE) with the aim of achieving disaggregations and maps of monetary poverty in households at the level of the zonal planning unit (UPZ for its acronym in Spanish) in the city of Bogotá. Based on the microdata derived from the Integrated Household Survey (GEIH for its acronym in Spanish) for the year 2021, and the use of 25 covariates obtained from geospatial data, Fay-Herriot models are carried out in order to obtain the best linear unbiased estimators (EBLUP) along with their robust spatial extensions (RSEBLUP), comparing their precisions through marginal errors. The results obtained show that the covariates used in the models are adequate predictors of monetary poverty, and that the addition of the spatial component to the model, applying robust processes, provides better precision compared to the direct estimates resulting from the survey.
Clasificación De Especies: Un Enfoque Para Mejorar La Precisión En La Identificación De Serpientes
(Universidad Santo Tomás, 2024) Ruiz Sandoval, Diego Ferney; Bru Cordero, Osnamir; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001425196; https://scholar.google.com/citations?user=jtoOoEIAAAAJ&hl=es&oi=ao; https://orcid.org/0000-0001-9425-9475
This work aims to apply modern data analysis techniques, particularly neural networks, to improve the classification of snake species in Colombia, using information obtained from records and observations shared on social platforms like Facebook, where users document sightings and characteristics of snakes. In addition to the accurate classification of species, the study is expected to identify patterns in the geographical distribution and behaviors of these species. While neural networks offer a significant advantage in terms of accuracy, they have the disadvantage of being ”black box”models, making them difficult to interpret. Despite this limitation, the study builds on evidence from previous research and data from the online community, with the expectation of improving both species identification and understanding of distribution patterns, contributing to the development of more effective conservation strategies and the protection of biodiversity in Colombia.
Automatización en la toma de decisiones para procesos de inversión en la bolsa de valores de Colombia. una aplicación de modelos avanzados de predicción, modelos de optimización de portafolio y teoría de juegos.
(Universidad Santo Tomás, 2024-11-06) Arevalo Herrera, Carlos Mario; Pineda Rios, Wilmer Dario; Universidad Santo Tomás
The stock market is a key driver for the economy. In this paper, we investigate the behavior of stocks in the Colombian Stock Exchange using linear dynamic models, random forests, and neural networks to identify moments of significant growth in their utility. We then apply the Sharpe and Markowitz models to the stocks projected to grow, in order to determine the optimal percentage of investment in each one. The results show that the Sharpe optimization model, applied to the stocks predicted by random forests, offers the highest return (24.4% monthly), followed by the Markowitz model applied to the stocks predicted by random forests (22.7%) and the traditional Sharpe model (9.9%). This underlines the importance of integrating advanced prediction models and considering both historical performance and future projections to achieve more effective investment.
Ecuaciones de Estimación Generalizada para Modelar el Efecto Inward-Outward en Español
(Universidad Santo Tomás, 2024-12-01) Macías Bohórquez, Ricardo; Ortiz Rico, Andres Felipe; Ortiz Rico, Andres Felipe; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000650579; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001821332; https://scholar.google.com/citations?user=xDebiZgAAAAJ&hl=es&oi=ao; https://orcid.org/0000-0002-0217-8756
The Inward-Outward effect suggests that oral articulatory movements can influence psychological processes, such as perception and trust, particularly in the context of e-commerce. This study replicated and extended the findings of Silva and Topolinski (2018) to investigate whether consumers perceive providers with names that generate “inward” articulatory movements (into the mouth) as more trustworthy compared to those with “outward” movements (out of the mouth). An experiment was designed involving 156 university undergraduate and graduate students selected by convenience sampling (91 women, 65 men, with a mean age of 26.13 years and a standard deviation of 7.77 years). Participants chose between pairs of Inward-Outward names and then evaluated the trustworthiness of the associated sellers. The results, modeled using Generalized Estimating Equations (GEE), showed that inward names were perceived as significantly more trustworthy than outward names (p < 0.001). However, no direct relationship was found between initial preference and final choices, suggesting that the Inward-Outward effect may function as a heuristic based on articulatory fluency and presentation order, rather than a conscious decision-making process. Ergonomic implications are discussed, and future research is suggested to explore the role of factors such as interface positioning and response time in the perception of trust.
Análisis Estadístico para el Cálculo de la UPC Utilizando Modelos Lineales Generalizados
(Universidad Santo Tomás, 2024) Caballero Otálora, Adriana Marcela; Pineda-Ríos, Wilmer Dario; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000294543; https://orcid.org/0000-0001-7774-951X; https://orcid.org/0000-0003-3710-923X
The correct estimation of an insurance premium ensures that, when a claim is filed, the insurance company is capable of responding under the agreed conditions. Colombia's healthcare system adheres to this principle, with the Ministry of Health and Social Protection responsible for estimating the amount to be allocated to each EPS (Health Promotion Entity), ensuring coverage of health risks and financial risks, promoting financial sustainability, and providing comprehensive care to affiliates. Therefore, it is necessary to approach models with predictive capabilities that allow for the proper distribution of resources. Generalized linear models will be explored to adequately address the country's needs, modeling frequency and severity independently, with the aim of reducing potential risk selection in the system.
Propuesta de Estimación de Características Sensibles Utilizando Métodos Bayesianos para la Técnica de Conteo de Ítems de Hussain
(Universidad Santo Tomás, 2023-11-17) Moreno Ibagué, Anyi Biviana; Cruz Pérez, Edwin Andrés; Pineda Ríos, Wilmer Dario; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001525346; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000101890; https://scholar.google.es/citations?hl=es&user=e6Oad5sAAAAJ; https://scholar.google.es/citations?hl=es&user=5KmOl5oAAAAJ; https://orcid.org/0000-0003-2134-0058; https://orcid.org/0000-0001-7774-951X
This paper presents a Bayesian proposal to improve the Hussain estimator in the Item Counting Technique (ICT), with the objective of eliminating or reducing the proportion of negative estimates that this estimator presents when a particular sensitive characteristic is to be studied. An analytical estimator is proposed using as prior distributions a beta distribution and the uniform distribution, the analysis is carried out via simulation by proposing different scenarios for the number of questions in the questionnaire, sample size and the known proportion of non-sensitive questions, obtaining finally the total elimination of the negative estimates for the proportion of people who have a sensitive characteristic of interest, presenting significant reductions in the estimated coefficient of variation.
Deserción Universitaria en Poblaciones Vulnerables. Estudio de Caso Sobre el Programa "Jóvenes a la U" en Bogotá.
(Universidad Santo Tomás, 2024) Pachón Ariza, Jose Daniel; Pineda Rios, Wilmer; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001566310; https://orcid.org/0000-0001-7774-951X
Automatización Cartográfica: Integración de Tecnologías para la Exportación Automatizada de Mapas
(Universidad Santo Tomás, 2023-11-13) Morera Robles, Joel Fernando; Ortiz Rico, Andrés Felipe; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000650579; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000037382; https://scholar.google.com/citations?hl=es&user=OuVxcUgAAAAJ
Reincidencia de la Población Carcelaria a Cargo del Instituto Nacional Penitenciario en Colombia; Caracterización y Modelamiento Estadístico
(Universidad Santo Tomás, 2023) Diaz Fonseca, Raúl Andrés; Pachecho Lopez, Mario Jose; Universidad Santo Tomás
This document presents a comprehensive analysis of the prison population in Colombia, with a particular focus on prison recidivism and the historical count of recidivism per individual. Using data provided by the National Penitentiary Institute of Colombia (INPEC), various social, demographic, and judicial characteristics will be explored to identify recurring profiles. Given the inflation of zeros in the recidivism distribution, different statistical models, including zero-inflated count models and zero-truncated count models, such as Poisson Regression, Negative Binomial Regression, Zero-Inflated Poisson (ZIP), Zero- Inflated Negative Binomial, Zero-Truncated Poisson, and Zero-Truncated Negative Binomial, will be compared and applied. Additionally, a recidivism score will be estimated to identify profiles prone to criminal recidivism. This study aims to shed light on the dynamics of prison recidivism in Colombia and provide insights that can contribute to the formulation of policies and reintegration programs within the country’s penal system, aiming for the best prediction and accurate recidivism counts.
Clasificación Litológica en Afloramientos de Rocas Mediante Técnicas de Aprendizaje Automático Usando Imágenes Satelitales
(Universidad Santo Tomás, 2024-01-29) Rodríguez Arias, Elizabeth; Tesón Del Hoyo, Eliseo; Rubriche Cárdenas, Juan Carlos; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001343533; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001457530; https://orcid.org/0000-0001-6812-2838
The application of machine learning techniques to perform terrain characterization from satellite images represents a significant advance in the study of the Earth’s surface. Because of the heterogeneity of rock structures and the difficulties associated with abrupt chan ges in topography, conventional classification possesses a large subjective component, which sometimes can affect the accuracy of the process. The desired result of using machine lear ning techniques in Lithological classification is to generate a tool that besides assisting the classification process, also helps to improve the aspects that may limit the results, such as optimizing processing time, increasing classification accuracy, larger data processing (images with higher spectral and temporal resolution) and to cover larger study areas. The metho dology is developed on the geospatial analysis platform with cloud processing Google Earth Engine (GEE) and it is implemented in four main phases: the first one consists of generating additional variables for the supervised classification model using statistical techniques, image transformation, and spectral enhancement, including the calculation of geological spectral indices and Principal Component Analysis (PCA), as well as incorporating topographic in formation through addition of Digital Terrain Model (DEM), adding together texture data through the Gray Level Matrix Co-occurrence (GLMC), and finally incorporate an additional band of the k-means algorithm no supervised classification. The second phase incorporates algorithm training under the supervision of Random Forest (RF), Support Vector Machine (SVM), Classification and Regression CART and Minimum Distance MD, taking into ac count the variables generated in the first phase together with the field reference information or ground thruth to reproduce several classification models that in the third phase, whichever displays the best performance metrics, is chosen leading to a reliable classification model, then, in the last phase, it will be applied to a surface area with unknown characteristics and lithology providing support information to carry out geological cartography without having required presence of people on site
Análisis del Efecto de la Pandemia de Covid-19 en los Servicios Hospitalarios de una Póliza de Salud Privada Mediante Metodologías de Series de Tiempo con Intervención e Interrumpidas
(Universidad Santo Tomás, 2024-01-23) Ordóñez Manrique, Sergio Alejandro; Moreno López, Edna Carolina; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001381730; https://scholar.google.com/citations?hl=es&user=3HPuekUAAAAJ; https://orcid.org/0000-0002-1364-0096
Time series are often affected by unusual or outlier values, making it necessary to measure the influence of infrequent events or to determine and consider the intervention point affecting the time series for accurate forecasting of future values and model parameter estimation. The 2019-2020 COVID-19 pandemic, an unexpected event in the 21st century, was an intervention event that impacted the normal provision of healthcare services. This study applied time series models with intervention and interrupted time series analysis to assess how the COVID-19 pandemic affected hospitalization services. Forecast scenarios were created to compare the observed reality with what would have been expected without the pandemic. The results demonstrate that the inclusion of time series methodologies with interventions and interruptions significantly improves the accuracy of forecasts, highlighting the importance of these methods in effective healthcare sector planning during crises.
Patrones espaciales y dinámica de un bosque subandino en el departamento del Meta (Colombia)
(Universidad Santo Tomás, 2023) Cepeda Buitrago, Leidy Marcela; Pineda Rios, Wilmer; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199; https://scholar.google.com/citations?hl=es&user=5KmOl5oAAAAJ; https://orcid.org/0000-0001-7774-951X
Monitoring forests through permanent plots allows understanding aspects such as dynamics, composition, structure, and the distribution of individuals. This study analyzes spatial distribution patterns, dynamics, and spatiotemporal processes of a permanent plot established in the Las Palmeras Natural Reserve, Cubarral (Meta, Colombia). By analyzing data collected over seven different years, individuals with a diameter at breast height greater than or equal to 10 cm (DBH ≥ 10 cm) were examined, including trees, tree ferns, and palms. The results show a peak in mortality and recruitment in the year 2017; however, supplementing the analysis with rates from other evaluated years suggests that the forest is approaching dynamic equilibrium by 2023. Additionally, individual dynamics indicate that the plot is in a mature forest that experienced disturbance. Although a random distribution was identified for annual data, spatiotemporal analysis reveals an aggregation pattern. The findings of this study significantly contribute to understanding forest dynamics in this region and provide valuable information that can support future management and conservation strategies for the reserve.
Perspectiva Bayesiana para Estimar el Efecto de las Condiciones Edafoclimáticas Sobre el Comportamiento Fisiológico de la Quinua
(Universidad Santo Tomás, 2024-01-19) Moreno Amaya, Lizeth Andrea; Pineda Rios, Wilmer Dario; Garcia Parra, Miguel Angel; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001518896; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001705364; https://scholar.google.com/citations?hl=es&user=5KmOl5oAAAAJ; https://scholar.google.com/citations?hl=es&user=-Fhy-mcAAAAJ; https://scholar.google.com/citations?hl=es&user=_9i6HskAAAAJ; https://orcid.org/0000-0001-7774-951X; https://orcid.org/0000-0001-6913-7855
The edaphoclimatic conditions are essential for the optimal development of quinoa, as they influence its physiological performance. Therefore, it is necessary to identify cultivars that adapt and remain stable in the interaction between cultivars and the environment. For this reason, this study aimed to analyze the physiological performance of seven quinoa cultivars in three municipalities of the Boyacá department, Colombia, using the frequentist and Bayesian methodology of the additive main effects and multiplicative interaction (AMMI) model. According to the results, Bayesian estimation showed better predictive capacity as well as better performance in the study of adaptability and stability. In this regard, the cultivar Pasankalla stood out in terms of main effect and stability. The adaptability of cultivars to specific locations was also observed, allowing for the utilization of the positive effect of interaction, as evidenced by the Bayesian model.
Estimación de los indicadores de Ingreso promedio y la tasa de desempleo municipal en Cundinamarca en el 2017 utilizando áreas pequeñas y transformaciones funcionales
(Universidad Santo Tomás, 2023) Guerrero Beltran, Jonnathan; Ortiz Rico, Andres Felipe; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000650579; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000085895; https://scholar.google.com/citations?hl=es&user=OuVxcUgAAAAJ
Small Area Estimation (SAE) aims to improve estimates in situations where sampling errors are significantly high, making it difficult to draw reliable conclusions. In this study, the SAE methodology is used to estimate the average income and unemployment rate at the municipal level in Cundinamarca, using data from the 2017 multipurpose survey. Transformations are applied to the data and the advantages and disadvantages of these transformations are analyzed. Based on these transformations, the most relevant auxiliary variables are selected for each type of transformation, and the quality of the estimates is evaluated using the coefficient of variation. As a result, it is concluded that the use of the Fay-Herriot model with transformations in the data reduces the value of the coefficient of variation, which suggests that the transformation of the data is a viable option to improve the quality of the estimates of the indicators of interest. In addition, the statistical software R is used as a work environment for data processing.
Clasificación de series de tiempo con datos funcionales y técnicas de Machine Learning: una aproximación para el Índice de Desarrollo Humano
(Universidad Santo Tomás, 2023) Rivera Gómez, Fredy Alexander; Pineda Rios, Wilmer; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199; https://scholar.google.com/citations?hl=es&user=5KmOl5oAAAAJ; https://orcid.org/0000-0001-7774-951X
Inequality and human development are two social aspects that have endured over time, capturing the interest of nations and various international organizations in measuring the progress and development of humanity. The United Nations Organization, as an international cooperation entity dedicated to designing comprehensive solutions to ensure the responsible development of nations, established the Human Development Index (HDI) in 1990, through the United Nations Development Program ( UNDP). This index stands as an instrument to evaluate the progress of humanity. In this work, what is necessary to carry out the application of statistical classification techniques with functional data is developed, in order to characterize data functions of the human development index and evaluate the efficiency of this technique under different classification models with this approach. For this, the R environment is used and the different packages currently available ‘fda.usc (Febrero-Bande and Oviedo de la Fuente, 2012), classiFunc ‘(Maierhofer and Pfisterer, 2017), among others.
Un Modelo Alternativo para los Estudios de Homogeneidad en la Producción de Materiales de Referencia
(Universidad Santo Tomás, 2024-01-19) Holguín Agudelo, Katherin; Pineda Rio, Wilmer Darío; Ahumada Forigua, Diego Alejandro; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001454199; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001710990; https://orcid.org/0000-0001-7774-951X
The proper use of reference materials (RMs) is crucial in testing and calibration laboratories, where homogeneous (ensuring the same property value) and stable materials (Centro Español de Metrología (2012)) are required to validate measurement methods, calibrate equipment, and ensure the validity of results. ISO Guide 35:2017 defines the homogeneity uncertainty (u_{homo}) as the uncertainty associated with the detected heterogeneity both between and within RMs during their production process. It is suggested to estimate this uncertainty using experimental designs and Analysis of Variance (ANOVA). However, the applicability and interpretation of this technique may pose challenges when asymmetric behaviors are observed among the analyzed bottles. Assuming normality can lead to overestimation or underestimation of this uncertainty, potentially resulting in incorrect decisions and costly consequences when accepting or rejecting a batch. This could lead to a loss of trust from clients and even the loss of laboratory accreditation or recognition. This study proposes an alternative model that employs the Skew-Normal distribution to estimate the effect of random factors among bottles. A shape parameter in the distribution allows quantifying asymmetry or deviations from the central value. Quasi-Newton optimization algorithms (L-BFGSB) were used, and optionally, in case of convergence limitations, the genetic algorithm (NSGA-II) was employed to maximize the likelihood function and find optimal values for μ, s^{2}_{τ} , s^{2}_{e}, and α. This alternative model aims to assess potential biases affecting method precision and, consequently, the homogeneity of a reference material. The application focused on producing a reference material for elements in water, evaluating the proposed model at different levels of induced homogeneity through gravimetric analysis. The proposed model incorporates the shape parameter α in the quantification of s^{2}_{τ}, adjusting this estimation without overestimating the variance. It was concluded that this approach allows for uncertainty estimates comparable to traditional techniques (ANOVA and DerSimonian-Lair) and is suitable for cases where the normality assumptions for the effect between bottles are not met. Although it has limitations in the presence of many outliers related to heterogeneity within the bottle, the model proves suitable for its intended purpose.
Análisis del Rendimiento Académico de los Estudiantes de Pregrado en Estadística de la Universidad Santo Tomás Mediante Ecuaciones Estructurales
(Universidad Santo Tomás, 2024-01-22) Camargo Colmenares, Vïctor Raúl; Gómez Fonseca, Lida Rubiela; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000125977; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001589989; https://scholar.google.com/citations?hl=es&user=uwl_sDgAAAAJ; https://orcid.org/0000-0002-3597-728X
Universities play a fundamental role in social transformation and face some challenges to carry out their mission, therefore, it is of great interest to analyze the interaction of factors that influence the academic achievement of students. The objective of this research was to develop a structural equation model to analyze the factors associated with academic achievement in undergraduate students of the Statistics program at the Universidad Santo Tomás (USTA). This work was previously submitted and approved by the University Ethics Committee. The information was collected from a sample of 128 students during the first semester of 2023. Three questionnaires were used: Self-concept Form 5 (AF-5), the Questionnaire for the Evaluation of Academic Goals (C.M.A-II) and finally, the Motivation and Learning Strategies Questionnaire Short Form (MSLQ-SF). Based on the model proposed by \cite{veas} that relates cognitive and non-cognitive variables. A structural equation model is used as an analysis tool, since it allows complex interactions between multiple variables to be analyzed, and in turn allows theories or hypotheses to be tested and validated. Thus, the results of this research show a structural equation model, where the latent Learning Strategies (made up of Cognitive Strategies, Metacognitive Strategies and Resource Management), showed a significant contribution to academic achievement. On the other hand, the latent variables of Self-concept and Learning Strategies do not turn out to have a significant relationship, and they also presented adequate goodness of fit: Chi Square Ratio (1.76), RMSEA (0.077) with a CI (0.056-0.098) and a p-value of 0.021, SRMR(0.09), CFI(0.923) and TLI(0.9).
Identificación de factores que inciden en las distintas prácticas de violencia en el noviazgo empleando Análisis Factorial Múltiple y Análisis Clúster: una aplicación en dos instituciones universitarias en Bogotá D.C.
(Universidad Santo Tomás, 2023) Nieto Pinto, Gabriel José; Pacheco, Mario; Universidad Santo Tomás; https://orcid.org/0000-0003-4752-703X
Violence in the context of dating relationships is a problem that has been growing in recent years. Unfortunately, in Colombia and in many Latin American countries, it is a poorly studied topic. However, various studies conducted primarily in the United States and Europe suggest that the presence of violence during this stage significantly increases the likelihood of its replication in marriage or cohabiting relationships, thus affecting entire families. Most studies on this topic propose different variables believed to directly influence the occurrence of violence within dating relationships but in a theoretical manner. For this reason, the present study conducted at two universities in the city of Bogotá, it aims to validate these variables using statistical tools such as Multiple Factor Analysis and Cluster Analysis. The ultimate goal is to construct a violence index that can identify individuals at risk of experiencing violence in a dating relationship.
Índice Multivariado de Medición del Conflicto Interno Colombiano
(Universidad Santo Tomás, 2023-09-29) Mateus Cetina, Yirdley Andrea; Rodríguez Pinzón, Heivar Yesid; Bermúdez Rubio, Dagoberto; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000014678; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000014751; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001256491; https://scholar.google.com/citations?hl=es&user=9gC738EAAAAJ; https://orcid.org/0000-0002-2651-5665; https://orcid.org/0000-0002-9553-0455
This document aims to contribute to the study of territorial conflict through measurement tools, which have not been developed for the study of armed conflict in Colombia. The goal is to provide analytical resources that better align with the specificity of each selected variable related to the time of the conflict under study. The result of this research will be the Multivariate Index for Measuring Colombian Internal Conflict, which will assess the level of conflict in each location we analyze after the signing of the agreements. Currently, Colombia lacks such a study, particularly in the context of territorial conflict. It is known that there are similar measurements, but none with the orientation of the current research. A mixed methodology was employed. Firstly, an examination of existing information from studies and research on both the Colombian conflict and the peace process was conducted. Additionally, a principal component analysis was performed to reduce the information, followed by the application of a multiple regression model, which allowed us to determine that there has been an escalation of the conflict from 2014 to 2021.
Estimación del Rendimiento Medio en las Pruebas PISA 2018. Un Enfoque Espacial Desde la Estimación en Áreas Pequeñas
(Universidad Santo Tomás, 2023-09-15) Jiménez Coley, Cupertino; Tellez Piñerez, Cristian Fernando; Universidad Santo Tomás; https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000016463; https://orcid.org/0000-0003-3869-1831; https://orcid.org/0000-0002-0805-0817
Estimating students' abilities in PISA tests is done using plausible values obtained through a three-parameter logistic model. With this methodology, only the information captured in the tests is taken into account, and estimates can only be made for countries and economies belonging to the OECD (domains) that were sampled. To improve the precision of the estimates and be able to make estimates in unsampled domains that have available and reliable auxiliary information, Tellez (2020) proposed using the small area estimation methodology through a Fay-Herriot model. This methodology incorporates external auxiliary information captured in addition to the test and allows for more precise estimates. In this research, the methodology proposed by Tellez (2020) is extended by including spatial variability in the small area estimation technique. This is achieved by using the spatial Fay-Herriot model, which takes into account the spatial autocorrelation among domains. This approach is specifically applied to the reading and mathematics tests of PISA 2018. The auxiliary information used in the spatial Fay-Herriot model includes variables associated with education, science, technology, sociodemographic characteristics, economy, infrastructure, and development. These auxiliary variables provide additional information to improve the precision of the estimates of students' abilities in the domains.

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