This document outlines a Bayesian statistics project analyzing a database of gender violence patients seen at Colombian health institutions from 2008-2019. The project aims to predict the type of violence experienced using criteria like location, date of consultation, and symptoms. A multinomial logistic regression model will be used to analyze variables like type of social security, case type, and hospitalization from the 56,948 observation database. References are provided to support using Bayesian methods like Stan and Zelig for multinomial logistic regression modeling.

1. Bayesian
Statistics
Project
Faculty of Sciences
Medellin Campus
National University of Colombia
Sofía Cuartas
Daniel Villa

2. Database
Selected database
Objective
Problem statement
and selection of
variables of interest
Model
Description of the model
to be treated
References
Documentation to support
the project
01
02
03
04
Table of contents

3. Database
01
Problem Context

4. gender violence in public
health
Registry of patients seen in health care institutions with a
suspected diagnosis of gender-based violence in public health
surveillance.
January 2008 - December 2019
Secretary of Health.
56,948
observations

5. Objectives
02
research questions to be answered

6. We want to know if the patient's
mode of violence can be explained
and predicted using certain
criteria that will be revealed later.
The database considers the
following kinds of violence:

7. Sexual Abuse
Neglect and
abandonment
Sexual
harassment
Commercial sexual
exploitation
Trafficking
in persons

8. Model
03
Description of the model to be treated

9. Comuna
week
type of social
security system
Case type
Symptom onset date
date of
consult
hospitalized
patient

11. References
04
Documentation to support the project

12. https://rpubs.com/kaz_yos/stan-glm1
http://docs.zeligproject.org/articles/zelig_mlogitbayes.html#:~:te
xt=Use%20Bayesian%20multinomial%20logistic%20regression,
likelihood%20estimation%20of%20this%20model.
https://www.frontiersin.org/articles/10.3389/fninf.2018.00051/full
"G:Mi unidad6to Semestre 2022-1SBayesianaTrabajo
FinalDocumat-RegresionLogisticaMultinomial-2981898.pdf"
"G:Mi unidad6to Semestre 2022-1SBayesianaTrabajo
FinalvanErp_2013.pdf"
"G:Mi unidad6to Semestre 2022-1SBayesianaTrabajo
Finalmatthias,+Journal+manager,+121Fruehwirth.pdf"