Acerca de este Curso

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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio

You'll need to have taken the Statistical Thinking and Linear Regression courses in this series or have equivalent knowledge.

Aprox. 12 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

Qué aprenderás

  • Describe a data set from scratch using descriptive statistics and simple graphical methods as a first step for advanced analysis using R software

  • Interpret the output from your analysis and appraise the role of chance and bias as potential explanations

  • Run multiple logistic regression analysis in R and interpret the output

  • Evaluate the model assumptions for multiple logistic regression in R

Habilidades que obtendrás

Logistic RegressionR Programming
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio

You'll need to have taken the Statistical Thinking and Linear Regression courses in this series or have equivalent knowledge.

Aprox. 12 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

Instructor

ofrecido por

Logotipo de Imperial College London

Imperial College London

Comienza a trabajar para obtener tu maestría

Este curso es parte del Global Master of Public Health completamente en línea de Imperial College London. Si eres aceptado en el programa completo, tus cursos cuentan para tu título.

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

2 horas para completar

Introduction to Logistic Regression

2 horas para completar
3 videos (Total 12 minutos), 7 lecturas, 2 cuestionarios
3 videos
Introduction to Logistic Regression5m
Odds and Odds Ratios3m
7 lecturas
About Imperial College & the team5m
How to be successful in this course5m
Grading policy5m
Data set and Glossary10m
Additional Reading10m
Why does linear regression not work with binary outcomes?10m
Odds Ratios and Examples from the Literature10m
2 ejercicios de práctica
Logistic Regression10m
End of Week Quiz10m
Semana
2

Semana 2

3 horas para completar

Logistic Regression in R

3 horas para completar
2 videos (Total 11 minutos), 4 lecturas, 2 cuestionarios
2 videos
Logistic Regression in R5m
4 lecturas
How to Describe Data in R20m
Results of Cross Tabulation20m
Practice in R: Simple Logistic Regression15m
Feedback - Output and Interpretation from Simple Logistic Regression35m
2 ejercicios de práctica
Cross Tabulation30m
Interpreting Simple Logistic Regression30m
Semana
3

Semana 3

3 horas para completar

Running Multiple Logistic Regression in R

3 horas para completar
1 video (Total 4 minutos), 6 lecturas, 1 cuestionario
6 lecturas
Describing your Data and Preparing to Run Multiple Logistic Regression35m
Practice in R: Describing Variables20m
Feedback20m
Practice in R: Running Multiple Logistic Regression15m
Feedback: Multiple Regression Model
Feedback on the Assessment10m
1 ejercicio de práctica
Running A New Logistic Regression Model30m
Semana
4

Semana 4

5 horas para completar

Assessing Model Fit

5 horas para completar
3 videos (Total 17 minutos), 10 lecturas, 3 cuestionarios
3 videos
Overfitting and Non-convergence6m
Summary of the Course3m
10 lecturas
Model Fit in Logistic Regression10m
How to Interpret Model Fit and Performance Information in R10m
Further Reading on Model Fit20m
Summary of Different Ways to Run Multiple Regression10m
Practice in R: Applying Backwards Elimination30m
Feedback: Backwards Elimination20m
Practice in R: Run a Model with Different Predictors30m
Feedback on the New Model10m
Further Reading on Model Selection Methods20m
R Code for the Whole Module20m
3 ejercicios de práctica
Quiz on R’s Default Output for the Model30m
Overfitting and Model Selection20m
End of Course Quiz

Revisiones

Principales revisiones sobre LOGISTIC REGRESSION IN R FOR PUBLIC HEALTH

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Acerca de Programa especializado: Análisis estadístico con R para el área de la salud pública

Statistics are everywhere. The probability it will rain today. Trends over time in unemployment rates. The odds that India will win the next cricket world cup. In sports like football, they started out as a bit of fun but have grown into big business. Statistical analysis also has a key role in medicine, not least in the broad and core discipline of public health. In this specialisation, you’ll take a peek at what medical research is and how – and indeed why – you turn a vague notion into a scientifically testable hypothesis. You’ll learn about key statistical concepts like sampling, uncertainty, variation, missing values and distributions. Then you’ll get your hands dirty with analysing data sets covering some big public health challenges – fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalisation – using R, one of the most widely used and versatile free software packages around. This specialisation consists of four courses – statistical thinking, linear regression, logistic regression and survival analysis – and is part of our upcoming Global Master in Public Health degree, which is due to start in September 2019. The specialisation can be taken independently of the GMPH and will assume no knowledge of statistics or R software. You just need an interest in medical matters and quantitative data....
Análisis estadístico con R para el área de la salud pública

Preguntas Frecuentes

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