Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, you'll extend simple regression to the prediction of a single outcome of interest on the basis of multiple variables. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include multiple logistic regression, the Spline approach, confidence intervals, p-values, multiple Cox regression, adjustment, and effect modification.
Este curso faz parte do Programa de cursos integrados Biostatistics in Public Health
oferecido por
Programa de cursos integrados Biostatistics in Public Health Universidade Johns HopkinsInformações sobre o curso
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Certificados compartilháveis
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100% on-line
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Curso 4 de 4 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível iniciante
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
Aprox. 14 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Turco, Inglês, Espanhol
O que você vai aprender
Practice multiple regression methods to determine relationships between an outcome and multiple predictors
Use the Spline approach for non-linear relationships with continuous predictors
Perform calculations with multiple predictor variables
Habilidades que você terá
effect modifcationProportional Hazards ModelRegression AnalysisSpline approach
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 4 de 4 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível iniciante
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
Aprox. 14 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Italiano, Vietnamita, Coreano, Alemão, Russo, Turco, Inglês, Espanhol
oferecido por
Universidade Johns Hopkins
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Programa - O que você aprenderá com este curso
4 horas para concluir
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression
Within this module, an overview of multiple regression will be provided. Additionally, examples and applications will be examined. A practice quiz is provided to test your knowledge before completing the graded quiz.
4 horas para concluir
9 vídeos (Total 177 mín.), 2 leituras, 2 testes
9 videos
Multiple Linear Regression: Some Examples23min
Multiple Linear Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates14min
Estimate Group Means and Mean Differences for Groups Who Differ in More than One Predictor with Multiple Linear Regression9min
The “Linearity” Assumption and Estimating Amount of Variability Explained by Multiple Predictors21min
Examples from the Literature21min
Investigating Effect Modification with Multiple Linear Regression (Forthcoming)20min
Investigating Effect Modification with Multiple Linear Regression—More Examples, For Those Interested18min
Additional Examples of Multiple Linear Regression34min
2 leituras
Solutions to Practice Quiz on Multiple Linear Regression10min
Solutions to Summative Quiz 110min
2 exercícios práticos
Practice Quiz: An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30min
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30min
4 horas para concluir
Multiple Logistic Regression
Module two covers examples of multiple logistic regression, basics of model estimates, and a discussion of effect modification. In addition to lectures, you will also be completing a practice quiz and graded quiz.
4 horas para concluir
8 vídeos (Total 173 mín.), 2 leituras, 2 testes
8 videos
Multiple Logistic Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates18min
Estimating Group Odds and Proportions, and Odds Ratios for Groups Who Differ in More than One Predictor with Multiple Linear Regression24min
The “Linearity” Assumption and A Brief Note about Prediction with Multiple Logistic Regression27min
Examples from the Literature26min
Investigating Effect Modification with Multiple Logistic Regression, Part 118min
Investigating Effect Modification with Multiple Logistic Regression, Part 210min
Additional Examples21min
2 leituras
Solutions to Practice Quiz Items 1-910min
Solutions to Quiz on Logistic Regression10min
2 exercícios práticos
Practice Quiz: Multiple Logistic Regression30min
Multiple Logistic Regression30min
3 horas para concluir
Multiple Cox Regression
The last module for this class focuses on multiple Cox regression, the “Linearity” assumption, examples, and applications. You will complete a practice quiz, graded quiz, and project.
3 horas para concluir
5 vídeos (Total 95 mín.), 2 leituras, 2 testes
5 videos
Some Examples17min
Basics of Model Estimation and Handling Uncertainty in the Resulting Estimates18min
Estimating Hazard Ratios for Groups who Differ in more than one Predictor with Multiple Cox Regression12min
The "Linearity" Assumption and Prediction with Multiple Cox Regression21min
Examples from the Literature25min
2 leituras
Soluitons To Multiple Cox Regression Practice Quiz10min
Solutions: Summative Quiz (Multiple Cox Regression)10min
2 exercícios práticos
Practice Quiz: Multiple Cox Regression30min
Multiple Cox Regression, and Course Concepts30min
2 horas para concluir
Course Project
During this module, you get the chance to demonstrate what you've learned by putting yourself in the shoes of biostatistical consultant on two different studies, one about self-administration of injectable contraception and one about medical appointment scheduling in Brazil. The two research teams have asked you to help them interpret previously published results in order to inform the planning of their own studies. If you've already taken other courses in this specialization, then this scenario will be familiar.
2 horas para concluir
1 leitura
1 leituras
Biostatistical Consulting Project10min
1 exercício prático
Project2h
Avaliações
Principais avaliações do MULTIPLE REGRESSION ANALYSIS IN PUBLIC HEALTH
por DK25 de Jul de 2020
lecture pattern gives enthusiasm in learning and solving quiz sessions. explanations for the solutions gives immense strength and confidence in learning. Excellant course and marvellous experience
por BV23 de Abr de 2020
This course covers all types of Multiple Regressions. Instructor explained the complex topics in simple language. Relevant examples from clinical field and thorough explanation by the Instructor.
por UK29 de Jul de 2019
The course is well structured. The numerous examples and practice questions help the student apply the concepts learned. I love the fact that almost every question was from a real article.
por AA20 de Jun de 2020
Excellent Course. The video lectures are thorough and provide many examples to help explain the concepts. If this professor produces more courses, I will certainly take them.
Sobre Programa de cursos integrados Biostatistics in Public Health
This specialization is intended for public health and healthcare professionals, researchers, data analysts, social workers, and others who need a comprehensive concepts-centric biostatistics primer. Those who complete the specialization will be able to read and respond to the scientific literature, including the Methods and Results sections, in public health, medicine, biological science, and related fields. Successful learners will also be prepared to participate as part of a research team.
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