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.
Этот курс входит в специализацию ''Специализация Biostatistics in Public Health '
Multiple Regression Analysis in Public Health
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Об этом курсе
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Learner Career Outcomes
Чему вы научитесь
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
Приобретаемые навыки
effect modifcationProportional Hazards ModelRegression AnalysisSpline approach
Learner Career Outcomes
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Начните сейчас и учитесь по собственному графику.
Курс 4 из 4 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Начальный уровень
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
Прибл. 13 часа на выполнение
Предполагаемая нагрузка: 4 weeks, 3-4 hours/week
Английский
Субтитры: Английский
Программа курса: что вы изучите
4 ч. на завершение
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 ч. на завершение
9 видео ((всего 177 мин.)), 2 материалов для самостоятельного изучения, 2 тестов
9 видео
Multiple Linear Regression: Some Examples23мин
Multiple Linear Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates14мин
Estimate Group Means and Mean Differences for Groups Who Differ in More than One Predictor with Multiple Linear Regression9мин
The “Linearity” Assumption and Estimating Amount of Variability Explained by Multiple Predictors21мин
Examples from the Literature21мин
Investigating Effect Modification with Multiple Linear Regression (Forthcoming)20мин
Investigating Effect Modification with Multiple Linear Regression—More Examples, For Those Interested18мин
Additional Examples of Multiple Linear Regression34мин
2 материала для самостоятельного изучения
Solutions to Practice Quiz on Multiple Linear Regression10мин
Solutions to Summative Quiz 110мин
2 практического упражнения
Practice Quiz: An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30мин
An Overview of Multiple Regression for Estimation, Adjustment, and Basic Prediction, and Multiple Linear Regression30мин
4 ч. на завершение
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 ч. на завершение
8 видео ((всего 173 мин.)), 2 материалов для самостоятельного изучения, 2 тестов
8 видео
Multiple Logistic Regression: Basics of Model Estimation, and Handling Uncertainty in the Resulting Estimates18мин
Estimating Group Odds and Proportions, and Odds Ratios for Groups Who Differ in More than One Predictor with Multiple Linear Regression24мин
The “Linearity” Assumption and A Brief Note about Prediction with Multiple Logistic Regression27мин
Examples from the Literature26мин
Investigating Effect Modification with Multiple Logistic Regression, Part 118мин
Investigating Effect Modification with Multiple Logistic Regression, Part 210мин
Additional Examples21мин
2 материала для самостоятельного изучения
Solutions to Practice Quiz Items 1-910мин
Solutions to Quiz on Logistic Regression10мин
2 практического упражнения
Practice Quiz: Multiple Logistic Regression30мин
Multiple Logistic Regression30мин
3 ч. на завершение
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 ч. на завершение
5 видео ((всего 95 мин.)), 2 материалов для самостоятельного изучения, 2 тестов
5 видео
Some Examples17мин
Basics of Model Estimation and Handling Uncertainty in the Resulting Estimates18мин
Estimating Hazard Ratios for Groups who Differ in more than one Predictor with Multiple Cox Regression12мин
The "Linearity" Assumption and Prediction with Multiple Cox Regression21мин
Examples from the Literature25мин
2 материала для самостоятельного изучения
Soluitons To Multiple Cox Regression Practice Quiz10мин
Solutions: Summative Quiz (Multiple Cox Regression)10мин
2 практического упражнения
Practice Quiz: Multiple Cox Regression30мин
Multiple Cox Regression, and Course Concepts30мин
2 ч. на завершение
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 ч. на завершение
1 материал для самостоятельного изучения, 1 тест
1 материал для самостоятельного изучения
Biostatistical Consulting Project10мин
1 практическое упражнение
Project2ч
4.7
Рецензии: 11
Лучшие отзывы о курсе Multiple Regression Analysis in Public Health
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.
The course was five stars, there were some quiz issues and a few numerical issues, but I learned a lot and appreciate the time and effort put into the content. Thank you!
Преподаватели
John McGready, PhD, MS
Associate Scientist, BiostatisticsBloomberg School of Public Health
О Университет Джонса Хопкинса
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.
Специализация Biostatistics in Public Health : общие сведения
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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