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.
이 강좌는 Biostatistics in Public Health 특화 과정의 일부입니다.
제공자:
이 강좌에 대하여
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
배울 내용
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
귀하가 습득할 기술
- effect modifcation
- Proportional Hazards Model
- Regression Analysis
- Spline approach
The recommended math prerequisite is up through and including basic algebra including logarithms and the equation of a line.
제공자:

존스홉킨스대학교
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.
강의 계획표 - 이 강좌에서 배울 내용
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.
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.
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.
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.
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- 5 stars79.68%
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- 3 stars4.68%
- 1 star0.39%
MULTIPLE REGRESSION ANALYSIS IN PUBLIC HEALTH 의 최상위 리뷰
A wonderful look at multiple regression, including effect modification, interactions, and adjusted slopes.
one of the finest courses on biostatistics, in order to get refreshed with the core concepts and applications!
Would love to learn more from Dr. McGready in statistical courses more advanced than the ones offered in this specialization
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.
Biostatistics in Public Health 특화 과정 정보
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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