courseraЗдоровье

MOST from a Methodological Perspective

Курс от New York University

Средний≈ 17.6 чАнглийский

О курсе

This course is aimed at intervention scientists working in any area--including public health, education, criminal justice, and others—interested in learning about an innovative framework for conducting intervention research. This course will show you how to use the multiphase optimization strategy (MOST) to: streamline interventions by eliminating inactive components; identify the combination of components that offers the greatest effectiveness without exceeding a defined implementation budget; develop interventions for immediate scalability; look inside the “black box” to understand which intervention components work and which do not; and improve interventions programmatically over time. In this course you will relate the MOST framework to your research objectives; learn how MOST differs from the standard approach to intervention development and evaluation; learn how to complete the preparation and optimization phases of MOST; and become familiar with rigorous and highly efficient experimental designs that will enable you to examine the performance of individual intervention components.

Навыки, которые вы освоите

Research Design Research Methodologies Clinical Trials Experimentation Program Evaluation Science and Research Statistical Analysis Statistical Methods Continuous Quality Improvement (CQI)Sample Size Determination Clinical Research Social Impact

Программа курса

7 модулей · 41 учебных материалов

01Module 1: MOST is a Different Way of Thinking9 материалов

Учитесь у экспертов

Linda M Collins

Professor

Kate Guastaferro

Assistant Research Professor

02Module 2: The Factorial Optimization Trial and the Factorial Analysis of Variance (ANOVA)7 материалов

Lesson 1: The Preparation Phase and Specifying the Optimization Objective

Lesson 1 VideoВидео Module 2 ReadingsЧтение

Lesson 2: Conceptual differences between the factorial experiment and the ERCT

Lesson 2 VideoВидео

Lesson 3: Main Effects and Interactions

Lesson 3 VideoВидео

Lesson 4: Fundamental Differences Between the ERCT and the Factorial Experiment

Lesson 4 VideoВидео

Lesson 5: The Factorial ANOVA as a Regression Model

Lesson 5 VideoВидео

Lesson 6: The Balance Property of Factorial Experiments

Lesson 6 VideoВидео

04Module 4: Powering a Factorial Optimization Trial7 материалов

Lesson 1: The Pilot Study

Lesson 1 VideoВидео Module 4 ReadingsЧтение

Lesson 2: Understanding the Basics of Powering a Factorial Experiment

Lesson 2 VideoВидео

Lesson 3: Interpretation of Main Effects and Interaction Effects

Lesson 3 VideoВидео

Lesson 4: Two Different Ways of Defining the Interaction

Lesson 4 VideoВидео

Lesson 5: Two Distinct Perspectives on Research: Conclusion-Priority and Decision-Priority

Lesson 5 VideoВидео

Lesson 6: Putting It All Together to Conduct a Power Analysis

Lesson 6 VideoВидео

MOST from a Methodological Perspective

О курсе

Навыки, которые вы освоите

Программа курса

Lesson 0

Lesson 1: Definitions of Key Concepts, Part 1

Lesson 2: Definitions of Key Concepts, Part 2

Учитесь у экспертов

Linda M Collins

Kate Guastaferro

Lesson 3: What Knowledge Can and Cannot Be Obtained from an ERCT

Lesson 4: Comparison of the Classical Treatment Package and Engineering Approaches

Lesson 5: The Concept of Optimization

Lesson 6: The Three Phases of MOST

Lesson 7: Why MOST is a Different Way of Thinking

Lesson 1: The Preparation Phase and Specifying the Optimization Objective

Lesson 2: Conceptual differences between the factorial experiment and the ERCT

Lesson 3: Main Effects and Interactions

Lesson 4: Fundamental Differences Between the ERCT and the Factorial Experiment

Lesson 5: The Factorial ANOVA as a Regression Model

Lesson 6: The Balance Property of Factorial Experiments

Lesson 1: Comparison of Effect Coding and Dummy Coding, Part 1

Lesson 2: Comparison of Effect Coding and Dummy Coding, Part 2

Lesson 3: More About the Economy of the 2^k Factorial Experiment

Lesson 4: The Resource Demands of Factorial Experiments Involving More Than Two Levels in a Factor

Lesson 5: Experimental Control in a Factorial Design

Lesson 1: The Pilot Study

Lesson 2: Understanding the Basics of Powering a Factorial Experiment

Lesson 3: Interpretation of Main Effects and Interaction Effects

Lesson 4: Two Different Ways of Defining the Interaction

Lesson 5: Two Distinct Perspectives on Research: Conclusion-Priority and Decision-Priority

Lesson 6: Putting It All Together to Conduct a Power Analysis

Lesson 1: Recognizing and Dealing with a Cluster Structure

Lesson 2: Brief Introduction to Adaptive Interventions

Lesson 3: Different Types of Interventions, Different Optimization Trial Designs

Lesson 4: Addressing Dose-Response Questions in an Optimization Trial

Lesson 5: Hybrid Evaluation-Optimization Designs

Lesson 1: Ensuring That All Factors Can Be Manipulated Independently

Lesson 2: Ensuring That All Participants Are Provided with at Least the Standard of Care

Lesson 3: Random Assignment

Lesson 4: Whether or Not to Use a Type I Error Rate Correction

Final Assessment