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Resources by TopicIan Burnette2026-03-12T19:35:29+00:00

Resources by Topic

Resources by Topic

Explore our comprehensive training resources and self-guided online courses designed to help researchers develop adaptive interventions.

Explore our comprehensive training resources and self-guided online courses designed to help researchers develop adaptive interventions.

Home / Resources by Topic

Home / Resources by Topic

Intervention Optimization

Intervention Optimization Fundamentals

ARTICLE Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology – Annual Review of Clinical Psychology

OVERVIEW Intervention Optimization

Evolution of Experimental Designs for Optimizing Adaptive Interventions

SLIDE DECK Slide Deck

VIDEO Recorded Presentation

SMART Designs + Standard Adaptive Interventions

Adaptive Intervention Fundamentals

ONLINE COURSE Module 1: Introduction to Adaptive Interventions

OVERVIEW Advancing the science of adaptive interventions

SLIDE DECK Adaptive Interventions: Introductory Review

VIDEO Adaptive Interventions: Introductory Review

SMART Fundamentals

ONLINE COURSE Module 2: Introduction to Sequential Multiple Assignment Randomized Trials (SMARTs)

ONLINE COURSE Module 3: SMART Design Principles

OVERVIEW Advancing the science of adaptive interventions

SLIDE DECK Sequential Multiple Assignment Randomized Trials: Introductory Review

VIDEO Sequential Multiple Assignment Randomized Trials: Introductory Review

HANDOUT Sample Size Standard Prototypical SMART

SMART Case Studies

SLIDE DECK SMART Case Studies

VIDEO SMART Case Studies

HANDOUT SMART Case Studies

CASE STUDIES Browse all SMART Case Studies

SMART Sample Size Calculation

APP Sample size Calculator for SMART Pilot Studies

APP illustrating tradeoffs between sample size and power for different research questions in a prototypical SMART

APP illustrating tradeoffs between sample size and power for a non-prototypical SMART with possibly unequal allocation

CODE Sample size for a SMART with a binary, longitudinal outcome

CODE Sample size for a SMART with a continuous, longitudinal outcome

CODE Sample size for a SMART with a binary or continuous end-of-study outcome

CODE Sample size for a SMART with a longitudinal count outcome

CODE Sample size for a clustered SMART with a continuous, end-of-study outcome

Analyzing Data from SMART Studies

SLIDE DECK 1 Main Effects

VIDEO 1 Main Effects

SLIDE DECK 2 Comparing Adaptive Interventions

VIDEO 2 Comparing Adaptive Interventions

CODE Compare adaptive interventions in a SMART with a binary, longitudinal outcome [Standard Least Squares Regression]

CODE Compare adaptive interventions in a SMART with a continuous, longitudinal outcome [Standard Least Squares Regression]

CODE Compare adaptive interventions in a SMART with a continuous, longitudinal outcome [Linear Mixed Modeling]

CODE Compare adaptive interventions in a SMART with a continuous end-of-study outcome [Weighted & Replicated Least Squares Regression]

SLIDE DECK 3 Moderators & Tailoring Variables

VIDEO 3 Recorded Presentation

CODE Construct a more deeply-tailored adaptive intervention using data from a SMART [Q-Learning Regression]

Pilot Studies

SLIDE DECK Pilot Studies in Adaptive Intervention Research

VIDEO Pilot Studies in Adaptive Intervention Research

APP Sample size Calculator for SMART Pilot Studies

Repeated Outcome Measures in SMARTs

SLIDE DECK Repeated Outcome Measures in SMARTs

VIDEO Repeated Outcome Measures in SMARTs

HANDOUT Sample Size – SMART w/Repeated Outcome Measures

Clustered SMARTs

SLIDE DECK Clustered SMARTs

VIDEO Clustered SMARTs

HANDOUT Sample Size – Clustered SMART

CODE Multilevel Primary Aim Analyses of Clustered SMARTs

CODE Clustered SMART Data Generation and Analysis

CODE Compare adaptive interventions within a clustered SMART with a continuous, end-of-study outcome [Weighted & Replicated Least Squares Regression]

Micro-Randomized Trial Designs [MRTs] + Just-in-Time Adaptive Interventions [JITAIs]

JITAI Fundamentals

ONLINE COURSE Module 1: Introduction to Just-in-Time Adaptive Interventions

OVERVIEW Advancing Mobile Health Interventions

MRT Fundamentals

COURSE MODULE Module 2: Introduction to Micro-Randomized Trials

OVERVIEW Advancing Mobile Health Interventions

MRT Case Studies

CODE Power calculation for the Mobile Assistance for Regulating Smoking (MARS) MRT

CODE Sample size calculations for the Sense2Stop stratified MRT

CODE The Self-Relevant Appeals to Engage in Self-Monitoring of Alcohol Use MRT

CODE The Substance Abuse Research Assistant (SARA) MRT

CODE Text-Based Support for Parents of Suicidal Adolescents (TESP) MRT

VISUAL AID Schematics of Micro-randomized Trials

CASE STUDIES Browse all MRT Case Studies

Analyzing Data from MRTs

SLIDE DECK 1 Analysis for MRTs with Continuous Outcomes

CODE Estimate the proximal and distal causal effects of a JITAI on a continuous outcome

SLIDE DECK 2 Analysis for MRTs with Binary Outcomes

CODE Primary and secondary analyses for MRT w/continuous or binary proximal outcome

MRT Sample Size & Power Calculation

CODE Sample size & power for an MRT with a continuous proximal outcome

CODE Sample size & power for an MRT with a binary proximal outcome

CODE Causal excursion effect for multi-treatment data with a continuous outcome

Additional Resources

Frequently Asked Questions about MRTs

Hybrid Experimental Designs [HEDs]

HED Fundamentals

OVERVIEW Integrating human-delivered and digital interventions

ARTICLE Hybrid Experimental Designs for Intervention Development: What, Why, and How

HED Data Analysis

CODE Data Analysis for Three Kinds of Hybrid Experimental Designs

CODE Analysis of proximal and distal effects using data from a hybrid SMART-MRT in which only non-responders are micro-randomized

CODE Simulating and analyzing data from a Hybrid Experimental Design (HED)

Personalizing JITAIs [pJITAI]

Reinforcement Learning Algorithms

JustIn Reinforcement Learning API

CODE Backend Service for the Oralytics RL Algorithm

CODE Backend Service for the MiWaves RL Algorithm

CODE RL for AYA Dyads to Enhance Medication Adherence (ADAPTS HCT)

CODE Online Learning in Bandits with Predicted Context

CODE Oralytics Post Deployment Analysis

CODE Bagged Decision Times

pJITAI Toolbox

APP pJITAI Toolbox

Factorial Experiments

Designing a Factorial Experiment

CODE Code to design a factorial experiment

NEW APP Sample Size Calculations for Factorials with Experiment-Induced Clustering

Factorial Experiment Sample Size Calculation

NEW APP Sample Size Calculations for Factorials with Experiment-Induced Clustering – This app implements formulas from “Multilevel factorial designs with experiment-induced clustering” (Nahum-Shani, Dziak & Collins, 2018).

Other

Cannabis Use Motives

CODE Latent Transition Analysis of Time-Varying Cannabis Use Motives to Inform Adaptive Interventions

Events

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