Transcription of Introduction to Interrupted Time Series Analysis
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Introduction to Interrupted Time Series Analysis
Interrupted Time Series Analysis for Single Series and Comparative Designs:Using Administrative Data for Healthcare Impact AssessmentJoseph M. Caswell, AnalystInstitute for Clinical Evaluative Sciences (ICES) North and Epidemiology, Outcomes & Evaluation ResearchHealth Sciences North Research Institute (HSNRI)Northeast Cancer CentrePresentation Overview Quasi-experimental research Interrupted time Series (ITS) ITS single Series with example ITS comparative with example Autocorrelation Adjusting standard errors (SE) in SAS Guide and macroQuasi-Experimental Research Experimental research: Gold-standard is randomized controlled trial (RCT) , drug trials (random assignment to treatment and placebo groups) Treatment and control groups balanced on baseline measures Can be time-consuming, expensive, and even unethical ( , withholding care) Quasi-experimental research.
-0.6875 0.3125 0.0386 Post-Intervention Level difference 2.88% Δslopedifference 0.69%. ut Remember…Autocorrelation! •What is it? •An outcome measured at some point in time is correlated with past values of itself •The lag order is how far back in time the correlation extends
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