The Validity and Precision of the Comparative Interrupted Time-Series Design: Three Within-Study Comparisons

Travis St.Clair, Kelly Hallberg, Thomas D. Cook

Research output: Contribution to journalArticlepeer-review

Abstract

We explore the conditions under which short, comparative interrupted time-series (CITS) designs represent valid alternatives to randomized experiments in educational evaluations. To do so, we conduct three within-study comparisons, each of which uses a unique data set to test the validity of the CITS design by comparing its causal estimates to those from a randomized controlled trial (RCT) that shares the same treatment group. The degree of correspondence between RCT and CITS estimates depends on the observed pretest time trend differences and how they are modeled. Where the trend differences are clear and can be easily modeled, no bias results; where the trend differences are more volatile and cannot be easily modeled, the degree of correspondence is more mixed, and the best results come from matching comparison units on both pretest and demographic covariates.

Original languageEnglish (US)
Pages (from-to)269-299
Number of pages31
JournalJournal of Educational and Behavioral Statistics
Volume41
Issue number3
DOIs
StatePublished - 2016

Keywords

  • causal inference
  • comparative interrupted time series
  • interrupted time series
  • randomized experiment
  • within-study comparison

ASJC Scopus subject areas

  • Education
  • Social Sciences (miscellaneous)

Fingerprint

Dive into the research topics of 'The Validity and Precision of the Comparative Interrupted Time-Series Design: Three Within-Study Comparisons'. Together they form a unique fingerprint.

Cite this