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Segmented regression analysis of interrupted time series studies in medication use research
Author(s) -
Wagner A. K.,
Soumerai S. B.,
Zhang F.,
RossDegnan D.
Publication year - 2002
Publication title -
journal of clinical pharmacy and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.622
H-Index - 73
eISSN - 1365-2710
pISSN - 0269-4727
DOI - 10.1046/j.1365-2710.2002.00430.x
Subject(s) - interrupted time series analysis , interrupted time series , regression analysis , regression , time series , psychological intervention , statistics , linear regression , econometrics , series (stratigraphy) , computer science , medicine , mathematics , paleontology , biology , psychiatry
Summary Interrupted time series design is the strongest, quasi‐experimental approach for evaluating longitudinal effects of interventions. Segmented regression analysis is a powerful statistical method for estimating intervention effects in interrupted time series studies. In this paper, we show how segmented regression analysis can be used to evaluate policy and educational interventions intended to improve the quality of medication use and/or contain costs.