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Analysing Interrupted Time Series with a Control [PDF]
Epidemiologic Methods, 2019 Abstract Interrupted time series are increasingly being used to evaluate the population-wide implementation of public health interventions. However, the resulting estimates of intervention impact can be severely biased if underlying disease trends are not adequately accounted for.
Bottomley, C, Scott, JAG, Isham, V
exaly +7 more sources
Clinical and epidemiological round: Interrupted time series [PDF]
Iatreia, 2017 In quasi-experimental research, it is commonly used the interrupted time series analysis, which measures the effect of an intervention from a specific time point.
León-Álvarez, Alba Luz +3 more
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Causal learning with interrupted time series data
Judgment and Decision Making, 2023 People often test changes to see if the change is producing the desired result (e.g., does taking an antidepressant improve my mood, or does keeping to a consistent schedule reduce a child’s tantrums?).
Yiwen Zhang, Benjamin M. Rottman
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Impact of two-dose varicella vaccination in Guangzhou: An interrupted time-series study [PDF]
Human Vaccines & ImmunotherapeuticsIn November 2017, Guangzhou implemented a self-paid two-dose varicella vaccination program. This study evaluated the program’s impact on varicella incidence trends across the general population and specific age groups. An interrupted time-series analysis
Huan Zhang +4 more
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Causal Learning With Interrupted Time Series. [PDF]
, 2021 Interrupted time series analysis (ITSA) is a statistical procedure that evaluates whether an intervention causes a change in the intercept and/or slope of the time series. However, very little research has accessed causal learning in interrupted time series situations.
Zhang, Yiwen, Rottman, Benjamin
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INTERRUPTED TIME‐SERIES ANALYSIS AND ITS APPLICATION TO BEHAVIORAL DATA [PDF]
Journal of Applied Behavior Analysis, 1980 This paper uses a question‐and‐answer format to present the technical aspects of interrupted time‐series analysis (ITSA). Topics include the potential relevance of ITSA to behavioral researchers, serial dependency, time‐series models, tests of significance, and sources of ITSA information.
D P, Hartmann +5 more
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Forecasting interrupted time series [PDF]
Journal of the Operational Research SocietyForecasting interrupted time series data is a major challenge for forecasting teams, especially in light of events such as the COVID-19 pandemic. This paper investigates several strategies for dealing with interruptions in time series forecasting ...
Rob J. Hyndman, Bahman Rostami Tabar
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Interpretation of coefficients in segmented regression for interrupted time series analyses
BMC Medical Research MethodologyBackground Segmented regression, a common model for interrupted time series (ITS) analysis, primarily utilizes two equation parametrizations. Interpretations of coefficients vary between the two segmented regression parametrizations, leading to ...
Yongzhe Wang +5 more
doaj +4 more sources
Changing Patterns of Domestic Homicide During Lockdown: Interrupted Time-Series Analysis in England and Wales [PDF]
, 2023 This study aimed to examine the effect of lockdown restrictions on domestic homicide incidents in England and Wales. We analyzed data on 1,104 domestic homicides recorded by the Home Office Homicide Index between January 2014 and March 2021 using ...
Abreu, V. +2 more
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‐19 in Australia: An interrupted time series analysis [PDF]
, 2023 Introduction In Australia, the available published literature demonstrated a spike in dispensed prescription medicines after the onset of the COVID-19 pandemic that subsequently returned to expected levels. Smoking cessation medicines may not follow this
Clair Sullivan +11 more
core +1 more source