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. Control series offer a potential solution to this problem, but there is little guidance on how to use them to produce trend-adjusted estimates. To address this lack of guidance, we show how interrupted time series can be analysed when the control and intervention series share confounders, i. e. when they share a common trend. We show that the intervention effect can be estimated by subtracting the control series from the intervention series and anal...
Robust evaluation of public health interventions is required to ensure that interventions that lead ...
Interrupted time series design has been widely applied to assess the causal effectiveness of an inte...
In this article, I introduce the itsa command, which performs interrupted time-series analysis for s...
Interrupted time series are increasingly being used to evaluate the population-wide implementation o...
Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness o...
Interrupted time series analysis differs from most other intervention study designs in that it invol...
Interrupted time series designs are a valuable quasi-experimental approach for evaluating public hea...
An interrupted time series with a parallel control group (ITS-CG) design is a powerful quasi-experim...
Current health policy calls for greater use of evidence-based care delivery services to improve pati...
Interrupted time series (ITS) is a powerful and increasingly popular design for evaluating public he...
Assessing the impact of complex interventions on measurable health outcomes is a growing concern in ...
Abstract Background The Interrupted Time Series (ITS) is a quasi-experimental design commonly used i...
Background: Various interacting and interdependent components comprise complex interventions. These ...
BACKGROUND: The Interrupted Time Series (ITS) is a quasi-experimental design commonly used in public...
Abstract Background An interrupted time series design...
Robust evaluation of public health interventions is required to ensure that interventions that lead ...
Interrupted time series design has been widely applied to assess the causal effectiveness of an inte...
In this article, I introduce the itsa command, which performs interrupted time-series analysis for s...
Interrupted time series are increasingly being used to evaluate the population-wide implementation o...
Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness o...
Interrupted time series analysis differs from most other intervention study designs in that it invol...
Interrupted time series designs are a valuable quasi-experimental approach for evaluating public hea...
An interrupted time series with a parallel control group (ITS-CG) design is a powerful quasi-experim...
Current health policy calls for greater use of evidence-based care delivery services to improve pati...
Interrupted time series (ITS) is a powerful and increasingly popular design for evaluating public he...
Assessing the impact of complex interventions on measurable health outcomes is a growing concern in ...
Abstract Background The Interrupted Time Series (ITS) is a quasi-experimental design commonly used i...
Background: Various interacting and interdependent components comprise complex interventions. These ...
BACKGROUND: The Interrupted Time Series (ITS) is a quasi-experimental design commonly used in public...
Abstract Background An interrupted time series design...
Robust evaluation of public health interventions is required to ensure that interventions that lead ...
Interrupted time series design has been widely applied to assess the causal effectiveness of an inte...
In this article, I introduce the itsa command, which performs interrupted time-series analysis for s...