Google

An interrupted time-series design with nonequivalent groups is a quasi-experimental approach that enhances the basic interrupted time-series design by incorporating a control group. This methodology involves taking multiple measurements of a dependent variable at regular intervals over an extended period both before and after an intervention is implemented across two or more groups that were not randomly assigned. By comparing the baseline and post-intervention trends of the treatment group to those of the nonequivalent control group, researchers can obtain stronger evidence regarding the effectiveness of the intervention.

Interrupted Time-Series Design with Nonequivalent Groups

An example of an interrupted time-series design with nonequivalent groups involves evaluating the impact of reducing a factory's work shifts from $$10$$ to $$8$$ hours. Researchers might track the weekly productivity of the factory making the change (the treatment group) for a year before and after the reduction. To improve the study's validity, they could also track the productivity of a similar factory that maintains its original schedule (the nonequivalent control group). If the treatment factory shows a rapid and sustained increase in productivity following the shift change while the control factory's productivity remains stable, it provides compelling evidence that the shortened shifts caused the improvement.

Example of an Interrupted Time-Series Design with Nonequivalent Groups: Factory Shift Reduction

Another practical example of an interrupted time-series design with nonequivalent groups involves assessing whether taking daily attendance reduces student absences. A researcher could track absences over the semester in one course section where the intervention is introduced (the treatment group), and simultaneously track absences in another section where attendance is not taken (the nonequivalent control group). Superior evidence for the intervention's effectiveness is established if the treatment group shows a consistently high number of absences before the policy change followed by a sustained decrease afterward, while the control group's absences remain consistently high throughout the entire term.

Learn Before

Related