Design |
Strengths |
Weaknesses |
Pre-Post |
- Is simple and quick to implement
- Can easily be used with surveys
- Can provide a reasonable estimate ofthe post-response change in theproblem
|
- Can show only short-term changes inthe problem
- Cannot account for preexisting trends
- Cannot account for the possibility that some other factor occurred at the same time as the response, and caused the problem to change
- Is very weak at ruling out other alternative explanations
|
Interrupted Time Series |
- Is easy to use with data routinely collected over many time periods
- Can rule out preexisting trends and many other alternative explanations
|
- Is very hard to use if special data collection methods, such as surveys, are used to measure the problem
- Cannot account for the possibility that some other factor occurred at the same time as the response, and caused the problem to change
- Takes a long time to establish results
- Is hard to interpret when there are few problem events per time period before the response
|
Pre-Post With a Control Group |
- Can easily be used with surveys
- Can account for the possibility thatsome other factor occurred at thesame time as the response, and caused the problem to change
|
- Can show only short-term changes in the problem
- Requires a control group that is similar to the response group
|
Multiple Time Series |
- Is easy to use with data routinely collected over many time periods
- Can rule out preexisting trends and many other alternative explanations
- Can account for the possibility that some other factor occurred at the same time as the response, and caused the problem to change
|
- Is very hard to use if special data collection methods, such as surveys, are used to measure the problem
- Requires a control group that is similar to the response group
- Takes a long time to establish results
- Is hard to interpret when there are few problem events per time period before the response
|
