A selection bias is a statistical error that causes a bias in the sampling portion of an experiment. The error causes one sampling group to be selected more often than other groups included in the experiment. This may produce an inaccurate conclusion if the selection bias is not identified.
Randomized experiments solve the problem of selection bias by generating an experimental control group of people who would have participated in a program but who were randomly denied access to the program or treatment. The random assignment does not remove selection bias but instead balances the bias between the participant and nonparticipant samples. In quasi-experimental designs, statistical models (for example, matching, double differences, instrumental variables) approach this by modeling the selection processes to arrive at an unbiased estimate using nonexperimental data. The general idea is to compare program participants and nonparticipants holding selection processes constant. The validity of this model depends on how well the model is specified.
- Baker, J. L. (2000): Evaluating the Impact of Development Projects on Poverty. A Handbook for Practioners. The World Bank, Washington, D.C.
- Impact Portal on energypedia
- Impact Evaluation - Mixed Methods
- ↑ Businessn Dictionary: http://www.businessdictionary.com/definition/selection-bias.htmlfckLR
- ↑ Baker, J. L. (2000): Evaluating the Impact of Development Projects on Poverty. A Handbook for Practioners. The World Bank, Washington, D.C.: http://siteresources.worldbank.org/INTISPMA/Resources/handbook.pdf (p.5)fckLR