What Is Selective Attrition?

Selective Attrition
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In psychology experiments, selective attrition describes the tendency of some people to be more likely to drop out of a study than others. This tendency can threaten the validity of a psychological experiment.

When data is collected at two or more points in time during an experiment, there will naturally be people who begin a study but then find that they cannot continue. Dropping out of a study can occur for a wide variety of reasons and can occur in both experimental and longitudinal designs.

It is important to note that selective attrition does not mean that certain people are more likely to quit a study. Instead, it simply implies that there is a tendency for people to quit an experiment for a variety of reasons.

Causes of Selective Attrition

The main reasons why people drop out of research studies are sometimes referred to as the four M's:

  1. Motivation: Sometimes people simply lose the motivation to continue an experiment. They become bored and lose interest or find other things that they prefer.
  2. Mobility: In other cases, people move out of the area and are simply no longer able to continue in the study do to geographic reasons. This is especially true during longitudinal studies. When researchers attempt to locate the original participants, they may find that many have moved and cannot be found.
  3. Morbidity: Illness can also prevent people from participating in research and may lead them to drop out of a study. Participants might experience brief episodes of sickness that prevent them from participating at critical points of the study, while others might develop serious diseases or addiction relapses that prevent any further participation.
  1. Mortality: Finally, participants sometimes pass away before research studies are completed. This is particularly true for longitudinal studies centered on aging adults.

Problems Caused By Attrition Bias

Attrition Bias

While selective attrition doesn’t imply that certain types of participants are more likely to drop out of a study, attrition can result in a research bias when the people who prematurely exit a study are fundamentally different from those who remain in the study.

When this happens, researchers end up with a final study group that is quite different from the original sample. Because of the differences between the original sample and the final group of participants, something known as an attrition bias can affect the results of the study.

It is important to note, however, that if there are no systematic differences between those who complete a study and those who drop out, then the results will not be impacted by the attrition bias.

Threats to Validity

When certain groups of individuals drop out of a study, attrition can also affect the validity of the results. Since the final group of participants no longer accurately reflects the original representative sample, the results cannot be generalized to a larger population.

Imagine that researchers are doing a longitudinal study on how cardio exercise impacts cognitive functioning as people age. The researchers begin their study by collecting data from a representative sample of middle-aged adults between the ages of 40 and 45.

Over the next few decades, the researchers continue to periodically collect data on the aerobic fitness and cognitive functioning of their original sample.

Selective attrition will happen naturally with a study that occurs over such a long period of time. Some participants will move, some will lose interest, some with suffer from illness, and some will even pass away.

But what if certain groups of individuals become more prone to selective attrition? Suppose that widowers tend to drop out of the study more frequently than those who have a surviving spouse. Because the final sample lacks data from this group, it may no longer reflect the tendencies that exist in the overall population at large, threatening the external validity of the study and making it difficult to generalize the results to the entire populace.

Internal validity can also be a problem with there are different attrition rates between the control groups and the experimental groups. If researchers were conducting an experiment on a treatment for anxiety, for example, the results of the study might be biased if people in the experimental group drop out at a higher rate than those in the control group.

Consider, for example, if this attrition rate is due anxiety that prevents participants from completing the study. Since the experimental group includes a higher proportion of individuals who benefited from the treatment, the results will be biased and suggest that the treatment was perhaps more effective than it really was.


Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47, 153–161.

Miller, R.B., & Hollist, C.S. (2007). Attrition Bias. Faculty Publications, Department of Child, Youth, and Family Studies. Paper 45. http://digitalcommons.unl.edu/famconfacpub/45/

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