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Final Output:In the event of participants dropping out of an experiment at different rates, researchers should be concerned about a threat to internal validity known as selection bias. This arises when the characteristics of participants who withdraw from the study differ significantly from those who complete it, thereby potentially affecting the results of the experiment.Steps:1. Identify the problem: When different groups of participants in a study drop out at varied rates, it invariably threatens the internal validity of the research.2. Define the threat to validity: In this case, the threat to internal validity is selection bias. This constitutes a situation wherein those leaving the study are significantly different from those following through with it.3. Understand its impact: Selection bias can jeopardize the reliability of the experiment's findings. Suppose, for instance, the majority of participants who dropped out have a shared characteristic or are more likely to experience a specific condition. In that case, their absence in the experiment could lead to biased results.4. Implement solutions: Researchers can reduce selection bias by employing stratagems such as random assignment and matching to ensure comparability between participants who remain and those who drop out. Also, analyzing the data from dropouts to spot trends or specific factors prompting their exit from the study can be helpful.5. Maintain participant involvement: High levels of participation are key to preserve the validity of the study's outcomes. Therefore, researchers need to minimize dropout rates and react swiftly if such issues manifest themselves. In conclusion, to ensure that the results are as accurate and reliable as possible, researchers must be aware of and mitigate this selection bias quickly. The answer is, therefore, selection bias.

Explanation