Registered Dietitian Practice Test 2025 - Free Practice Questions and Study Guide

Attrition is a potential threat to both the internal and external validity of a longitudinal study because it refers to the loss of participants over time. In longitudinal studies, researchers collect data from the same subjects repeatedly across different points in time. When participants drop out, it can lead to a biased sample, as those who remain may not represent the original cohort. This loss can affect the study's findings, reducing the generalizability of the results (external validity) and potentially confounding the relationships being analyzed (internal validity).

Furthermore, if the attrition is related to the outcome being measured (for example, individuals with poor health may be more likely to drop out), this could skew the results and lead to incorrect conclusions. Addressing attrition is crucial for maintaining the integrity and validity of longitudinal research.

The other concepts, such as bootstrapping, cluster sampling, and dispersion, do not directly create the same threats to validity in longitudinal studies. Bootstrapping is a statistical method for estimating the distribution of a sample statistic, cluster sampling is a specific sampling technique, and dispersion pertains to the spread of data, which influences data analysis but does not inherently affect the validity of the study itself.