The primary consequence of a reduced sample size is decreased statistical power, which can lead to:
Type II Errors: Failing to detect a true effect or association. Biased Results: Smaller sample sizes are more susceptible to biases. Limited Generalizability: Findings may not be applicable to a broader population.
