sampling error

Related concepts: alpha and beta The number of subjects studied, including those in the intervention group and the control group, where applicable. Note: In general, a large sample size decreases the probability of Type I (α) (false-positive) errors and increases the statistical power of the trial, i.e. decreases the probability of Type II (β) (false-negative) errors. A large sample size decreases the effect of random variation on the estimate of a treatment effect. In designing a study, the desired sample size can be calculated using a statistical formula based on the acceptable levels of α and β errors, the smallest difference between intervention groups considered clinically relevant, and the measurement variance.


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