Worked example

Definition

$NPV\; =\; frac\{rm\; number\; of\; True\; Negatives\}\{\{rm\; number\; of\; True\; Negatives\}+\{rm\; number\; of\; False\; Negatives\}\}$

or, alternatively,

$NPV\; =\; frac\{(\{rm\; specificity\})\; (\{rm\; 1\; -\; prevalence\})\}\{(\{rm\; specificity\})\; (\{rm\; 1\; -\; prevalence\})\; +\; (1\; -\; \{rm\; sensitivity\})\; (\{rm\; prevalence\})\}$

See also

• Positive predictive value
• Sensitivity and specificity
• Binary classification

References

• Altman DG, Bland JM (1994). "Diagnostic tests 2: Predictive values". BMJ 309 (6947): 102.