TY - JOUR
T1 - Precision verification
T2 - Effect of experiment design on false acceptance and false rejection rates
AU - Lim, Chun Yee
AU - Markus, Corey
AU - Loh, Tze Ping
PY - 2021/12
Y1 - 2021/12
N2 - Objectives: We examined the false acceptance rate (FAR) and false rejection rate (FRR) of varying precision verification experimental designs. Methods: Analysis of variance was applied to derive the subcomponents of imprecision (ie, repeatability, between-run, between-day imprecision) for complex matrix experimental designs (day × run × replicate; day × run). For simple nonmatrix designs (1 day × multiple replicates or multiday ×1 replicate), ordinary standard deviations were calculated. The FAR and FRR in these different scenarios were estimated. Results: The FRR increased as more samples were included in the precision experiment. The application of an upper verification limit, which seeks to cap FRR at 5% for multiple experiments, significantly increased the FAR. The FRR decreases as the observed imprecision increases relative to the claimed imprecision and when a greater number of days, runs, or replicates are included in the verification design. Increasing the number or days, runs, or replicates also reduces the FAR for between-day imprecision and repeatability. Conclusions: Design of verification experiments should incorporate the local availability of resources and analytical expertise. The largest imprecision component should be targeted with a greater number of measurements. Consideration of both FAR and FRR should be given when committing a platform into service.
AB - Objectives: We examined the false acceptance rate (FAR) and false rejection rate (FRR) of varying precision verification experimental designs. Methods: Analysis of variance was applied to derive the subcomponents of imprecision (ie, repeatability, between-run, between-day imprecision) for complex matrix experimental designs (day × run × replicate; day × run). For simple nonmatrix designs (1 day × multiple replicates or multiday ×1 replicate), ordinary standard deviations were calculated. The FAR and FRR in these different scenarios were estimated. Results: The FRR increased as more samples were included in the precision experiment. The application of an upper verification limit, which seeks to cap FRR at 5% for multiple experiments, significantly increased the FAR. The FRR decreases as the observed imprecision increases relative to the claimed imprecision and when a greater number of days, runs, or replicates are included in the verification design. Increasing the number or days, runs, or replicates also reduces the FAR for between-day imprecision and repeatability. Conclusions: Design of verification experiments should incorporate the local availability of resources and analytical expertise. The largest imprecision component should be targeted with a greater number of measurements. Consideration of both FAR and FRR should be given when committing a platform into service.
KW - Accreditation
KW - Laboratory management
KW - Precision
KW - Validation
KW - Verification
UR - http://www.scopus.com/inward/record.url?scp=85120435428&partnerID=8YFLogxK
U2 - 10.1093/ajcp/aqab049
DO - 10.1093/ajcp/aqab049
M3 - Article
C2 - 34111241
AN - SCOPUS:85120435428
SN - 0002-9173
VL - 156
SP - 1058
EP - 1067
JO - American Journal of Clinical Pathology
JF - American Journal of Clinical Pathology
IS - 6
ER -