Karimollah Hajian-Tilaki1. 1. Dept of Social Sciences and Health, Babol University of Medical Sciences, Babol, Iran. Electronic address: drhajian@yahoo.com.
Abstract
OBJECTIVES: This review provided a conceptual framework of sample size calculations in the studies of diagnostic test accuracy in various conditions and test outcomes. METHODS: The formulae of sample size calculations for estimation of adequate sensitivity/specificity, likelihood ratio and AUC as an overall index of accuracy and also for testing in single modality and comparing two diagnostic tasks have been presented for desired confidence interval. RESULTS: The required sample sizes were calculated and tabulated with different levels of accuracies and marginal errors with 95% confidence level for estimating and for various effect sizes with 80% power for purpose of testing as well. The results show how sample size is varied with accuracy index and effect size of interest. CONCLUSION: This would help the clinicians when designing diagnostic test studies that an adequate sample size is chosen based on statistical principles in order to guarantee the reliability of study.
OBJECTIVES: This review provided a conceptual framework of sample size calculations in the studies of diagnostic test accuracy in various conditions and test outcomes. METHODS: The formulae of sample size calculations for estimation of adequate sensitivity/specificity, likelihood ratio and AUC as an overall index of accuracy and also for testing in single modality and comparing two diagnostic tasks have been presented for desired confidence interval. RESULTS: The required sample sizes were calculated and tabulated with different levels of accuracies and marginal errors with 95% confidence level for estimating and for various effect sizes with 80% power for purpose of testing as well. The results show how sample size is varied with accuracy index and effect size of interest. CONCLUSION: This would help the clinicians when designing diagnostic test studies that an adequate sample size is chosen based on statistical principles in order to guarantee the reliability of study.
Authors: Michael Darmon; Aurelie Bourmaud; Marie Reynaud; Stéphane Rouleau; Ferhat Meziani; Alexandra Boivin; Mourad Benyamina; François Vincent; Alexandre Lautrette; Christophe Leroy; Yves Cohen; Matthieu Legrand; Jérôme Morel; Jeremy Terreaux; David Schnell Journal: Intensive Care Med Date: 2018-10-05 Impact factor: 17.440
Authors: Andrea K Graham; Alexa Minc; Erin Staab; David G Beiser; Robert D Gibbons; Neda Laiteerapong Journal: Ann Fam Med Date: 2019-01 Impact factor: 5.166
Authors: S T Williams; P T Lawrence; K L Miller; J L Crook; J LaFleur; G W Cannon; R E Nelson Journal: Osteoporos Int Date: 2017-07-30 Impact factor: 4.507
Authors: Gary E Weissman; Lyle H Ungar; Michael O Harhay; Katherine R Courtright; Scott D Halpern Journal: J Biomed Inform Date: 2018-12-14 Impact factor: 6.317
Authors: Manus Schmedding; Bayode R Adegbite; Susan Gould; Justin O Beyeme; Akim A Adegnika; Martin P Grobusch; Michaëla A M Huson Journal: Am J Trop Med Hyg Date: 2019-01 Impact factor: 2.345
Authors: Sarmed S Sami; Prasad G Iyer; Prachi Pophali; Magnus Halland; Massimiliano di Pietro; Jacobo Ortiz-Fernandez-Sordo; Jonathan R White; Michele Johnson; Indra Neil Guha; Rebecca C Fitzgerald; Krish Ragunath Journal: Clin Gastroenterol Hepatol Date: 2018-08-03 Impact factor: 11.382