Sentence examples for accuracy was analyzed using from inspiring English sources

Marker accuracy was analyzed using linear mixed effects models as implemented in the lmer-function of the lme4 package (Bates, Maechler, Bolker, & Walker, 2015) for R (R Development Core Team, 2012), using a binomial link function and the Bobyqa optimizer.

Diagnostic accuracy was analyzed using sensitivity and specificity.

Recognition accuracy was analyzed using the R Statistical Package v2.8 (R Development Core Team, 2008).

Accuracy was analyzed using a two-way repeated measures ANOVA, with factors Speller and Attention.

Group differences in semantic priming effects (for RT and accuracy) were analyzed using Linear Mixed Model (LMM) analysis, with group (LHD, Control) as a between-subjects factor, and target visual field (LVF, RVF), stimuli condition (CA, CO, AO, UNR) and memory load (0-, 2-, 6-word) as fixed factors.

The accuracy of predicted results was analyzed using the analysis of variance (ANOVA) method.

The well-behavedness of the parameters and the accuracy of the method was analyzed using the Mori–Tanaka model for aligned ellipsoidal inclusions and using Buckminster Fuller's octet-truss lattice.

Accuracy in the recognition memory task was analyzed using one-sample t tests with participant performance compared against 50%% accuracy, which constituted chance accuracy.

Accuracy of outcome prediction via BT was analyzed using the receiver operating characteristic (ROC) defined by the area under the curve (AUC) (Figure 1C).

ΔΨm was analyzed using JC-1.

Data was analyzed using FlowJo software (TreeStar).