Sentence examples for bias difference from inspiring English sources

We used different accuracy indices: the relative bias (difference between expected and estimated values expressed as a percent of the known value), the relative standard error (the standard error expressed as a percent of the known value), and the relative root mean square error (RMSE) (the mean square error expressed as a percent of the known value).

When tested against hourly measurements, the model exhibits a coefficient of variance (R2) equal to or better than 0.96, and root mean square difference (RMSD) in the range of 7.3 7.9% and mean bias difference (MBD) of −4.5% to 3.5%.

The comparison between simulated and experimentally measured outlet air temperatures showed a good agreement: a root mean square error on the outlet air temperature of about 0.50 K and a mean bias difference of 0.15 K were observed for experiments conducted on a bright sunny day.

When tested with an independent data set, the multiple regression model performed best with a higher coefficient of variance R2 (0.78 vs. 0.70), lower root mean square difference (RMSD) (12.92% vs. 13.05%) and the same mean bias difference (MBD) of −2.20%.

The bias (difference mean) 1.16 m provided limits of agreement (±2SD) [−0.2919902, 0.291990) which included all except 3 patients.

The agreement between methods was assessed by calculating the paired difference between them for each measurement and by estimating the bias (difference) and 95%% limits of agreements (LoA) relative to the mean measurement of both methods [8].

Topics include generalized method of moments, empirical likelihood, instrumental variables, bootstrapping, clustering, treatment effects, selection bias, difference-in-differences, qualitative choice, quantile regression, nonparametric methods, and semiparametric methods.

Characterizing spatial bias differences among species and across time clarifies underlying causes of spatial bias, information that can be leveraged to improve spatial bias correction.

Given that sequential lineups result in lower AUCs (e.g., Mickes et al., 2012), this effect is most likely due to the well-documented response bias differences that these two procedures induce (e.g., Clark, 2012).

No main effect of ITI bin on response bias differences RI (F 4,20) = 1.2, NS) was observed.

See supporting information File S1 for a more complete discussion on the affects of DIC bias, differences in fibril density between strained and unstrained RIOs, and diffusion delays.