Sentence examples for standardised fit from inspiring English sources

A perfect fit is indicated by a standardised fit residual value of ±2.5 and a non-significant χ.

Item fit was assessed with the information-weighted (infit) mean-square (MnSq) statistics and standardised fit residuals (Zstd), both of which measure the discrepancy between the observed responses and responses predicted from the Rasch model.

Five year age-standardised fitted and projected rates were estimated from samples of 15 000 drawn from the posterior distribution, taking the median as an overall summary rate.

Standardised residuals and fitted EQ-5D index values from fitting the final model in both the estimation and validation datasets were plotted against one another.

The performance of the orthogonal design, with respect to standardised AIC model-fit, is better when longer recall periods of 30-days, 6-months and 12-months are used.

Figure 1 shows plots of standardised residuals versus fitted EQ-5D index values in both the estimation and validation datasets, showing evidence of the partly discrete nature of the EQ-5D index at its upper end.

Open image in new window Fig. 9 Measured run time, standardised run time, and linear fit of the standardised run time of GIMME, applied to 1,000 line locations with various numbers of segments.

The next version of the luxury Phaeton saloon car will be electric and VW will develop a standardised electric toolkit to fit all passenger cars and light commercial vehicles.

Observed patient event times and patient factor values are used to fit models; standardised residuals are the differences between the log of observed and log of expected patient event times, divided by estimated error.

The Final Detailed Budget for Phase I, included in the grant agreement, provided to the Global Fund by the Principal Recipient, was reorganized to fit a standardised template in Microsoft Excel to remove any inconsistencies in formatting and, therefore, facilitate comparison.

This is done by means of least squares regression as implemented in the lm-function in R. Model control is performed by plotting the standardised residuals vs. the fitted values and normal probability plots of the standardised residuals.