monkeysnanax.blogg.se - Excel linear regression force intercept

Multiple prior probabilities for computation of predictive values.ĭistribution / Compare groups / Compare pairs.

Hide excluded outliers in Variability plot.

Improved handling of small negative numbers in fitting a precision profile variance function (thanks to Bill Sadler for his suggestions).

Predict variance at a given U for precision profile variance function.

Transform X and Y variable in simple regression.

Probit regression (including features to perform CLSI EP17-A2 using Probit regression) (Fitting a simple probit regression, Estimating the detection limit using a probit fit).

New help topics on binary/semi-quantitative agreement measures.

Dice-Sørensen average agreement measure.

Bangdiwala's agreement plot for visualizing agreement (Agreement plot).

Probit regression multiple inverse predictions.Updated help topics for comparing sensitivity/specificity.Noninferiority/Equivalence tests for comparing sensitivity/specificity.Probit/Logit regression inverse prediction confidence intervals.

(Estimating the linearity of a measurement procedure (EP06-Ed2)) CLSI now defines the deviation from linearity as the difference between the mean of replicates and the linear fit, and therefore no longer requires fitting polynomial models. Added support for the new CLSI EP6-Ed2 linearity procedure.Added ability to plot predictions or inverse predictions on scatter plotĪdded Recalculate All command to recalculate all analyses in the workbook.Added support for inverse prediction of X given Y in simple regression models.