10-May-2013 Analyse-it Method Evaluation Edition 3.5 alpha 2 now available

Update 14th October 2013

The Analyse-it Method Validation Edition version 3.50 has now been released, see Analyse-it Method Validation edition version 3.5 is now available.

Original article

Today we released the 2^nd alpha of the Analyse-it Method Evaluation Edition 3.5.

Alpha releases are pre-release versions of the software that are still in active development. We release them to a small group of customers so we can get feedback and quickly identify and fix any problems before the public beta release. If you want to take part in the test phase reply or comment on to this post or contact us. You can use pre-release versions of Analyse-it alongside your existing version of Analyse-it, so it won't disrupt your work. And, if you help during in the test phases you will get a discount on the upgrade (a free upgrade for those who contribute the most) when the product is released later this year.

This latest alpha release includes linearity and precision analysis, plus diagnostic test performance (ROC analysis and binary test performance) and reference intervals from the 1^st alpha.

Some of the new features included so far are:

Precision

• Graybill-Wang / Ting-Burdick-Graybill-Jeyaratnam-Lu modified large sample confidence interval estimators for variance components – produces confidence closer to the stated level than Satterthwaire confidence intervals, which can be too liberal.
• Support for unbalanced 1-way and 2-way nested random ANOVA models.

Linearity

• Hsieh-Liu confidence interval estimator for degree of nonlinearity.
• Equality and equivalence hypothesis tests for nonlinearity.

Reference interval

• Harrel-Davis, Bootstrap, and Robust Biweight quantiles.
• Box-Cox and other transformations.

ROC

• Compare up to 10 independent or correlated ROC curves.
• Equality, equivalence and non-inferiority hypothesis tests.
• Estimate false positive fraction (FPF) at fixed sensitivity, sensitivity at fixed FPF, and sensitivity/FPF at fixed cut-off.
• Find optimal decision threshold based on costs.

Binary diagnostic tests

• Compare sensitivity and specificity of 2 independent or correlated tests.
• Diagnostic odds-ratio and Youden’s index.
• Improved confidence interval estimators for likelihood ratio and predictive values.