Tag: onyx

Fit indices for missing data (chi^2, RMSEA, CFI)

Great news! It took us long enough but we finally have implemented chi^2 and derived fit statistics for missing data. Ωnyx now separately estimates the log-likehood of the saturated model when data have missing values. So, we finally can offer

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Latent Factor Score Estimation

Today, we are proud to release another update to Ωnyx. The latest version allows you to obtain latent factor scores. You can find this new feature in the model’s context menu Estimation -> Obtain Latent / Missing Scores. Choosing this option

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Mint and Camouflage

We are happy to release another update of Ωnyx with bug fixes and a couple of new features (see section Downloads for the latest version). Primarily, we fixed a couple of GUI-related problems with copy&paste and drag&drop, particularly so with definition

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New Chapter on Ωnyx in “Health Science Statistics using R and R Commander”

We are happy to announce the publication of Robin Beaumont’s book “Health Science Statistics using R and R Commander” (Scion Publishing; ISBN 9781907904318, which has a whole chapter on Ωnyx. We feel honored and are excited about the daily growing Ωnyx community out there.

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Out now: Structural Equation Modeling with Ωnyx

We are happy to announce the online publication of our manuscript soon to be published in Structural Equation Modeling: A Multidisciplinary Journal. We are allowed to share 50 online copies of it for free on a first come first serve

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Ωnyx 1.0

We are happy to announce the release of Ωnyx 1.0. We are grateful for your positive feedback throughout the development process.   Among the new features in this release are: – improved optimization engine – external runners allowing to run

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Version 0.9-700 released

In the mean time, we have given a couple of workshops on Ωnyx and received many helpful comments on how to improve our program. With this release, we have included several bugfixes for problems reported by our great community of fans. Fixed

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