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JMP Wish List

We want to hear your ideas for improving JMP software.

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We consider several factors when looking for what ideas to add to JMP. This includes what will have the greatest benefit to our customers based on scope, needs and current resources. Product ideas help us decide what features to work on next. Additionally, we often look to ideas for inspiration on how to add value to developments already in our pipeline or enhancements to new or existing features.

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Fit curve - quantal data

The "Fit Curve" platform in JMP does not support quantal (e.g. dead/alive) dose-response analysis, which is essential for bioassays with arthropods for example. Instead, users must resort to the "Fit Model" platform. While "Fit Model" can conduct the analysis using a Generalized Linear Model with binomial distribution and Logit or Probit link functions, it requires a cumbersome, manual multi-step process for essential tasks such as testing for parallelism, fitting parallel lines, and estimating potencies and relative potencies. This manual process is not only time-consuming but also susceptible to errors. In contrast, the "Fit Curve" platform offers automated procedures for similar analyses with continuous data, highlighting a gap in JMP's capabilities for quantal data. Enhancing the "Fit Curve" platform to handle quantal data would significantly improve efficiency, accuracy, and overall user experience. 

Below, you will find the detailed manual steps required in Fit Model platform to analyse the results of an experiment involving three strains of insects (i.e., lab, field 1, and field 2), each subjected to five doses of an insecticide across three replicates with 20 insects per replicate.

 

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