JMP Wish List

I realize that there is a workaround for doing a Friedman's test, but it is certainly not a big ask to have it in the program.   This is especially true if using it for teaching . ... View more

Now, Expanded Estimates are available only for basic regression models. It would be great to have them for models that are less standard, like logistic regression, ordinal regression, ... ... View more

I have one request/recommendation for a future release of JMP.  In the one-sample equivalence test platform in JMP 16.0.0, I noticed that there is no correction for the non-parametric test case.  Yes I can, in essence conduct the test using the one-sample T-test platform: and by running the Test mean option 2X and picking off the appropriate tests as shown in the graphic below:   But I can’t get the Equivalence region nor can I get the TOST framework formalized in this same way which is what I like about the Test Equivalence Platform for the normality assumed case. So formally the request is for a non-parametric version of the TOST for the one-sample test.    Note that for the 2-sample case I can compute a non-parametric confidence interval on the median difference and compare that to the practical difference region and effectively run the TOST in this way (e.g. Hodges-Lehmann confidence interval on median difference using Wilcoxon all-pairs NP test). This is just the “confidence interval version” of the TOST.  So this actually works quite well for the 2-sample case without any need for an additional feature in the Equivalence Test platform in Fit Y by X.   But in the 1-sample case, in the Distribution platform, I cannot do the same, why? The only way I know of doing something similar to this would be using Custom Quantiles in  JMP's Distribution platform, and that does provide a non-parametric estimate (albeit not the Hodges-Lehmann one, and I have trouble specifying the exact desired coverage for Confidence level of the TOST which is a standard 90% for a 5% significance level).   So (lower-priority) an additional feature altogether could be, the calculation of a non-parametric confidence interval estimate using Hodges-Lehmann on the median in the Distribution Platform. Or perhaps a boot-strapped confidence interval (which you can do for almost every table already in JMP Pro with Right Click > Bootstrap on data table output).   ... View more

JMP should support an improvement to the box-cox λ parameter when transforming the response in the least squares fit model, so that the reverse transformation is automatically applied to graphs. This would save messing around for hours withg the graph builder. ... View more

I think it should be possible to add custom axis breaks to the Graph Builder, in the same way it is often possible in other graphing software like Origin Lab.   At the moment, producing a good display for continuous X-axis data with X-axis grouping is quite involved. For example: if we have continuous timestamps over multiple days, but the data goes only for one hour during each day, but you still want the graph to show the course during a single day.   Previous post explaining the problem: https://community.jmp.com/t5/Discussions/How-to-insert-X-axis-break-in-graph-builder/m-p/525673 ... View more

The  number of decimals shown in the UCL/LCL varies from chart to chart randomly.  I cannot find a way to set the number decimals manually.  @PatrickGiuliano suggested I submit this issue via the wish list. I feel it is a bug.  ... View more

JMP long ago wrote a White Paper on the procedural steps to go thru to produce interpolations (at the X's I DESIRE/NEED) from a spline fit.  Works fine.  As with Excel files, you keep opening and et cetera, so you don't have to create from scratch the formulas and so on.  Every time though it's still a bit tedious.  The rows adding / the columns creation / whole new data table too and so on.  So even with an already done set of formulas, still tedious.  I'd like to see JMP have a formula or "red triangle" that says "USE THE SPLINE TO INTERPOLATE / ESTIMATE VALUES BASED ON THE SPLINE FOR THE VALUES IN THIS ______ COLUMN" and the red triangle would have a dialog to simply ask you for which column of X's are the spline "responses" to be interpolated.  Once JMP has LOESS regression (per my suggestion), DITTO there.  LOESS interpolate with a red triangle to pop up the dialog, for which column of X values do I want LOESS-Interpolated response estimates.  For the motivation, see my LOESS suggestion.  It's in the realm of metrological statistics.  Fully rigorous, but not fancy for the sake of it.  And a FULLY PRACTICAL NEED.  A NEED unfulfilled (the LOESS) and fulfilled only with a big rigamaroll (interpolation of spline via the White Paper involved procedures). ... View more

Let's say you are running a One-way ANOVA with 5 groups.  You test for equal variance and conclude that the assumption of equal variance does not hold.  You then evaluate Welch's test.  The p-value from Welch's test indicates that the 5 group means are not equal.  Is there a simple way to run a multiple comparison test (to compare the 5 means or a Dunnett's like test to compare 4 of the means to a control group) when you have unequal variance?    Ideally, this would be an option found in the "red triangle" when using Fit Y by X (for the One-way ANOVA case).  Perhaps found in the Compare Means choices (see attached for a possible example).   Thanks ... View more

Hi, I think it would be a terrific idea to enable the option to turn on sample size (n) within Least Square Means Tables within the Fit Model Platform, particularly for cases of retrospective data analysis where sample sizes are often unbalanced across groups.  The reason being is that the platform frustratingly shows you the total sample size for the model, but doesn't show you how many samples belong to each respective variable you are testing.     Also, while the LS Means Plots are an excellent visualization tool for comparing the LS means by group, they can be somewhat misleading to the statistically naive because they don't illustrate where the individual data values are located in relation to the mean location and LS mean error bars.  For this I would recommend allowing the user to turn on the points as an overlay to the current Least Square Means Plot.     ... View more

I'd like to have a multivariate x axis in the Fit Y by X platform, with the ability to run Means testing. I use the Variability chart in the variability gauge platform to show how multiple (non-continuous) variables grouped on the X axis impact a Y numeric product response. I'd like to be able to run means ANOVA testing for each of the variables plotted on the X-Axis.  ... View more

I was recently running OC curves to determine AQL and RQL figures. Of interest was the difference in these figures when different sample sizes are used. It would be great to have the option of entering multiple sample sizes (along with population size, and allowable defects), and then plot the overlapped OC curves on one plot to help you visualise the ‘trade-off’ that exists in AQL/RQL figures for various sample size options. At present, JMP will only show curves for individual sample sizes. ... View more

The tolerance intervals in the distribution platform require you to adjust the proportion and confidence levels for each response individually.  It would be great if a preference could set the confidence, proportion and 1-sided/two-sided along with the option to remove the input prompt when performing the analysis. ... View more

Don't make me get SPSS - include an ANOVA with a correction for unequal variances (not to test IF there are unequal variances but to actually run the ANOVA when they ARE unequal variances) ... View more

Dear members of the JMP Team,   May I suggest to implement the QUADE test in the portfolio of the statsitical tests offered by JMP: This test is especially heading at low or very low sample sizes (down to n = 5).   Many thanks for condering my suggestion.   Happy Easter,   Ulrich Schiefer ... View more

Extend Fit Ordinal Logistic by the following two features: - Add the Odds Ratios together with 95%-CIs, - Add a test to check the proportional odds assumption. ... View more

It would be nice if Tolerance Intervals calculated in the Distribution Platform came with a visualization (e.g.) on top of the Histogram. The graph below gives an example. There, I added the Graph Builder visualization of a Tolerance Interval below the Distribution Histogram. I left out Spec-Limits there, but if so specified in the column properties, they should be shown there, as well. Similar to other features in Distribution I image it would be possible to show or hide this visualization via the red triangle menu.   There are further ideas presented in the Wish List in connection with Tolerance Intervals, e.g. https://community.jmp.com/t5/JMP-Wish-List/Setting-Confidence-and-Proportion-to-Cover-for-Tolerance/idi-p/51188 https://community.jmp.com/t5/JMP-Wish-List/3-Sigma-Intervals-and-Tolerance-Intervals-in-Graph-Builder/idi-p/51192 https://community.jmp.com/t5/JMP-Wish-List/Statistical-rationales-for-sample-sizes/idi-p/52052   ... View more

See the attached journal.  This is a simple example of a variability/gauge plot. from one of the sample datasets. I do a lot of beginning JMP user training, and I always show them the variability chart because it is so useful for visulaizing the effects of different X factors on a Y response all on one plot. I would like to be able to do more statistical analysis off this platform. I am looking for the same analysis that is on the fit Y by X platform. For instance in this case an Anova/Tukey means comparison by Gender. And/or a T test comparing gender by each drug. ... View more

Other places where you are picking a column have a little red triangle (lrt) that allows me to select things that "contains" or such.   When I put ~100 (ish) columns in, and want to reduce them in the effect summary, it would be so much nicer if I could limit the shown columns to those containing or not containing some piece of text in the name. ... View more

What inspired this wish list request? When I have been optimizing the profiler I will often want to reset the X factors back to their original state but there is no good way of doing this.  I either have to try and use remember state before I do any optimization or have to manually reset them all back to their mean value.     What is the improvement you would like to see? I'd like the ability to have a "reset to original values" button under the Factor Settings tab     Why is this idea important? It will remove a source of frustration when using the Profiler.     ... View more