![]() Then, click on the variable in Column 2 in the Select Columns box and then click X, Factor. Enter the appropriate frequencies for each contingency table cell in Column 3.Ĭhoose Analyze from the top row of the JMP spreadsheet, select Fit Y by X.įrom the Select Columns box click on the variable in Column 1 and then and click Y, Response. With a JMP Data Table open, enter the categories appearing in the rows of the contingency table into Column 1 and the categories appearing in the columns of the contingency table into Column 2, repeating categories to include all intersections of rows and columns from the contingency table. Select Run.Ĭhi-Square Distribution Test for Association Highlight the names of your data in Column 2 and Column 3 at the same time in the Select Columns box. Label the columns as fitting.Ĭlick on the name of your data in Column 1 in the Select Columns box and click Y. Repeat this step to add a third column.Įnter the row names into Column 2 and the column numbers into Column 3. In the New Column window that opens, click the dropdown beside Modeling Type. Note: You can adjust the α level by clicking the red triangle next to Oneway Analysis of… and then select Set α Level. Click OK.įrom the Oneway Analysis output, click on the red triangle next to Oneway Analysis of…, then click on Compare Means and select All Pairs, Tukey HSD. Click on your response and then click on Y, Response. ![]() Select Analyze in the top row of the JMP spreadsheet and then select Fit Y by X.įrom the Select Columns box, click on your treatments, then click on X, Factor. In the window that opens, click on the Red Triangle and select Means/Anova.Įnter the data for the treatments in one column of an open JMP data table and a column for the response variable in another column and label the columns accordingly. Click on the name of your data in Column 2 in the Select Columns box and click X, Factor. Label the columns as fitting.Ĭlick on the name of your data in Column 1 in the Select Columns box and click Y, Response. Select OK.Įnter the groups into Column 2 for each data value. One option is also to remove the effect of users preferences, but depending on the platform this might take a lot of effort to set all default values to 1 or 0.Enter all of the data into Column 1, one column at a time. Names Default To Here(1) Īxisbox = (Report(dist) << XPath("//ScaleBox")) Īxisbox << Add Ref Line(55, "Dotted", red, "F mean", 2) Usually I use XPath with some combination of << child, << sib, << parent and so on. Sometimes these have to be built a bit case by case. If there's multiple distributions in the report, loop through or be more specific when grabbing the xpath. use xpList instead of referencing an axisbox index. XpList = myrpt << XPath("//DropBox/BorderBox/AxisBox") // returns a list of matching occurrences Hopefully this stands the test of time, but it's worked for me so far. Meaning, don't just look for an axis box as there could be 4 of them, rather look for the axis box in a border box in a drop box, which appears to be unique to the 'main' axis. You can look at the xml, or look at the properties of an output report to see what might work. I probably could have found a workaround there, but ended up using xpath. I tried doing a 'get items' but I think it always returned 4 even though some were empty. But if the script is deployed widely, you need to account for other user preference settings. if you always have the same settings, you can hard code it and it should be fine. But if you add any of the other axes, the index becomes 2, 3 or 4 (the max of the total axes displayed. In the distribution platform, if you don't have the probability, density, and show counts axes set to be displayed, then the index for the axis box of the distribution's data is 1, meaning you can reference it with report(xxxx), similar to Jarmo's post above. I would not expect to be an issue in graph builder, mostly because I don't think user preferences come into play as much. It's related to the Distribution platform specifically (not graph builder which was in the original question), but may apply to other platforms depending on user preferences, I'm not sure. This is tangentially related but I'll put it here anyway.
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