The PValues data table contains a row for each pair consisting of a Y variable and a model Effect. The columns in the table include the following. If you select the Robust Fit option on the launch window, the models are fit using Huber M-estimation.
Y
The specified response columns.
Effect
The specified model effects.
FRatio
The test statistic for a test of the Effect. This is the value found in the Effect Tests report in Least Squares Fit.
PValue
The p-value for the significance test corresponding to the FRatio. See Effect Tests in Fitting Linear Models for more information about Effect Tests.
LogWorth
The quantity -log10(p-value). This transformation adjusts p-values to provide an appropriate scale for graphing. A value that exceeds 2 is significant at the 0.01 level (because -log10(0.01) = 2).
FDR PValue
The False Discovery Rate p-value calculated using the Benjamini-Hochberg technique. This technique adjusts the p-values to control the false discovery rate for multiple tests. For more information about the FDR correction, see Benjamini and Hochberg (1995). For more information about the false discovery rate, see The False Discovery Rate or Westfall et al. (2011).
FDR LogWorth
The quantity -log10(FDR PValue). This is the best statistic for plotting and assessing significance. Note that small p-values result in high FDR LogWorth values.
Rank Fraction
The rank of the FDR LogWorth expressed as a fraction of the number of tests. If the number of tests is m, the largest FDR LogWorth value has Rank Fraction 1/m, and the smallest has Rank Fraction 1. Equivalently, the Rank Fraction ranks the p-values in increasing order, as a fraction of the number of tests. The Rank Fraction is used in plotting the PValues and FDR PValues in rank order of decreasing significance.
Test DF
The degrees of freedom for the effect test.
The PValues data table also contains a table variable called Original Data that gives the name of the data table that was used for the analysis. If you specified a By variable, JMP creates a PValues table for each level of the By variable, and the Original Data variable gives the By variable and its level.