Publication date: 08/13/2020

PValues Data Table Columns

The PValues data table displays columns containing measures and statistics that are appropriate for the selected fit and combination of Y and X modeling types. The columns in the data table include:

Y

The specified response columns.

X

The specified factor columns.

Count

The number of rows used for testing, or the corresponding sum of the Freq or Weight variable.

PValue

The p-value for the significance test corresponding to the pair of Y and X variables. For more information about Fit Y by X statistics, see Introduction to Fit Y by X of Basic Analysis.

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. If there is no Group variable, the set of multiple tests includes all tests displayed in the table. If there is a Group variable, the set of multiple tests consists of all tests conducted for each level of the Group variable. 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.

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. Cells corresponding to FDR LogWorth values greater than two (p-values less than 0.01) are colored with an intensity gradient.

Effect Size

Indicates the extent to which response values differ across the levels or values of X. Effect sizes are scale invariant.

When Y is continuous, the effect size is the square root of the average sum of squares for the hypothesis divided by a robust estimate of the response standard deviation. If the interquartile range (IQR) is nonzero and IQR > range/20, the standard deviation estimate is IQR/1.3489795. Otherwise the sample standard deviation is used.

When Y is categorical and X is continuous, the effect size is the square root of the average ChiSquare value for the whole model test.

When Y and X are both categorical, the effect size is the square root of the average Pearson ChiSquare.

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.

YMean

The mean of Y.

SSE

Appears when Y is continuous. The sum of squares for error.

DFE

Appears when Y is continuous. The degrees of freedom for error.

MSE

Appears when Y is continuous. The mean squared error.

F Ratio

Appears when Y is continuous. The F Ratio for the analysis of variance or regression test.

RSquare

Appears when Y is continuous. The coefficient of determination, which measures the proportion of total variation explained by the model.

Intercept

Appears when Y and X are both continuous. The intercept of the regression model relating the corresponding pair of Y and X variables.

Slope

Appears when Y and X are both continuous. The slope of the regression model relating the corresponding pair of Y and X variables.

DF

Appears when Y and X are both categorical. The degrees of freedom for the ChiSquare test.

LR Chisq

Appears when Y and X are both categorical. The value of the Likelihood Ratio ChiSquare statistic.

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