QScript StatisticalAssumptions

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StatisticalAssumptions

Allows one to obtain cell significance, cell arrow size and cell font color from input p-values using a table's or plot's statistical assumptions.

arrows(p_values, signs)

Given a 2D array of p-values, returns a corresponding array with arrow sizes. The signed values determine whether to use up or down arrows.
p_valuesA matrix of p-values.
signsA matrix of signed values.
Example:
var arrows = table.cellArrows;
arrows[0][0] = table.statisticalAssumptions.arrowSizes([[0.00001]]);
table.cellArrows = arrows;

cellMultipleComparisonCorrection

A read-only property that is true if multiple comparison correction is enabled.
Example:
alert("Multiple comparison correction is " + (table.statisticalAssumptions.cellMultipleComparisonCorrection ? "enabled" : "disabled"))

equals(obj)

Whether two objects are the same.
objThe object to compare against.
Returns:true or false
Example:
data_file.getQuestionByName('Q2').equals(data_file.questions()[0])

fontColors(p_values, signs)

Given 2D arrays of p-values and signed values, returns a corresponding array with font colors. The signed values determine whether to use positive or negative colors.
p_valuesA matrix of p-values.
signsA matrix of signed values.
Example:
var colors = table.cellColors;
colors[0][0] = table.statisticalAssumptions.fontColors([[0.00001]], [[-0.01]]);
table.cellColors = colors;

overallSignificanceLevel

A read-only property that returns the overall significance level (e.g. 0.05).
Example:
alert('The overall significance level is: ' + table.statisticalAssumptions.overallSignificanceLevel);

significance(p_values)

Given a 2D array of p-values, returns an array where each element is true if the corresponding p-value is less than or equal to the overallSignificanceLevel and false otherwise. Note that Q uses corrected p-values when determining cell significance, and this function assumes that the input p-values are already corrected.
p_valuesA matrix of p-values.
Example:
var significance = table.cellSignificance;
significance[0][0] = table.statisticalAssumptions.significance([[0.00001]]);
table.cellSignificance = significance;

type

Returns 'StatisticalAssumptions'.

See also