dataFrame.columns.stat — minDetectableEffect()

Description

The minDetectableEffect() method of the stat object computes the minimum detectable effect (MDE) for the selected sample.

Signature

dataFrame.columns(...columnNames).stat.minDetectableEffect({ power: 0.8, significance: 0.05, variants: 1 })
Scope
columns
Family
stat
Returns
object

Arguments

...columnNames ( string[] )
The name of the columns from which to compute the MDE.
  • Column 1: sample size for each observation.
  • Column 2: number of observed successes for the corresponding sample.
options (object)
Minimum detectable effect options.

Options

power (number)
The desired statistical power. (Default: 0.8)
significance (number)
The significance level of the test. (Default: 0.05)
variants (number)
The number of treatment variants compared against the reference group. (Default: 1)

Returns

mask ( number[] )
The minimum detectable effect computed for each observation.

Notes

  • The method requires exactly two selected columns.
  • The method estimates the smallest effect size that can be detected with the available sample size.
  • The method automatically computes the baseline proportion from the selected columns.
  • Larger samples produce smaller detectable effects.
  • Higher statistical power requires larger detectable effects when sample size is fixed.
  • Lower significance levels require larger detectable effects when sample size is fixed.
  • Increasing the number of variants increases the detectable effect required for each comparison.
  • The result should be interpreted as the smallest effect likely to be detected reliably under the specified assumptions.

Example

// computes the MDE from 2 columns of a dataFrame
var mask = dataFrame.columns('visitors', 'conversions').stat.minDetectableEffect();

// add the MDEs to the dataFrame
dataFrame.column('MDE').set(mask);