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Predictive validity

As explained in Effective Data Analysis

Predictive validity is the degree to which a measure is associated with a criterion assessed at a subsequent time.

Predictive validity is the degree to which a measure is associated with a criterion assessed later. It tests whether an earlier measure predicts a subsequent outcome. section 6.3.2

Assess predictive validity by:

  • Collecting the measure first and assessing the criterion at a later, appropriate time window. section 6.3.2
  • Examining the correlation between the earlier measure and the later criterion. section 6.3.2
  • Comparing it with concurrent validity, which evaluates the measure and criterion simultaneously or within similar periods. section 6.3.2

Financial metric across fiscal quarters

Compare a new financial metric from the current fiscal quarter with net income or profit in the following quarter. Strong correlation supports its predictive validity. section 6.3.2

How Effective Data Analysis covers it

How deep it goes
Distinguishes predictive from concurrent validity and specifies timing, criterion selection, and correlation, without detailing statistical procedures.
Examples
Uses a current-quarter financial metric and following-quarter net income or profit as the criterion.
What it assumes
Assumes an identified measure, an external criterion, and a justified later assessment period.
What you can do after
Evaluate whether a measure correlates with an outcome assessed during a later, deliberately selected time window.
How it connects
Connects criterion validity with concurrent validity, correlation, financial metrics, and business performance.
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