What Does Spearman-Brown Reveal About Your Test?

Spearman-Brown Prophecy Formula

The Spearman-Brown Prophecy (SBP) formula is a cornerstone in psychometric testing, offering a method to predict the impact of changing the length of psychological and educational tests on their reliability. Developed in the early 20th century by psychologists Charles Spearman and William Brown, this formula has become integral to ensuring that tests yield consistent and accurate results over time, irrespective of modifications to their length (Spearman, 1910; Brown, 1910). Its development marked a significant advancement in psychometric theory, providing a mathematical solution to the challenge of test length versus reliability trade-off.

The essence of the SBP formula lies in its ability to estimate the reliability of a test after adjusting its number of items. This is critical for researchers and educators aiming to enhance a test’s reliability without compromising its practicality or validity. The formula is expressed as:

\[ r' = \frac{kr}{1 + (k-1)r} \]


One critical application of the SBP formula involves the adjustment of split-half reliability estimates. When a test's reliability is measured using the split-half method, this typically reflects the reliability of only half the test. To correct for this underestimation and estimate the reliability of the full test, \(k=2\) is used in the SBP formula. This adjustment is essential for accurately reflecting the test's overall reliability, especially when the initial reliability is measured by the split-half method.

The practical applications of the SBP formula extend beyond academic assessments to include any scenario where test reliability is paramount. It assists in making informed decisions about test design, helping to balance between test length and reliability. This formula thereby facilitates the optimization of test design for both practicality and psychometric robustness.

Understanding and applying the Spearman-Brown Prophecy formula is vital for psychometricians, educational researchers, and anyone involved in the development and validation of testing instruments. It underscores the importance of reliability in measurement and offers a mathematical approach to achieving it through strategic test design. The enduring relevance of this formula in psychometrics exemplifies its foundational role in the construction and evaluation of reliable measurement instruments across various fields of study (Guilford & Fruchter, 1978).


Brown, W. (1910). Some experimental results in the correlation of mental abilities. British Journal of Psychology, 3(2), 296-322.

Guilford, J. P., & Fruchter, B. (1978). Fundamental statistics in psychology and education (6th ed.). McGraw-Hill.

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

Spearman, C. (1910). Correlation calculated from faulty data. British Journal of Psychology, 3, 271-295.

Author: Cogn-IQ.org
Publication: 2023