Spotfire Statistica® Reliability and Item Analysis

Reliability, as applied to product quality, should be analyzed with the Spotfire Statistica® Process Analysis module. The term reliability used in industrial statistics denotes a function describing the probability of failure as a function of time.

To test specific hypotheses about the relationship between sets of items or different tests (e.g., whether two sets of items measure the same construct, analyze multi-trait, multi-method matrices, etc.) use the Spotfire Statistica® Structural Equation Modeling and Path Analysis article.

This module is focused on reliability of measurement as used in social sciences. Unreliable measurements of people's beliefs, biases or intentions hamper efforts to predict their behavior. The issue of precision of measurement is also a problem when variables are difficult to observe. For example, reliable measurement of employee performance can be difficult to collect but is required for a performance-based compensation system. Another example,  the quality of an educational test could be assessed. 

The quality of a process derives from the quality of the items within the process. This module can be used to construct reliable measurement scales, to improve existing scales, and to evaluate the reliability of scales already in use. Specifically, it will aid in the design and evaluation of sum scales. These are scales made up of multiple individual measurements (e.g., different items, repeated measurements, different measurement devices, etc.). The module builds and evaluate scales following the "classical testing theory model". The classical testing theory model of scale construction has a long history, and there are many textbooks available on the subject.

Note: For additional detailed discussions, see Carmines and Zeller (1980), De Gruijter and Van Der Kamp (1976), Kline (1979, 1986), or Thorndyke and Hagen (1977). The standard formulas from classical testing theory are used to compute Cronbach's Alpha, and for the attenuation correction (see Nunnally, 1970).