Reliability and Item Analysis

In many areas of research, the precise measurement of hypothesized processes or variables (theoretical constructs) poses a challenge by itself. For example, in psychology, the precise measurement of personality variables or attitudes is usually a necessary first step before any theories of personality or attitudes can be considered. In general, in all social sciences, unreliable measurements of people's beliefs or intentions will obviously hamper efforts to predict their behavior. The issue of precision of measurement will also come up in applied research whenever variables are difficult to observe. For example, reliable measurement of employee performance is usually a difficult task; yet, it is obviously a necessary precursor to any performance-based compensation system.

In all of these cases, Reliability & Item Analysis can be used to construct reliable measurement scales, to improve existing scales, and to evaluate the reliability of scales already in use. Specifically, Reliability & Item Analysis will aid in the design and evaluation of sum scales, that is, scales that are made up of multiple individual measurements (e.g., different items, repeated measurements, different measurement devices, etc.). Reliability & Item Analysis provides numerous statistics that allow the user to build and evaluate scales following the so-called classical testing theory model.

For more information, see the Reliability and Item Analysis Introductory Overview.

The term reliability used in industrial statistics denotes a function describing the probability of failure (as a function of time). For a discussion of the concept of reliability as applied to product quality (e.g., in industrial statistics), refer to Reliability/Failure Time Analysis in the Process Analysis Introductory Overview (see also Repeatability and Reproducibility in the same overview and the Survival/Failure Time Analysis Introductory Overviews). For a comparison between these two (very different) concepts of reliability, see Reliability.