My Current Thoughts on Coefficient Alpha and Successor Procedures. CSE Report 643

Résumé du livre

Where the accuracy of a measurement is important, whether for scientific or practical purposes, the investigator should evaluate how much random error affects the measurement. New research may not be necessary when a procedure has been studied enough to establish how much error it involves. But, with new measures, or measures being transferred to unusual conditions, a fresh study is in order. Sciences other than psychology have typically summarized such research by describing a margin of error; a measure will be reported followed by a "plus or minus sign" and a numeral that is almost always the standard error of measurement (which will be explained later). The alpha formula is one of several analyses that may be used to gauge the reliability (i.e., accuracy) of psychological and educational measurements. This formula was designed to be applied to a two way table of data where rows represent persons (p) and columns represent scores assigned to the person under two or more conditions (i). "Condition" is a general term often used where each column represents the score on a single item within a test. But it may also be used, for example, for different scorers when more than one person judges each paper and any scorer treats all persons in the sample. Because the analysis examines the consistency of scores from one condition to another, procedures like alpha are known as "internal consistency" analyses.