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ISSUES AND STRATEGIES FOR REDUCING THE LENGTH OF SELF‐REPORT SCALES
Author(s) -
STANTON JEFFREY M.,
SINAR EVAN F.,
BALZER WILLIAM K.,
SMITH PATRICIA C.
Publication year - 2002
Publication title -
personnel psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.076
H-Index - 142
eISSN - 1744-6570
pISSN - 0031-5826
DOI - 10.1111/j.1744-6570.2002.tb00108.x
Subject(s) - psychology , scale (ratio) , consistency (knowledge bases) , construct (python library) , quality (philosophy) , set (abstract data type) , social psychology , applied psychology , computer science , artificial intelligence , philosophy , physics , epistemology , quantum mechanics , programming language
Greater understanding of the complex interrelationships among work‐relevant constructs has increased the number of constructs on organizational surveys. Good psychometric practice also dictates the use of multiple items per construct. The net result has been longer surveys. Longer surveys take more time to complete, tend to have more missing data, and have higher refusal rates than short surveys. Arguably, then, techniques for reducing the length of scales while maintaining psychometric quality are worthwhile. Little guidance exists on how to reduce the length of a multi‐item scale and we argue that the most common technique, maximizing internal consistency, is problematic and should be avoided. We present a set of item “quality indices” to help conceptualize the competing issues that influence item retention decisions. Statistical analysis of an example case using these indices suggested that there are 3 key aspects of item quality to consider when reducing a scale. We describe strategies that can assist scale developers in using these 3 aspects of item quality when making scale reduction decisions.