New blog post: "(Not) by any stretch of the imagination: A cautionary tale about linear stretching" by Dr. Ranjit K. Singh

| Categories: GESIS-News

This month Dr. Singh writes about 'linear stretching', which is a frequently used approach to combine data from response scales with different numbers of response options. In linear stretching, the scales’ minimum and maximum scores are set as equal, respectively, and all values in between are spread with equal distances within this range. However, while temptingly easy to use, linear stretching runs the risk of seriously biasing analyses in the harmonized dataset.

Part 4: (Not) by any stretch of the imagination: A cautionary tale about linear stretching

DOI: 10.34879/gesisblog.2021.30

Overview of the following parts of the series