Theory testing and measurement error

Accurate empirical tests of theories and hypotheses are not possible unless the inevitable biases induced into data by measurement error are controlle d for. Yet despite 90 years of recommendations from measurement theory and methodology, some still do not control for these biases in their research. This paper presents simple and direct demonstrations showing why basic meas urement principles require that biases in data created by measurement error be removed and refutes commonly heard objections to the corrections for th ese biases. One factor contributing to resistance on the part of some resea rchers is the fact that most psychologists are not aware that measurement e rror is produced by real psychological processes that can be studied and un derstood. This paper describes those substantive psychological process and shows how each generates a different type of measurement error. We also sho w how different types of reliability estimates assess and calibrate differe nt error processes and types of measurement error, leading directly to conc lusions about which types of reliability estimates are appropriate for meas urement error corrections in different research settings. Failure to contro l for biases induced by measurement error has retarded the development of c umulative research knowledge. It is our hope that this paper will contribut e to removing these hobbles from psychological research.