TY - JOUR
T1 - Why researchers should not ignore measurement error and skewness in questionnaire item scores
AU - Lodder, P.
PY - 2023
Y1 - 2023
N2 - Researchers commonly study associations between latent variables measured with items showing ordinal and skewed score distributions. Researchers can estimate associations between latent variables according to several statistical methods that vary for instance in how they handle the presence of skewness and measurement error in the item scores. In this commentary I use a computer simulation to illustrate that ignoring skewness or measurement error in questionnaire item scores often results in biased effect estimates, especially when testing interaction effects.
AB - Researchers commonly study associations between latent variables measured with items showing ordinal and skewed score distributions. Researchers can estimate associations between latent variables according to several statistical methods that vary for instance in how they handle the presence of skewness and measurement error in the item scores. In this commentary I use a computer simulation to illustrate that ignoring skewness or measurement error in questionnaire item scores often results in biased effect estimates, especially when testing interaction effects.
KW - Variables
UR - http://www.scopus.com/inward/record.url?scp=85133450480&partnerID=8YFLogxK
U2 - 10.1080/2153599X.2022.2070250
DO - 10.1080/2153599X.2022.2070250
M3 - Comment/Letter to the editor
SN - 2153-599X
VL - 13
SP - 321
EP - 324
JO - Religion, Brain & Behavior
JF - Religion, Brain & Behavior
IS - 3
M1 - 2070250
ER -