TY - JOUR
T1 - A non-arbitrary method of identifying and scaling latent variables in SEM and MACS models
AU - Little, Todd D.
AU - Siegers, David W.
AU - Card, Noel A.
N1 - Funding Information:
This work was supported in part by grants from the NIH to the University of Kansas through the Mental Retardation and Developmental Disabilities Research Center (5 P30 HD002528) and the Center for Biobehavioral Neurosciences in Communication Disorders (5 P30 DC005803) and by an NIH Individual National Research Service Award (1F32 MH072005) to the third author.
PY - 2006
Y1 - 2006
N2 - A non-arbitrary method for the identification and scale setting of latent variables in general structural equation modeling is introduced. This particular technique provides identical model fit as traditional methods (e.g., the marker variable method), but it allows one to estimate the latent parameters in a nonarbitrary metric that reflects the metric of the measured indicators. This technique, therefore, is particularly useful for mean and covariance structures (MACS) analyses, where the means of the indicators and latent constructs are of key interest. By introducing this alternative method of identification and scale setting, researchers are provided with an additional tool for conducting MACS analyses that provides a meaningful and nonarbitrary scale for the estimates of the latent variable parameters. Importantly, this tool can be used with single-group single-occasion models as well as with multiple-group models, multiple-occasion models, or both.
AB - A non-arbitrary method for the identification and scale setting of latent variables in general structural equation modeling is introduced. This particular technique provides identical model fit as traditional methods (e.g., the marker variable method), but it allows one to estimate the latent parameters in a nonarbitrary metric that reflects the metric of the measured indicators. This technique, therefore, is particularly useful for mean and covariance structures (MACS) analyses, where the means of the indicators and latent constructs are of key interest. By introducing this alternative method of identification and scale setting, researchers are provided with an additional tool for conducting MACS analyses that provides a meaningful and nonarbitrary scale for the estimates of the latent variable parameters. Importantly, this tool can be used with single-group single-occasion models as well as with multiple-group models, multiple-occasion models, or both.
UR - http://www.scopus.com/inward/record.url?scp=33644671129&partnerID=8YFLogxK
U2 - 10.1207/s15328007sem1301_3
DO - 10.1207/s15328007sem1301_3
M3 - Article
AN - SCOPUS:33644671129
SN - 1070-5511
VL - 13
SP - 59
EP - 72
JO - Structural Equation Modeling
JF - Structural Equation Modeling
IS - 1
ER -