. Author manuscript; available in PMC: 2023 Apr 14.

Published in final edited form as: J Exp Psychol Gen. 2022 Sep 22;152(3):763–779. doi: 10.1037/xge0001290

Table 4.

Standardized Factor Loadings of Drift Rates in Measurement Models of LCSMs

Masking time	Letters		Digits		Figures

	Pretest	Posttest	Pretest	Posttest	Pretest	Posttest

12ms	.381^*	.499^*	.448^*	.597^*	1.047^*^a	1.025^*^a
24ms	.360^*	.452^*	.515^*	.568^*	.911^*	1.091^*^a
47ms	.541^*	.619^*	.552^*	.652^*	.763^*	.901^*
94ms	.664^*	.659^*	.727^*	.790^*	.628^*	.836^*
all	.496^*	.587^*	.599^*	.709^*	.786^*	.926^*

Note. Strong measurement invariance; correlated residuals for same tasks at pretest and posttest, as well as for the Letters and Digits task at pretest and at posttest.

p < .05.

Standardized factor loadings > 1.00 indicate that the residual variance is estimated slightly negative. In these cases, it is likely that the true variance of the indicator tasks can almost completely be explained by the common factor, so that the true residual variance is very small, and error of estimation may lead to a negative variance estimate.