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. 2022 Jan 13;145(4):1338–1353. doi: 10.1093/brain/awac010

Table 2.

Relative contributions of structural LNM-LL and functional LNM-LL to the prediction of latent growth curve intercept and slope parameters beyond LBM-LL and one another

Model comparison Chi-squared difference ΔR2 12-month intercept ΔR2 Slope
Boston Naming Test
 sLNM-LL Over LBM-LL 19.12** 0.021 0.182
 fLNM-LL Over LBM-LL 29.65* 0.123 0.127
 sLNM-LL Over fLNM-LL 36.00*** 0.042 0.177
 fLNM-LL Over sLNM-LL 30.47* 0.129 0.064
Complex Ideational Material Test
 sLNM-LL Over LBM-LL 24.9*** 0.117 0.29
 fLNM-LL Over LBM-LL 22.00** 0.141 0.158
 sLNM-LL Over fLNM-LL 33.63*** 0.038 0.347
 fLNM-LL Over sLNM-LL 30.79*** 0.206 0.035
Hopkins Verbal Learning Test Delayed Recall
 sLNM-LL Over LBM-LL 4.33 −0.006 0.144
 fLNM-LL Over LBM-LL 2.8 0.019 0.02
 sLNM-LL Over fLNM-LL 8.59* 0.021 0.142
 fLNM-LL Over sLNM-LL 5.16 0.04 0.014
Action Research Arm Test
 sLNM-LL Over LBM-LL 18.31* 0.092 0.064
 fLNM-LL Over LBM-LL 0.053 0.000 0.000
 sLNM-LL Over fLNM-LL 42.99*** 0.19 0.088
 fLNM-LL Over sLNM-LL 3.78 0.012 0.003
*

P < 0.05, **P < 0.01, ***P < 0.001.

ΔR2 = Change in R2 from null model to alternative model; fLNM = functional LNM; sLNM = structural LNM.