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. Author manuscript; available in PMC: 2022 Nov 29.
Published in final edited form as: Neurobiol Aging. 2022 Jul 5;118:88–98. doi: 10.1016/j.neurobiolaging.2022.06.013

Table 3.

Competitive Hierarchical Linear Regression Results

Model Formula DF AIC BIC R2 Adjusted R2 ΔR2
base CSF sTREM2 ~ age + sex + education + cognitive diagnosis 150 2778 2798 0.118 0.089 N/A
1 CSF sTREM2 ~ base covariates + p-tau181 149 2747 2770 0.288 0.259 0.169
2 CSF sTREM2 ~ base covariates + p-tau181 + Aβx-40 148 2738 2765 0.333 0.302 0.046
3 CSF sTREM2 ~ base covariates + p-tau181 + Aβx-40 + CSF/plasma Albumin ratio 143 2636 2664 0.481 0.452 0.148

ΔR2 = change in R2 from previous nested model. Akaike information criterion (AIC) and Bayesian information criterion (BIC) calculations derived as follows: AIC = 2K – 2ln(L); where K = number of model parameters, and ln(L) = model log-likelihood. BIC = (RSS+log(n)dσ 2) / n; where RSS = residual sum of squares, n = total observations, d = number of predictors, and σ = estimate of variance of the error associated with each response measurement.