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. 2023 Dec 13;4(3):100454. doi: 10.1016/j.xops.2023.100454

Figure 3.

Figure 3

Mean absolute error (MAE) of ordinary least squares (OLS) regression and Bayesian linear mixed models (LMMs) in predicting retinal nerve fiber layer thickness of subsequent OCT tests. Mean absolute error values for the models constructed using the first (A) 3, (B) 4, (C) 5, (D) 6, and (E) 7 OCTs of eyes are shown. The x-axis represents the predicted OCT test. Error bars represent bootstrapped 95% confidence intervals. Three asterisks (∗∗∗) above the OLS estimate indicate the statistical significance of OLS MAE compared with those of all 3 LMMs, whereas 2 asterisks (∗∗) above the OLS estimate indicate the statistical significance of OLS MAE compared with only the Gaussian and Student t estimates. One asterisk (∗) above the Gaussian or Student t estimate indicates statistical significance compared with the LG estimate.