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The residuals of a model are the actual values minus the predicted values. Many statistical models make assumptions about the error, which is estimated by the residuals.

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Why are residuals correlated with prediction when using linear mixed model with low number o...

**At this stage I got a problem: the residuals show an upward-trend in relation to the fitted values the residuals show an upward-trend in relation to the random effect prediction, which contradicts the … of residuals") # qq plot of random effect graph.4 <- ggplot(data = db_pred, aes(sample = ranef)) + stat_qq() + stat_qq_line() + theme_bw() + ggtitle("qq plot of random effect") # plot residuals
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