This function generates the Q-Q plot for network meta-analyisis model.
object of class NMAoutlier.measures (mandatory).
Plot of Q-squared Mahalanobis distance for each study included in the network meta-analysis. Vertical axis provides the Q-squared Mahalanobis distance for each i study included in the network meta-analysis. Horizontal axis provides Q estimated quantiles (theoretical quantiles from the normal distribution). A reference line is fitted from the cartesian points of the two measures. The Q-Q plot can visualize studies that are away from the reference line (potiential outliers).
Q-Q plot for network meta-analysis has been introduced by Petropoulou (2020).
Maria Petropoulou <email@example.com>
Petropoulou M (2020): Exploring methodological challenges in network meta-analysis models and developing methodology for outlier detection. PhD dissertation
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data(smokingcessation, package = "netmeta") p1 <- netmeta::pairwise(list(treat1, treat2, treat3), list(event1, event2, event3), list(n1, n2, n3), data = smokingcessation, sm = "OR") # Outlier and influential detection measures measures <- NMAoutlier.measures(p1) # Mahalanobis distance values for each study in the network measures$Mah # Q-Q netplot for the network of smoking cessation dataset Qnetplot(measures)
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