Qnetplot {NMAoutlier} | R Documentation |
Q-Q plot for network meta-analysis (Q-Q netplot).
Description
This function generates the Q-Q plot for network meta-analyisis model.
Usage
Qnetplot(data)
Arguments
data |
object of class NMAoutlier.measures (mandatory). |
Details
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).
Author(s)
Maria Petropoulou <petropoulou@imbi.uni-freiburg.de>
References
Petropoulou M (2020): Exploring methodological challenges in network meta-analysis models and developing methodology for outlier detection. PhD dissertation
Examples
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)