Qnetplot: Q-Q plot for network meta-analysis (Q-Q netplot).

In NMAoutlier: Detecting Outliers in Network Meta-Analysis

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 <[e-mail]>

References

Petropoulou M (2020): Exploring methodological challenges in network meta-analysis models and developing methodology for outlier detection. PhD dissertation

Examples

library("netmeta")
data(smokingcessation)

p1 <- 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)

NMAoutlier documentation built on April 3, 2025, 6:23 p.m.