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python-3.xforest-plots

How can I create a forest plot?

I would like to combine different risk ratios into one forest plot. I would expect the output to be similar to metamiss in STATA or metafor in R. How can I do this in Python?

Solution

  • By using the zEPID package I create a forest plot of different risk ratios.

    import matplotlib.image as mpimg
import numpy as np
import matplotlib.pyplot as plt
import zepid
from zepid.graphics import EffectMeasurePlot

labs = ["ACA(Isq=41.37% Tausq=0.146 pvalue=0.039 )",
        "ICA0(Isq=25.75% Tausq=0.092 pvalue=0.16 )",
        "ICA1(Isq=60.34% Tausq=0.121 pvalue=0.00 )",
        "ICAb(Isq=25.94% Tausq=0.083 pvalue=0.16 )",
        "ICAw(Isq=74.22% Tausq=0.465 pvalue=0.00 )"]
measure = [2.09,2.24,1.79,2.71,1.97]
lower = [1.49,1.63,1.33,2.00,1.25]
upper = [2.92,3.07,2.42,3.66,3.11]
p = EffectMeasurePlot(label=labs, effect_measure=measure, lcl=lower, ucl=upper)
p.labels(effectmeasure='RR')
p.colors(pointshape="D")
ax=p.plot(figsize=(7,3), t_adjuster=0.09, max_value=4, min_value=0.35 )
plt.title("Random Effect Model(Risk Ratio)",loc="right",x=1, y=1.045)
plt.suptitle("Missing Data Imputation Method",x=-0.1,y=0.98)
ax.set_xlabel("Favours Control      Favours Haloperidol       ", fontsize=10)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(True)
ax.spines['left'].set_visible(False)
plt.savefig("Missing Data Imputation Method",bbox_inches='tight')

    Forest plot