[R-meta] Quick question on metaprop output

[Joao Afonso]

Dear all,

I think I have managed to set the model for running the meta-analysis
using metaprop function and run the outlier and influential case
diagnostic using the InfluenceAnalysis function.

I have a question regarding the output of my subgroup analysis. After
running the code below:

metaprop(nlameanimal, ssizeanimal, author, data=prevalence_2020_noout,
method="inverse", sm="PLOGIT", method.tau="DL", method.ci="NAsm",
byvar=lcmbi, tau.common=TRUE,prediction = TRUE)

I get

Number of studies combined: k = 40

                     proportion           95%-CI  z p-value
Fixed effect model       0.1934 [0.1920; 0.1949] --      --
Random effects model     0.2526 [0.1991; 0.3150] --      --
Prediction interval             [0.0445; 0.7104]

Quantifying heterogeneity:
tau^2 = 0.9339; H = 30.19 [29.42; 30.98]; I^2 = 99.9% [99.9%; 99.9%]

Quantifying residual heterogeneity:
tau^2 = 0.7064; H = 24.86 [24.12; 25.62]; I^2 = 99.8% [99.8%; 99.8%]

Test of heterogeneity:
        Q d.f. p-value
 35545.91   39       0

Results for subgroups (fixed effect model):
                                    k proportion           95%-CI
  Q  tau^2
lcmbi = Records                    12     0.1351 [0.1337; 0.1366]
20819.72 0.7064
lcmbi = Locomotion Scoring Method  28     0.3157 [0.3124; 0.3189]
2661.60 0.7064
                                    I^2
lcmbi = Records                   99.9%
lcmbi = Locomotion Scoring Method 99.0%

Test for subgroup differences (fixed effect model):
                      Q d.f. p-value
Between groups 12064.59    1       0
Within groups  23481.32   38       0

Results for subgroups (random effects model):
                                    k proportion           95%-CI
  Q  tau^2
lcmbi = Records                    12     0.1834 [0.1207; 0.2687]
20819.72 0.7064
lcmbi = Locomotion Scoring Method  28     0.2877 [0.2265; 0.3578]
2661.60 0.7064
                                    I^2
lcmbi = Records                   99.9%
lcmbi = Locomotion Scoring Method 99.0%

Test for subgroup differences (random effects model):
                      Q d.f. p-value
Between groups     3.83    1  0.0505
Within groups  23481.32   38       0

Details on meta-analytical method:
- Inverse variance method
- DerSimonian-Laird estimator for tau^2 (assuming common tau^2 in subgroups)
- Logit transformation
- Normal approximation confidence interval for individual studies

Previously I would get the amount of heterogeneity explain by the
moderator with r^2. However I can't find this parameter in the output
above. Am I missing something in my code to generate this parameter?

Many thank and sorry for flooding your email box with so many messages.

Wishing all a great day,

Joao
-- 
João Afonso
DVM, MSc Veterinary Epidemiology
PhD Student
Department of Infection and Global Health
University of Liverpool
+351914812305