[R-meta] An issue with selmodel( type="step")

[Will Hopkins]

Wolfgang, according to the documentation "there must be at least one
observed p-value within each interval to fit this model. If this is not the
case, an error will be issued." When I tried it with steps=(0.025) for a
simulated meta-analysis in which all estimates were significant (p<0.05), it
issued an error ("One or more intervals do not contain any observed
p-values"), but the analysis nevertheless produced a result. When I ran it
with 2500 such simulations, it produced point estimates for the fixed
effects with 2456 simulations, and confidence limits with 2399. See below
for a typical result. The selection model results show 0.0000 for the
estimated probability of non-significant p values, as expected, so how is it
able to make adjustments?

 

Type="steps" seems to be about as good as type="beta" for bias and coverage
with this particular set of study characteristics, but the beta type runs so
slowly that I have only used it for 100 simulations for comparison so far.
It took more than an hour, and only 51/100 produced confidence limits for
the fixed effects, so in these respects the steps type is definitely
better). 

 

Will

 

Mixed-Effects Model (k = 22; tau^2 estimator: ML)

 

tau^2 (estimated amount of residual heterogeneity): 0.2541 (SE = 0.2288)

tau (square root of estimated tau^2 value):         0.5041

 

Test for Residual Heterogeneity:

LRT(df = 1) = 4.9738, p-val = 0.0257

 

Test of Moderators (coefficients 1:2):

QM(df = 2) = 94.2813, p-val < .0001

 

Model Results:

 

               estimate      se    zval    pval    ci.lb   ci.ub      

xxx$SexFemale    2.9331  0.3022  9.7046  <.0001   2.4359  3.4302  *** 

xxx$SexMale      1.1294  0.7376  1.5312  0.1257  -0.0838  2.3425      

 

Test for Selection Model Parameters:

LRT(df = 1) = 22.8488, p-val < .0001

 

Selection Model Results:

 

                     k  estimate   se  zval  pval  ci.lb  ci.ub   

0     < p <= 0.025  22    1.0000  ---   ---   ---    ---    ---   

0.025 < p <= 1       0    0.0000   NA    NA    NA     NA     NA 

 


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