[R-meta] Adjusting for small sample sizes in metafor

[Célia Sofia Moreira]

Dear Professor Wolfgang,

I have a basic question regarding effects calculation in a pretest-psttest
control design, using metafor. I'm following your "Morris (2008)" example
to calculate effect sizes and variances. However, I do not have
pretest-posttest correlations, and so, I considered a reasonable range of
correlation values -r-, together with a sensitive analysis. Moreover, I
have small sample sizes and so I want to adjust sampling variance
estimates. Concerning the outputs, I obtained that:

1) Changing r only affects the variance estimates, not the effect sizes
2) The unbiased estimates of the sampling variances (vtype="UB") provides
the same results. I mean that

datT <- escalc <http://finzi.psych.upenn.edu/library/metafor/html/escalc.html>(measure="SMCR",
m1i=m_post, m2i=m_pre, sd1i=sd_pre, ni=ni, ri=ri, data
<http://stat.ethz.ch/R-manual/R-devel/library/utils/html/data.html>=datT)

and

datT <- escalc <http://finzi.psych.upenn.edu/library/metafor/html/escalc.html>(measure="SMCR",
m1i=m_post, m2i=m_pre, sd1i=sd_pre, ni=ni, ri=ri, vtype="UB", data
<http://stat.ethz.ch/R-manual/R-devel/library/utils/html/data.html>=datT)

provide the same sampling variance estimates.

Should I be concerned about these two facts?

Thank you very much,
celia

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