[R-meta] confidence interval very large
jepu@to @end|ng |rom gm@||@com
Wed Jul 27 17:50:48 CEST 2022
The wide confidence interval is due to having only one degree of freedom (a
t distribution with 1 degree of freedom is equivalent to the dreaded,
ill-behaved Cauchy distribution). I would not trust confidence intervals
based on so few degrees of freedom. Tipton (2015 Psych Methods) suggests
disregarding results based on RVE if df < 4.
Generally, low degrees of freedom means that there is very little
information available to estimate standard errors--i.e., the SEs will be
very noisy. This can happen, for instance, if you are comparing two
different categories of effect sizes and one of the categories only appears
in two studies.
You could, in these instances, report the model-based confidence interval,
but in doing so you're relying on all of the additional assumptions of the
model (such as homoskedasticity of random effects, correctness of
correlations between sampling errors). So you would need to be clear about
these caveats. You might consider also reporting sensitivity analyses under
some range of plausible alternative assumptions.
On Tue, Jul 26, 2022 at 10:39 PM Huang <wuhuang0421 using gmail.com> wrote:
> Hi folks,
> I am using conf_int to calculate the confidence interval but the results
> showed the confidence interval are very large. For example, I have a mean
> estimate 0.1655 with a SE of 0.3014 (df = 1), but the 95% confidence
> interval is [-3.659, 3.990]. Is this correct? Should I report the model
> based confidence interval instead of RVE based? Thank you so much for
> taking time to respond to my email.
> Best wishes,
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