[R-meta] confidence interval very large

[Huang]

Thanks so much for your responses. Dr.Pustejovsky, besides confidence
interval, are other results (e.g., robust SE and t-tests & F-tests
trustable) when df < 4? I appreciate your help.

Best wishes,
Huang

On Wed, Jul 27, 2022 at 11:51 AM James Pustejovsky <jepusto using gmail.com>
wrote:

> Hi Huang,
>
> 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.
>
> James
>
> 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,
>> HUang
>>
>>
>> >
>> >
>>
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>>
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