<p>In a <a href="https://stats.stackexchange.com/a/91181/1390">recent Answer</a> I posted on CV, I included markdown for a link, just like I have done thousands of times on CV and SO. This time the link text wasn't rendered as a hyperlink, either using the inline notation:</p>

<pre><code>[link text](URL)
</code></pre>

<p>or the reference link notation:</p>

<pre><code>[link text][1]
....
[1]: URL
</code></pre>

<p>Rendering links seems to be working just fine here on CV Meta. Have I lost the plot and gotten my syntax in a muddle or is there some other problem with CV's rendering?</p>

<p>I include the entire source for my Answer below to save you heading to CV to look at it. The <strong>Gelman et al 2008</strong> part should be rendered as a hyperlink. The Answer uses the reference notation, but I've tried the inline notation as well with no luck.</p>

<pre><code>Given the stated sample size (150,000), why do you think there will be bias due to "small sample" size? You have 1500 observations of the positive case, which I wouldn't normally think of as being *small*.

An alternative in R is the **brglm** package, which also implements Firth's method.

However, I was recently pointed to a paper [Gelman et al 2008][1] which showed Firth's method performing quite badly compared to other methods for bias reduction, in a Bayesian context. The authors of that paper wrote the `bayesglm()` function in R package **arm** to provide a range of priors on the model coefficients (Firth's method boils down to a particular choice of prior in the model; a Jeffreys prior). My main reason for mentioning it is that it may also work more efficiently than the options considered thus far.

(For some reason the markdown isn't rendering the link to the paper: http://www.stat.columbia.edu/~gelman/research/published/priors11.pdf‎)

[1]: http://www.stat.columbia.edu/~gelman/research/published/priors11.pdf‎
</code></pre>
