Archive for April, 2013

An algebra guy’s take on the meta-analysis posts

April 29, 2013

As I was reading through the meta-analysis posts in order to correct various typos, the forgotten non-probability me woke up and raised the following question:

What if one were to treat the reported RR (t), 95% confidence interval (t_L, t_U) and p-value (p_v) as the true values of the non-reported quantities, in essence ignoring the round-off error?

Could this lead to a (?simpler) solution bypassing the need for Monte Carlo? What this solution would look like and how it differs (implementationally) from the Bayesian one ? More importantly how does it hold up against the Bayesian solution?


Extracting standard errors and effect estimates for meta-analysis: paging Rev Bayes

April 14, 2013

After a very long leave of absence I return to the issue of extracting the effect estimate (T) and standard error (se ) from reported and (rounded to a fixed number of decimal points) relative risk (t ), limits of 95% confidence intervals (t_L and t_U) and p-value (p_v) figures found in scientific publications. This solution is a Bayesian one, requiring nothing more than a straightforward application of the Bayes theorem for the posterior distribution of the A straightforward application of Bayes theorem for the quantities T, se given the t, t_L, t_U, p_v :

P(T,se|t, t_L, t_U, p_v) \propto P(t|T,se,t_L, t_U, p_v) \times P(T,se|t_L, t_U, p_v)