Archive for the ‘measurement error’ Category

Extracting standard errors (cont’d) : critique

February 1, 2013

In a previous post I presented a possible solution to the extraction of standard errors and hazard ratios from publications in which only rounded approximations to the risk ratios and the associated 95% confidence interval are considered.

This solution, is subject to a criticism that I will now discuss : it suffers from an internal contradiction. Specifically, while one can use two of the three pieces of data (the actual risk ratio and the two limits of the 95% CI) simultaneously, one will arrive at different and conflicting probability estimates which is clearly not what one wants!.



Extracting standard errors from 95%CI for meta-analysis (or weird uses for measurement error models)

December 29, 2012

I was recently confronted with the task of running a meta-analysis of a subject in which the various studies had reported (adjusted) measures of treatment efficacy on various continuous outcomes. This is one of the areas in which the data for meta-analysis comes not in the usual form of #events and #patients(N) , but as treatment effects and their associated standard errors. Not too uncommon examples include the effects of a given intervention on Blood Pressure, Cholesterol levels, Psychometric scales, Cox regression Hazard Ratios or Logistic Regression Odds Ratios etc. And then it hit me: for almost all of the studies I wanted to pool, I did have access at all to the actual data that I had to process!! For sure, there were treatment effects (actually hazard ratios,HRs, for my project) in the papers but the standard errors were not reported; furthermore, the information that was actually contained in the manuscripts (HRs, 95%CI and the p-value) was not the “real thing” but its approximation, rounded down to one (and sometimes two) significant digits.

I’m sure that others have run into this issue previously, but I have never seen a formal, discussion for handling this missing data problem. (more…)