Accounting for centre-effects in multicentre trials with a binary outcome – when, why, and how?

Open Access Research article Accounting for centre-effects in multicentre trials with a binary outcome – when, why, and how? Brennan C Kahan Correspondence: Brennan C Kahan [email protected] Author Affiliations Pragmatic Clinical Trials Unit, Queen Mary University of London, 58 Turner Street, London E1 2AB, UK MRC Clinical Trials Unit at UCL, 125 Kingsway, London WC2B 6NH, UK BMC Medical Research Methodology 2014, 14:20 doi:10.1186/1471-2288-14-20 The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2288/14/20 Received: 5 July 2013 Accepted: 3 February 2014 Published: 10 February 2014 © 2014 Kahan; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. Formula display: Abstract Background It is often desirable to account for centre-effects in the analysis of multicentre randomised trials, however it is unclear which analysis methods are best in trials with a binary outcome. Methods We compared the performance of four methods of analysis (fixed-effects models, random-effects models, generalised estimating equations (GEE), and Mantel-Haenszel) using a re-analysis of a previously reported randomised trial (MIST2) and a large simulation study. Results The re-analysis of MIST2 found that fixed-effects and Mantel-Haenszel led to many patients being dropped from the analysis due to over-stratification (up to 69% dropped for Mantel-Haenszel, and up to 33% dropped for fixed-effects). Conversely, random-effects and GEE included all patients in the analysis, however GEE did not reach convergence. Estimated treatment effects and p-values were highly variable across different analysis methods. The simulation study found that most methods of analysis performed well with a small number of centres. With a large number of centres, fixed-effects led to biased estimates and inflated type I error rates in many situations, and Mantel-Haenszel lost power compared to other analysis methods in some situations. Conversely, both random-effects and GEE gave nominal type I error rates and good power across all scenarios, and were usually as good as or better than either fixed-effects or Mantel-Haenszel. However, this was only true for GEEs with non-robust standard errors (SEs); using a robust ‘sandwich’ estimator led to inflated type I error rates across most scenarios. Conclusions With a small number of centres, we recommend the use of fixed-effects, random-effects, or GEE with non-robust SEs. Random-effects and GEE with non-robust SEs should be used with a moderate or large number of centres

What\u27s In? - A Name! - Part V

The consolidations in the list below are the result of eradicating four-letter male names from thirty words and closing up any subsequent spaces formed. (Perhaps a more apt title would have been Four - The Boys ?) Restore as many of these guys as you can to their rightful positions in order to identify the original words. Fear not, however - MENsa membership is not a prerequisite for a successful pursuit of this challenge

WITWITs - Part 1

A WITWIT is merely an acronym for Where In The World Is That?, an orthographic challenge that I introduced in May I Have A Word With You?. In the first of this seven-part series, two dozen letter sequences have been extracted, without interruption, from either the beginning, middle, or end of a word. Reinserting each into its proper position at the rate of one per hour, you\u27ll identify the sources of all these sequences in a single day. Moreover, you\u27ll certainly have the last laugh and avoid a fracas provided you recognize that HAHA came from BROUHAHA

Dissections

A word puzzle

What\u27s In? - A Name! - Part IV

The fourth chapter in this continuing saga epitomizes the maxim that variety is the spice of life. Presented below are forty new word compressions resulting from the deletion of a person\u27s name. This time, in addition to evenly distributing the genders of these individuals, the lengths of their names are not supplied

Hebrew Scandinavian Charades

Fifteen Hebrew Scandinavian charades can be constructed from the sixty components that are presented below, wherein fifteen decoys have been included to heighten the challenge. Are you up for it

The A List

Each entry in the A list is made up of two words, names, or phrases that have at least two overlapping letters and in which each blank stands for a consonant, e.g. XAXAXAXXAX (6; 3-4) represents a six-letter word and two-part name or phrase consisting of a three-letter and a four-letter component. As asterisk denotes the word is capitalized. Since there are thirteen letters in all and only ten positions indicated, we can deduce that there is a three-letter overlap

Here\u27s to U

Presented below are the definitions of thirty two words, each of which contains three or more appearances of the letter U . All of these have been inserted in their proper place in each answer, with blanks representing members of the remaining twenty five letters of the alphabet. As you peruse (sorry!) the list in your search for solutions, be forewarned -- this exercise is not for the U N A D V E N T U R O U S

Palindromic Triads: Not Quite Agamemnon

Logologists recognize Agamemnon, the leader of the Greeks in the Trojan War, as the only common dictionary entry that is made up of three consecutive palindromic triads. In the challenge that follows, you are asked to find twenty-seven more words that begin and end with a palindromic triad

Word Ladders

A word ladder is a link between two given words in which each rung is obtained from its predecessor by altering exactly one letter in it