Methods for assesing trends in cumulative meta-analysis ---------------------------------------------------------------

^metatrend^ logor_var se_var logor_var is the variable containing the logarithm of the OR (or any other measure of association) se_var is the variable containing the standard error of the logarithm of OR

Description -----------

^metatrend^ performs tests for estimating the trend over time in a cumulative meta analysis

^metatrend^ performs a cumulative meta-analysis (Lau et al, 1995) using the DerSimonian and Laird random-effects method and afterwards, performs two tests for assesing the "Proteus" phenomenon (i.e. the appearence of an early extreme estimate that is refuted by subsequent research). The first method is the so-called "first vs. subsequent" approach (Ioannidis and Trikalinos, 2005). The second method, consists of performing a GLS regression of the cumulative logOR on the rank of the studies using an AR(1) process to handle the serial correlation. The GLS regression is performed using the ^xtgls^ command.

The method is described in detail in (Bagos and Nikolopoulos, 2007).

It is the user's responsibility to ensure that data are in the appropriate format when ^metatrend^ is been called. In particular, the studies should be sorted according to the publication time, prior to running the command.

Authors ------- Pantelis G. Bagos, University of Athens, GR pbagos@biol.uoa.gr and, Georgios K. Nikolopoulos, Hellenic Centre for Diseases Control, GR nikolopoulos@keelpno.gr

References ----------

1) Lau J, Schmid CH, Chalmers TC. Cumulative meta-analysis of clinical trials builds evidence for exemplary me > dical care. J Clin Epidemiol 1995;48(1): 45-57

2) Ioannidis JP, Trikalinos TA. Early extreme contradictory estimates may appear in published research: the Proteus phenomenon in molecular genetics research and randomized trials. > J Clin Epidemiol 2005;58(6): 543-9.

3) Bagos PG, Nikolopoulos GK. Generalized least squares for assessing trends in cumulative meta-analysis: applications in genetic epidemiology J Clin Epidemiol, 2009, in press

Also see -------- On-line: help for @xtgls@