------------------------------------------------------------------------------- help for

meta_lr-------------------------------------------------------------------------------Graph of positive and negative likelihood ratios in diagnostic test

meta_lr{theta1} {se_theta1} {theta2} {se_theta2} {stratavariables} [if> exp] [inrange] [,stratifycombineweightingid(strvar)fixeformylabgraphoption]

Description

meta_lrdoes mainly two things: it can do stratified meta-analysis of i > ndividual estimatestheta1andtheta2bystratavariables, save the stratified pooled estima > tes and their confidence intervals in new data set and draw them in one graph; > if stratified variables are not given,meta_lrdrawtheta1andtheta2and their confidence interval by > individual study in one graph, with or without weighting. Combined meta-analysis results > are shown in star.This command is mainly used to draw graph in diagnostic test.The user p > rovides the effect estimate as thetas (e.g., log positive likelihood ratio and log negative likelihood ratio) > . Likewise, the user provides the standard error of thetas. Commands meta and metareg must be installed before using this command.

options for stratified analysis

stratifymust be given when do the stratified analysis. Meanwhile, at l > east onestratavariablemust be given.

fixindicates statified meta-analysis using fixed model. Default is ran > dom effect model.

eformis the same option as in meta. It requests that the output of str > atified meta-analysis is exponentiated. When this option is chosen, optionxscale(log)is sug > gested to use.ylabgives labels on y axis. These labels are the strata variables.graphoptionthe following graph options of STATA 8 can be used in this > command.symbol() msize()mcolor() xscale() xline() xlabel() blpattern() blcolor() ytitle() xtitl> e() scheme()

options for not stratified analysisOption

stratifymust not be given.

id(strvar)is a character variable which is used to label the studies. > A string variable must be given.combineprovide the combined estimates oftheta1andtheta2with their > confidence intervals. In graph, they are shown in star with two vertical lines to show the combined point es > timates.combinecan be chosen together withfixwhich means that fixed meta-analysis model is used, random model is > the default one.weightinggives individual study weights. Iffixis chosen, weights are > reverse of variance oftheta1andtheta2. Iffixis not chosen, weights are 1/(tau^2 + variance).fixdefine that combined estimates are obtained from fixed meta-analysi > s and weighting is reverse of variance. Default is that combined estimates are from random effect model and weights are > 1/(tau^2 + variance).graphoptionthe same as for stratified analysis.Required input variables

theta1the first effect estimate (for example log negative likelihood > ratio)se_theta1the corresponding standard error

theta2the second effect estimate (for example log positive likelihoo > d ratio)se_theta2the corresponding standard errortheta1andtheta2can be the same effect estimates. This means that str > atified meta-analysis will be done only on one effect estimate and the graph only shows for one es > timate. Hence, this command also can be used in meta-analysis of randomised controlled trails which will show t > he similar graph as meta. Howevermeta_lrprovide more options, with or without combine, weighting and mo > re graph options. The disadvantage is that the user needs to type the same theta and its corresponding standa > rd error twice.stratavariableare the stratified variables. They must be discrete or b > inary variables. These variables are re-grouped before drawing the graph. For example, if the user has a variable calle > d test which can be 0, 0.5 or 1. This variable is re-grouped to 1, 2 and 3. This change is made in order to label y ax > is. But the user's data set will not be changed at all.Example.

meta_lr llrpos llrposse llrneg llrnegse test funding, stratify fix ef> orm xscale(log) xline(1).meta_lr llrpos llrposse llrneg llrnegse, id(author) combine weighting.meta_lr logitsens se_sens logitsens se_sens, id(author) combineAuthorAijing Shang Institute of Social and Preventive Medicine, University Berne, Switzerl > and Email: shang@ispm.unibe.ch

Also seeOn-line: help for meta (if installed), metan (if installed), metareg (i > f installed)