{ mu ~ dnorm( 0.0, 1.0E-6 ) sigma.theta ~ dunif( 0.0, 16.0 ) for ( i in 1:k ) { theta[ i ] ~ dnorm( mu, tau.theta ) y[ i ] ~ dnorm( theta[ i ], tau.y[ i ] ) } tau.theta <- 1.0 / ( pow( sigma.theta, 2 ) ) positive.effect <- step( mu ) }