funnelplot               package:rmeta               R Documentation

_F_u_n_n_e_l _p_l_o_t _f_o_r _p_u_b_l_i_c_a_t_i_o_n _b_i_a_s

_D_e_s_c_r_i_p_t_i_o_n:

     Plots the treatment difference for trials against the size of the
     trial (or other specified variable).  Asymmetry in the plot often
     indicates publication bias.  Generic, with methods for
     meta-analysis objects.

_U_s_a_g_e:

     funnelplot(x,...)
     funnelplot.default(x, se, size=1/se, summ=NULL,
             xlab="Effect", ylab="Size", colors=meta.colors(),
             conf.level=0.95, plot.conf=FALSE,
             zero=NULL, mirror=FALSE, ...)

_A_r_g_u_m_e_n_t_s:

       x: Treatment difference

      se: Standard error of 'x'

    size: Variable for the vertical axis

    summ: summary treatment difference

    xlab: x-axis label 

    ylab: y-axis label

  colors: list of colors for components of the plot

conf.level: For confidence interval plotting 

plot.conf: Plot confidence intervals instead of just points?

    zero: location of a null hypothesis line

  mirror: Add points reflected around 'summ'?

     ...: further arguments to be passed from or to methods.

_D_e_t_a_i_l_s:

     With the default value of 'size' the plot should appear as a
     upwards-pointing funnel shape.  Publication bias often causes one
     side of the funnel to be trimmed near the base.  The 'mirror' plot
     creates a symmetric funnel by reflecting the plot around the
     'summ' value.  In the presence of publication bias the added
     points will separate from the real studies.

_V_a_l_u_e:

     Used for its side-effect.

_A_u_t_h_o_r(_s):

     Thomas Lumley

_S_e_e _A_l_s_o:

     'meta.DSL', 'meta.MH', 'meta.summaries', 'metaplot'

_E_x_a_m_p_l_e_s:

     data(catheter)
     a <- meta.MH(n.trt, n.ctrl, col.trt, col.ctrl, data=catheter,
                  names=Name, subset=c(13,6,5,3,7,12,4,11,1,8,10,2))
     funnelplot(a$logOR, a$selogOR)
     funnelplot(a$logOR, a$selogOR,
                plot.conf=TRUE, summ=a$logMH, mirror=TRUE)
     funnelplot(a, plot.conf=TRUE)

