find_umax {metarep}

Lower bounds on the number of studies with replicated effect

Description

lower bounds on the number of studies with increased and\ or decreased effect.

Usage

find_umax(
  x,
  alternative = "two-sided",
  t = 0.05,
  confidence = 0.95,
  common.effect = FALSE
)

Arguments

x

Object of class 'meta'

alternative

'less', 'greater' or 'two-sided'

t

truncation threshold for truncated-Pearsons' test ('t=0.05' by default). t is ignored if 'common.effect = TRUE'.

confidence

Confidence level used in the computaion of the lower bound(s) u_{max}^L and\or u_{max}^R.

common.effect

Use common.effect = FALSE (default) for replicability-analysis combining with no assumptions (Pearson or truncated-Pearson test).

Value

An object of class list reporting the bounds on the number of studies with a positive or negative effect, as follows:

worst.case

A charachter vector of the names of n-u_{max}+1 studies at which the the r(u_{max})-value is computed.

side

The direction of the replicated signal in the 'worst.case' studies. 'less' if the effect is negative, 'greater' if positive.

u_max

The bound on the number of studies with either a positive or a negative effect.

r-value

The 'u-out-of-n' r(u)--value calculated with u=u_max.

Replicability_Analysis

Report of the replicability lower bounds on the number of studies with negative effect and with positive effect.

Examples

n.i.1 <- c( 20, 208, 24, 190, 58, 36, 51)
a.i <- c( 2,79,0,98,15,34,9) 
n.i.2 <- c( 20, 119, 22, 185, 29, 51, 47)
c.i <- c(9,106,14,98,12,49,9) 
m1 <- metabin( event.e = a.i,n.e = n.i.1,
               event.c = c.i,n.c = n.i.2,
               studlab = paste('Study',1:7), sm = 'OR',
               common = FALSE, random = TRUE )
find_umax(m1 , common.effect = FALSE, alternative = 'two-sided',
          t = 0.05 , confidence = 0.95 )