BHHR2009p92: Fictional Data Set, with Binary Outcomes

In SAMURAI: Sensitivity Analysis of a Meta-analysis with Unpublished but Registered Analytical Investigations

Description

A fictional meta-analytic data set with 6 published studies and 2 unpublished studies. The binary outcome event is not desired.

Usage

data(BHHR2009p92)

Format

A data frame with 8 observations on the following 8 variables.

number	integer	Study numeric id (optional)
study	character	Name of study or principal investigator
year	integer	Year (optional)
outlook	factor	Denotes whether a study is unpublished, and if so, what outlook it has.
ctrl.n	integer	The sample size of the control arm.
expt.n	integer	The sample size of the experimental arm.
ctrl.events	integer	The number of (undesired) events within the control arm.
expt.events	integer	The number of (undesired) events within the experimental arm.

Details

The outlook of a study can be one of the following: published, very positive, positive, negative, very negative, current effect, no effect, very positive CL, positive CL, negative CL, or very negative CL.

Since the outcome event is undesired, when using the function forestsens(), specify the option higher.is.better=FALSE. Since this is the default setting for forestsens(), this does not need to be specified explicitly.

Source

Borenstein, Hedges, Higgins, and Rothstein. Introduction to Meta-analysis. Wiley, 2009, page 92.

Examples

library(SAMURAI)
data(BHHR2009p92)

forestsens(table=BHHR2009p92, binary=TRUE, higher.is.better=FALSE)

# To assign all unpublished studies to each of ten outlooks, one at a time, 
# and then return a table of summary effects, their 95% confidence interval, 
# and tau-squared.
summtab <- forestsens(table=BHHR2009p92, binary=TRUE, higher.is.better=FALSE, all.outlooks=TRUE)
summtab

SAMURAI documentation built on May 1, 2019, 11:31 p.m.