mmeta (version 3.0.0)

SingleTable.summary: Summarize the object of class singletable.

Description

Summarize model of the single table analysis fitted by SingleTable.modelFit.

Usage

SingleTable.summary(
  single_table_Obj,
  alpha = 0.05,
  verbose = TRUE,
  digit = 3,
  control = list()
)

Value

A list with the following components: measure, model, posterior mean, posterior median, equal tail CI, and HDR CI.

Arguments

single_table_Obj

The object created by SingleTable.create and fitted by SingleTable.modelFit.

alpha

a numeric value specifying the significant level. Default value sets to 0.05.

verbose

a logical value; if TRUE(default), the detailed summary messages will display.

digit

an integer value specifying how many decimal places to keep. Default value sets to 3.

control

a list can be specified to control the fitting process.

Examples

## Assume we have a 2x2 table:{{40,56},{49,60}} and set prior parameters as a1=b1=a2=b2=rho=0.5.
 # \donttest{
 library(mmeta)
 library(ggplot2)
 ## If exact method is used, the codes for sampling method are similar.
 ## Create object \code{single_table_obj_exact}
 single_table_obj_exact <- SingleTable.create(a1=0.5,b1=0.5,
 a2=0.5,b2=0.5,rho=0.5, y1=40, n1=96, y2=49, n2=109,model="Sarmanov",measure="OR")
 ## model fit
 single_table_obj_exact <- SingleTable.modelFit(single_table_obj_exact, method = 'exact')
 ## Summary of the fitting process (default)
 single_table_obj_exact <- SingleTable.summary(single_table_obj_exact, alpha = 0.05)
 ## Structure of SingleTable object
 str(single_table_obj_exact)
 ## If set alpha level to 0.1
 single_table_obj_exact <- SingleTable.summary(single_table_obj_exact, alpha = 0.1)
 ## If set digit to 2
 single_table_obj_exact <- SingleTable.summary(single_table_obj_exact, digit  = 2)
 ## If decided not to print out
 single_table_obj_exact <- SingleTable.summary(single_table_obj_exact, verbose = FALSE)
 # }