View source: R/SingleTable-methods-exported.R
SingleTable.summary | R Documentation |
singletable
.Summarize model of the single table analysis fitted by SingleTable.modelFit
.
SingleTable.summary( single_table_Obj, alpha = 0.05, verbose = TRUE, digit = 3, control = list() )
single_table_Obj |
The object created by |
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. |
A list with the following components: measure, model, posterior mean, posterior median, equal tail CI, and HDR CI.
## Assume we have a 2x2 table:{{40,56},{49,60}} and set prior parameters as a1=b1=a2=b2=rho=0.5. 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)
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