Apply label information to metric object of jstable using label data

LabeljsMetric(obj.metric, ref)

Arguments

obj.metric

metric of lmer.display, coxme.display

ref

Label data made by mk.lev function

Value

metric of lmer.display, coxme.display with label information

Details

DETAILS

Examples

library(coxme)
#> Loading required package: bdsmatrix
#> #> Attaching package: ‘bdsmatrix’
#> The following object is masked from ‘package:base’: #> #> backsolve
fit <- coxme(Surv(time, status) ~ sex + ph.ecog + ph.karno + (1 | inst) + (1 | sex), lung) fit.table <- coxme.display(fit)
#> Warning: Using formula(x) is deprecated when x is a character vector of length > 1. #> Consider formula(paste(x, collapse = " ")) instead.
#> Warning: Using formula(x) is deprecated when x is a character vector of length > 1. #> Consider formula(paste(x, collapse = " ")) instead.
#> Warning: Using formula(x) is deprecated when x is a character vector of length > 1. #> Consider formula(paste(x, collapse = " ")) instead.
lung.label <- mk.lev(lung) LabeljsTable(fit.table$table, ref = lung.label)
#> crude HR(95%CI) crude P value adj. HR(95%CI) adj. P value #> sex "0.59 (0.42,0.82)" "0.002" "0.56 (0.4,0.79)" "< 0.001" #> ph.ecog "1.66 (1.32,2.09)" "< 0.001" "1.96 (1.38,2.8)" "< 0.001" #> ph.karno "0.98 (0.97,1)" "0.005" "1.01 (0.99,1.03)" "0.241"
LabeljsRanef(fit.table$ranef, ref = lung.label)
#> [,1] [,2] [,3] [,4] #> Random effect NA NA NA NA #> inst(Intercept) 0.02 NA NA NA #> sex(Intercept) 0.00 NA NA NA
LabeljsMetric(fit.table$metric, ref = lung.label)
#> [,1] [,2] [,3] [,4] #> <NA> NA NA NA NA #> No. of group(inst) 18 NA NA NA #> No. of group(sex) 2 NA NA NA #> No. of observations 225 NA NA NA #> No. of events 162 NA NA NA