Hi, and welcome!
Please see the FAQ: What's a reproducible example (`reprex`) and how do I do one? Using a reprex, complete with representative data will attract quicker and more answers. In this case, however, where you're looking for general guidance, a reprex is not needed.
I suspect your question is very narrow for this discussion group, but someone (maybe even me!) might be able to help with more information.
How does your data structure differ from the chicago data frame in its layout?
library(oaxaca)
#>
#> Please cite as:
#> Hlavac, Marek (2018). oaxaca: Blinder-Oaxaca Decomposition in R.
#> R package version 0.1.4. https://CRAN.R-project.org/package=oaxaca
# load data set of Hispanic workers in Chicago
data(chicago)
str(chicago)
#> 'data.frame': 712 obs. of 9 variables:
#> $ age : int 52 46 31 35 19 50 33 43 39 22 ...
#> $ female : int 0 1 1 0 0 1 0 0 1 0 ...
#> $ foreign.born : int 1 1 1 1 0 1 1 1 1 0 ...
#> $ LTHS : int 0 0 0 0 0 1 1 0 0 0 ...
#> $ high.school : int 1 1 1 1 1 0 0 1 1 0 ...
#> $ some.college : int 0 0 0 0 0 0 0 0 0 1 ...
#> $ college : int 0 0 0 0 0 0 0 0 0 0 ...
#> $ advanced.degree: int 0 0 0 0 0 0 0 0 0 0 ...
#> $ ln.real.wage : num 2.14 NA 2.5 2.71 2.08 ...
Created on 2020-03-14 by the reprex package (v0.3.0)
Also, is your data similar to the apiclus1 dataset from data(api) in the survey package? If so, see the extended vignette