Applicants must often demonstrate adequate English proficiency when applying to postsecondary institutions by taking an English language proficiency test, such as the TOEFL iBT, IELTS Academic, or Duolingo English Test (DET). Concordance tables aim to provide equivalent scores across multiple assessments, helping admissions officers to make fair decisions regardless of the test that an applicant took. We present our approaches to addressing practical (i.e., data collection and analysis) challenges in the context of building concordance tables between overall scores from the DET and those from the TOEFL iBT and IELTS Academic tests. We summarize a novel method for combining self-reported and official scores to meet recommended minimum sample sizes for concordance studies. We also evaluate sensitivity of estimated concordances to choices about how to (a) weight the observed data to the target population; (b) define outliers; (c) select appropriate pairs of test scores for repeat test takers; and (d) compute equating functions between pairs of scores. We find that estimated concordance functions are largely robust to different combinations of these choices in the regions of the proficiency distribution most relevant to admissions decisions. We discuss implications of our results for both test users and language testers.