Original Article| Volume 114, P125-132, October 2019

Download started.


Who is in this study, anyway? Guidelines for a useful Table 1



      Epidemiologic and clinical research papers often describe the study sample in the first table. If well-executed, this “Table 1” can illuminate potential threats to internal and external validity. However, little guidance exists on best practices for designing a Table 1, especially for complex study designs and analyses. We aimed to summarize and extend the literature related to reporting descriptive statistics.

      Study Design and Setting

      In consultation with existing guidelines, we synthesized and developed reporting recommendations driven by study design and focused on transparency related to potential threats to internal and external validity.


      We describe a basic structure for Table 1 and discuss simple modifications in terms of columns, rows, and cells to enhance a reader's ability to judge both internal and external validity. We further highlight several analytic complexities common in epidemiologic research (missing data, sample weights, clustered data, and interaction) and describe possible variations to Table 1 to maintain and add clarity about study validity in light of these issues. We discuss considerations and tradeoffs in Table 1 related to breadth and comprehensiveness vs. parsimony and reader-friendliness.


      We anticipate that our work will guide authors considering layouts for Table 1, with attention to the reader's perspective.


      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'


      Subscribe to Journal of Clinical Epidemiology
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect


        • Moher D.
        • Hopewell S.
        • Schulz K.F.
        • Montori V.
        • Gotzsche P.C.
        • Devereaux P.J.
        • et al.
        CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials.
        Int J Surg. 2012; 10: 28-55
        • Vandenbroucke J.P.
        • von Elm E.
        • Altman D.G.
        • Gotzsche P.C.
        • Mulrow C.D.
        • Pocock S.J.
        • et al.
        Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration.
        Int J Surg. 2014; 12: 1500-1524
        • Schwartz S.
        • Campbell U.B.
        • Gatto N.M.
        • Gordon K.
        Toward a clarification of the taxonomy of “bias” in epidemiology textbooks.
        Epidemiology. 2015; 26: 216-222
        • Malmivaara A.
        Generalizability of findings from randomized controlled trials is limited in the leading general medical journals.
        J Clin Epidemol. 2019; 107: 36-41
        • von Elm E.
        • Altman D.G.
        • Egger M.
        • Pocock S.J.
        • Gotzsche P.C.
        • Vandenbroucke J.P.
        • et al.
        The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies.
        Int J Surg. 2014; 12: 1495-1499
        • Des Jarlais D.C.
        • Lyles C.
        • Crepaz N.
        • the Trend Group
        Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement.
        Am J Public Health. 2004; 94: 361-366
        • Soltoft Larsen K.
        • Pottegard A.
        • Lindegaard H.M.
        • Hallas J.
        Impact of urate level on cardiovascular risk in allopurinol treated patients. A nested case-control study.
        PLoS One. 2016; 11: e0146172
        • Chong S.Y.
        • Chittleborough C.R.
        • Gregory T.
        • Mittinty M.N.
        • Lynch J.W.
        • Smithers L.G.
        Parenting practices at 24 to 47 Months and IQ at age 8: effect-measure modification by infant temperament.
        PLoS One. 2016; 11: e0152452
        • Knol M.J.
        • Groenwold R.H.H.
        • Grobbee D.E.
        P-values in baseline tables of randomised controlled trials are inappropriate but still common in high impact journals.
        Eur J Prev Cardiol. 2012; 19: 231-232
        • Palesch Y.Y.
        Some common misperceptions about P values.
        Stroke. 2014; 45: e244-e246
        • Goodman S.
        A dirty dozen: twelve p-value misconceptions.
        Semin Hematol. 2008; 45: 135-140
        • Greenland S.
        • Senn S.J.
        • Rothman K.J.
        • Carlin J.B.
        • Poole C.
        • Goodman S.N.
        • et al.
        Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations.
        Eur J Epidemiol. 2016; 31: 337-350
        • de Boer M.R.
        • Waterlander W.E.
        • Kuijper L.D.J.
        • Steenhuis I.H.M.
        • Twisk J.W.R.
        Testing for baseline differences in randomized controlled trials: an unhealthy research behavior that is hard to eradicate.
        Int J Behav Nutr Phys Act. 2015; 12: 4
        • Furler J.
        • Magin P.
        • Pirotta M.
        • van Driel M.
        Participant demographics reported in “Table 1” of randomised controlled trials: a case of “inverse evidence”?.
        Int J Equity Health. 2012; 11: 14
        • Stuart E.A.
        • Bradshaw C.P.
        • Leaf P.J.
        Assessing the generalizability of randomized trial results to target populations.
        Prev Sci. 2015; 16: 475-485
        • Cole S.R.
        • Stuart E.A.
        Generalizing evidence from randomized clinical trials to target populations: the ACTG 320 trial.
        Am J Epidemiol. 2010; 172: 107-115
        • Allison P.D.
        Missing data. vol. 136. Sage, Thousand Oaks, CA2001
        • Daniel R.M.
        • Kenward M.G.
        • Cousens S.N.
        • De Stavola B.L.
        Using causal diagrams to guide analysis in missing data problems.
        Stat Methods Med Res. 2012; 21: 243-256
        • Westreich D.
        Berkson's bias, selection bias, and missing data.
        Epidemiology. 2012; 23: 159-164
        • Perkins N.J.
        • Cole S.R.
        • Harel O.
        • Tchetgen Tchetgen E.J.
        • Sun B.
        • Mitchell E.M.
        • et al.
        Principled approaches to missing data in epidemiologic studies.
        Am J Epidemiol. 2018; 187: 568-575
        • Hardy S.E.
        • Allore H.
        • Studenski S.A.
        Missing data: a special challenge in aging research.
        J Am Geriatr Soc. 2009; 57: 722-729
        • Sterne J.A.
        • White I.R.
        • Carlin J.B.
        • Spratt M.
        • Royston P.
        • Kenward M.G.
        • et al.
        Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.
        BMJ. 2009; 338: b2393
        • National Research Council (US) Panel on Handling Missing Data in Clinical Trials
        The prevention and treatment of missing data in clinical trials.
        National Academies Press, Washington, DC2010 (Available at
        • Ware J.H.
        • Harrington D.
        • Hunter D.J.
        • D’Agostino R.B.
        Missing data.
        N Engl J Med. 2012; 367: 1353-1354
        • Little R.J.
        • D'Agostino R.
        • Cohen M.L.
        • Dickersin K.
        • Emerson S.S.
        • Farrar J.T.
        • et al.
        The prevention and treatment of missing data in clinical trials.
        N Engl J Med. 2012; 367: 1355-1360
        • Duquia R.P.
        • Bastos J.L.
        • Bonamigo R.R.
        • Gonzalez-Chica D.A.
        • Martinez-Mesa J.
        Presenting data in tables and charts.
        An Bras Dermatol. 2014; 89: 280-285
        • Franzblau L.E.
        • Chung K.C.
        Graphs, tables, and figures in scientific publications: the good, the bad, and how not to be the latter.
        J Hand Surg Am. 2012; 37: 591-596
        • Boers M.
        Graphics and statistics for cardiology: designing effective tables for presentation and publication.
        Heart. 2018; 104: 192-200