Table Presentation Guidelines
Compiled by James Beard
Introduction
The tables and figures of are the most important elements of a research article, and should enable the reader to understand the main findings of the study independently of the text.
Research articles will typically include several tables. These will detail (at least):
 the characteristics of the study population
 the main results
 secondary findings
Although the study population will often be described in a single table, multiple tables may be necessary or desirable for the main results and secondary findings.
If a table has been previously published elsewhere you must obtain the consent of the copyright holder to republish it (unless the copyright notice allows noncommercial reuse) and the source must be acknowledged.
Formatting and content of tables
Each table must have a number and an informative title, and be mentioned in, and discussed in, the text. The numbering should be sequential in the order they are referred to in the text, Table 1, Table 2, etcetera.
Keep tables simple, and do not include irrelevant data, especially data that are not referred to in the text. Very large tables will generally not be accepted for publication in their entirety, but can be offered as an addendum to the publication, available on request from the corresponding author. Do not present the same information in both tables and figures.
Tables should be inserted into the manuscript as editable cellbased tables, not as images or constructed with text boxes or tabs. Do not use shading. Each row and column of the table must be a separate element of the table  do not use the Enter key to create new rows or spacing / tabs to create new columns.
Table titles may include an indication of the sample size, for example (N=81). But often it will also be necessary to include a total row at the bottom of tables, and sometimes a total column.
Row and column labels should be clear but concise, whilst avoiding abbreviations if possible, and should include units where appropriate.
Raw numbers and percentages should be in the same table column labelled n (%), not N (%).
Numbers and row labels should be leftjustified in cells. In cells containing a number and a percentage, there should be a space between the number and the (.
Percentages should be presented with the same number of decimal places (normally one) for all cells in a table. That is, (15.6), (10.0), (100.0), not (15.6), (10), (100). Do not include the % sign, as this will have been included in the column heading.
Columns of probabilities should be labelled pvalue, not Pvalue, P or p. They should be displayed to 3 decimal places, so 0.020, not 0.02. Values rounded to zero should be reported as <0.001.
Confidence intervals should be displayed as (lower limit, upper limit), for example (0.72, 1.27). They may be presented in the same column as numbers, in which case, a space should precede the ( or in a separate column immediately to the right of the numbers column. The label for the column should include the significance level, for example, 95% CI.
Odds, risk or hazard ratios should normally be presented to two decimal places. But if all the ratios presented within a single table have large confidence intervals, it is preferable to use one decimal place. For example, 1.2 (0.1, 9.7) is more appropriate than 1.23 (0.13, 9.68).
There is almost never justification for presenting numbers with more than 3 significant digits.
When reporting chisquared tests, it is rarely useful to include the actual value of the chisquared statistic, the probability is enough.
If the chisquared statistic is reported, it is usually best not to use the actual Greek letter chi (χ) in the label (or in a table title), as it may look like the Western European letter X in the fonts used in the production version of the article.
Category labels for a variable should be exhaustive and nonoverlapping. This is easy to get wrong for numerical ranges – for age (years) for example, the categories might be <20, 20–24, 25–29, ≥30, not <20, 20–24, 25–29, >30 (30 omitted) or <20, 20–25, 25–30, >30 (25 in two categories).
Category labels that are numeric ranges should be lower to upper, even when the quantities are negative, so 3 to <2, not <2 to 3.
Consider grouping categories when one or more contain very small numbers. For example, education level may have been collected with categories None, Primary, Secondary, University, but only 5 people out of a sample of 400 had university education  in this case it would usually be sensible to combine the Secondary and University categories for reporting. This is particularly important if statistical tests are reported in the table.
Table footnotes should be indicated with consecutive use of the following symbols: * † ‡ § ¶ ‖ then ** †† ‡‡ etcetera.
Example tables
All the following use invented data. Table 1 is an (rather short) example of a table showing participant characteristics. Note related characteristics grouped together. Table 2 shows an analysis of behaviour of interest by sex and socioeconomic status, with chisquared test probabilities. Note the use of rows, rather than a column (as in Table 1) for the variable labels, to save horizontal space. Table 3 shows the output of a logistic regression analysis investigating the relationship of acceptance into postgraduate studies (the dependent variable) to Graduate Record Exam score, Grade Point Average and the prestige of the student's undergraduate institution (the independent variables). The table shows both the crude, unadjusted, odds ratio (cOR) and the adjusted odds ratio (aOR). Note that the percentages in the Total column are column percentages, whilst those in the other columns are row percentages.
Table 1. Patient characteristics (N=162)

n (%) 

Age (years) 
< 20 
18 (11.1) 
20 – 24 
52 (32.1) 

25 – 29 
41 (25.3) 

≥ 30 
51 (31.5) 

Gestational age (weeks) 
< 10 
46 (28.4) 
≥ 10 
94 (58.0) 

Missing 
22 (13.6) 

Gravidity 
1 
75 (46.2) 
2 
46 (28.4) 

≥ 3 
41 (25.3) 

Marital status 
Single 
32 (19.8) 
Married 
105 (64.8) 

Divorced 
25 (15.4) 

Highest educational level 
None 
31 (19.1) 
Primary 
96 (59.3) 

Secondary or higher 
35 (21.6) 
Table 2. Description of starting high school students' choices, according to sex and socioeconomic status (N=200)

Sex 
Socioeconomic status 


Male n (%) 
Female n (%) 
pvalue 
Low n (%) 
Middle n (%) 
High n (%) 
pvalue 
Total n (%) 

Program Type 








General 
21 (23.1) 
24 (22.0) 
0.974 
16 (34.0) 
20 (21.1) 
9 (15.5) 
0.002 
45 (22.5) 
Academic 
47 (51.7) 
58 (53.2) 

19 (40.4) 
44 (46.3) 
42 (72.4) 

105 (52.5) 
Vocation 
23 (25.3) 
27 (24.8) 

12 (25.5) 
31 (32.6) 
7 (12.1) 

50 (25.0) 
School Type 








Public 
77 (84.6) 
91 (83.5) 
0.828 
45 (95.7) 
76 (80.0) 
47 (81.0) 
0.030* 
168 (84.0) 
Private 
14 (15.4) 
18 (16.5) 

2 (4.3) 
19 (20.0) 
11 (19.0) 

32 (16.0) 
Total 
91 (100.0) 
109 (100.0) 

47 (100.0) 
95 (100.0) 
58 (100.0) 

200 (100.0) 
Source: https://stats.idre.ucla.edu/stat/data/hsbdemo.dta* Fisher’s exact test used
Table 3. Logistic regression exploring relationship between student characteristics and admission to postgraduate study

Total 
Not admitted 
Admitted 
cOR (95% CI) 
pvalue 
aOR (95% CI) 
pvalue 
Graduate record exam score 




<580 
174 (43.5) 
131 (75.3) 
43 (24.7) 
1.00 

1.00 

≥580 
226 (56.5) 
142 (62.8) 
84 (37.2) 
1.80 (1.16, 2.79) 
0.008 
1.31 (0.82, 2.10) 
0.261 
Grade point average 




<3.395 
200 (50.0) 
155 (77.5) 
45 (22.5) 
1.00 

1.00 

≥3.395 
200 (50.0) 
118 (59.0) 
82 (41.0) 
2.39 (1.55, 3.70) 
<0.001 
2.33 (1.46, 3.70) 
<0.001 
Prestige of undergraduate institution 




Lower 
188 (47.0) 
148 (78.7) 
40 (21.3) 
1.00 

1.00 

Higher 
212 (53.0) 
125 (59.0) 
87 (41.0) 
2.58 (1.65, 4.01) 
<0.001 
2.61 (1.65, 4.13) 
<0.001 
Total 
400 (100.0) 
273 (68.3) 
127 (31.8) 




Source: https://stats.idre.ucla.edu/stat/stata/dae/binary.dta
Acknowledgements
Some of the text above was drawn from:
Appendix 23.1: Guidance on how to write a scientific paper in Smith PG, Morrow RH, Ross DA (Ed.). Field Trials of Health Interventions: A Toolbox: 3^{rd} ed. Oxford University Press, Oxford; 2015 https://doi.org/10.1093/med/9780198732860.001.0001
and
South African Medical Journal. Author Guidelines
http://www.samj.org.za/index.php/samj/about/submissions#Tables
Table 2 uses invented data from UCLA Statistical Consulting Group. Multinomial Regression, Stata data analysis examples https://stats.oarc.ucla.edu/stata/dae/multinomiallogisticregression/
Table 3 uses the invented data and example at UCLA Statistical Consulting Group. Logistic Regression, Stata data analysis examples https://stats.oarc.ucla.edu/stata/dae/logisticregression/