Presentation is loading. Please wait.

Presentation is loading. Please wait.

Designing effective tables Kostas Danis. Competency to be gained from this lecture Lay out data effectively in tables.

Similar presentations


Presentation on theme: "Designing effective tables Kostas Danis. Competency to be gained from this lecture Lay out data effectively in tables."— Presentation transcript:

1 Designing effective tables Kostas Danis

2 Competency to be gained from this lecture Lay out data effectively in tables

3 Key areas Essential rules when arranging a table Common tables in field epidemiology

4 Communicating patterns and messages contained in your data Show the patterns inherent in the data Focus attention on these patterns Serve as a basis for narrative or discussion Lead observer to insight, discussion, conclusions

5 Avoid visual puzzles in tables Poorly organized data Series of complicated numbers Important data obscured Unnecessary frames, lines, coloring Decoration Basic table rules

6 Column headings Data Footnotes Title Row headings Typical table layout with components

7 Making sure that a table is understandable without referral to other material Title Person Time Place Content of cells (any measurement found in all columns) Row and column headings Content of the row or column Any modifier applied to all cells of a row or column Unit of measurement Abbreviations, if necessary Eliminate acronyms, unless standard (eg.OR) Avoid excessive use of capitals Basic table rules

8 Using footnotes in a table Clarify points of potential ambiguity Explain all: Abbreviations Symbols Codes Note exclusions Mention data source if applicable Basic table rules

9 Table 2. Cases And Controls Among Customers at UMFS CasesControlsTotal OR (95%CI) Swordfish ( ) Paella ( ) Chicken ( ) Flan caramel ( ) Crema catalan ( ) Lemon tarte Incomplete title Absence of necessary footnotes Excess use of capitals Acronyms

10 REVISED Table 2. Frequency of exposures among 42 cases of gastrointestinal illness and 82 controls by fish consumption, Uncle Mikes Fish & Chips, Berlin, 2005 Exposure Cases * n=42 Controls n=82 Odds Ratio (95CI% ) Swordfish (5.3-33) Paella ( ) Chicken ( ) Flan caramel ( ) Crema catalan ( ) Lemon tarte080Reference * 2 cases were excluded 95% Confidence Interval

11 *ASC Ehrenberg, J R Statis Soc A, 140(3): , 1977 Suggestions for data arrangement in tables* 1.Round data to 2 meaningful figures 2.Summarize rows and columns 3.Compare numbers in columns 4.Arrange key data by magnitude 5.Help the reader with easy table layout 6.Align numbers by decimalures Basic table rules

12 Table with excessive number of meaningful figures FactorCasesRate Rate Ratiopapa None Ref b A B C a. p-value b. Reference exposure category Up to five meaningful figures Rate ratios difficult to compare 1. Round data to 2 meaningful figures Basic table rules

13 Rounding data in a table to 2 meaningful figures Factor Cases (1000s)Rate Rate ratiop None Ref* C >0.100 A <0.050 B <0.001 a. p-value b. Reference exposure category 2 meaningful figures Rate ratios easier to compare 1. Round data to 2 meaningful figures Basic table rules

14 Rounding tips Cut decimals for percentages, eg % Use of thousand dividers, eg 18,526 Round up measures of associations to 2 meaningful figures: 2 decimals between decimal between decimals between round to nearest 10 between ORs symmetrical around 1 on log scale 134 same precision as 13.4 or 1.34 or X

15 Rounding tips: p-values Basic table rules P-value Number of decimalsExample > < < p<0.001

16 YearMF Both Sexes Mean Summary of the columns Summary of the rows 2. Summarize rows and columns Summarizing rows and columns with totals, averages or other statistics Basic table rules

17 Compare numbers in columns Difficult to compare numbers in rows st improvement: Right-justify numbers vertically nd improvement: Sort numbers 3. Compare numbers in columns Basic table rules

18 Organize data by magnitude Exposure Cases (1000s)Rate Rate ratioPaPa A > B < C > None Ref b 4. Arrange key data by magnitude a. p-value b. Reference exposure category Basic table rules

19 Organize data by magnitude Exposure Cases (1000s)Rate Rate ratiopapa B < C < A > None Ref b a. p-value b. Reference exposure category 4. Arrange key data by magnitude Basic table rules

20 Year Both sexesMaleFemale Spaced out table layout: Comparisons difficult for the reader 5. Help the reader with easy table layout Basic table rules

21 Year Both sexesMaleFemale Help the reader with easy table layout Drawing columns and rows close together facilitates comparisons Basic table rules

22 Intervening statistics: Separated numbers are harder to compare Rate per 1000 (SE) YearMaleFemaleAll Help the reader with easy table layout Basic table rules

23 Rate per 1000 (SE) YearMaleFemaleAll (2.3) 78 (2.2) 80 (1.9) (2.5) 66 (2.7) 63 (1.8) (2.1) 54 (2.0) 56 (1.7) (2.0) 45 (2.0) 51 (1.7) Moving and minimizing intervening numbers facilitates readability 5. Help the reader with easy table layout Basic table rules

24 Rate per 1000 a YearMFAll a. Standard errors for all rates less than 5% of rate. Remove intervening numbers entirely if consequence minimal 5. Help the reader with easy table layout Basic table rules

25 Align columns by decimal Difficult to compare numbers in rows Keeping the zeros or not is a question of personal style 6. Align numbers by decimal Basic table rules

26 More suggestions 1.Use one column for each of figures 2.Use only horizontal lines between sections of table 3.Avoid redundant (duplicated) data 4.Use landscape format to display more information, if needed 5.Merge tables that share the same denominator, but do not mix data from different populations, denominators, indicators (medians/proportions) Basic table rules

27 Table 1: Distribution of the Households (n=506) by per capita monthly income, Place X, Monthly income per capita (Euros) Number (%) Up to (53.0) 501 – (25.94) 1001 – (14.82) > (6.31) Place number and % in separate columns Excessive use of formatting lines, vertical divider not needed Text not aligned to the left Proportions not rounded

28 REVISED Table 1: Distribution of the households (n=506) by per capita monthly income, Place X, 2012 Monthly income Per capita (Euros) NumberPercentage Up to , ,001-2, >2,000326

29 Table 2- Baseline characteristics of parents/guardians and their children, vaccination coverage survey, Greece, 2006 Common tables SexNumberPercentage Female1, Male1, Total3, Redundant: Proportion of females will indicate proportion of males X

30 Table 4- Complete vaccination coverage of children by place of residence, vaccination coverage survey, Greece, 2006 Place of residencen (weighted %)95% CI Urban Rural 1676 (65%) 448 (58%) Table 3- Complete vaccination coverage of children by maternal belief, vaccination coverage survey, Greece, 2006 n (weighted %) [95%CI] Positive attitude of mother towards her childs vaccination No 1993 (64.5) [ ] 24 (52.3) [ ] Row heading takes more than one line-too wordy Use one column for each figure Consider landscape format Merge tables with identical structrure Use thousand dividers Cut decimals from percentages Explain 95%CI in a footnote

31 n% *95% CI Place of residence Urban Rural 1, Maternal attitude Positive Negative 1, REVISED Table 3- Complete vaccination coverage of children by selected characteristics, vaccination coverage survey, Greece, 2006 * Weighted % allowing for clustering 95% Confidence Interval

32 Table 2. Clinical characteristics of 102 cases of campylobacteriosis, Ireland, 2002 CharacteristicsValue Total cases102 Median age (years) Range (years) Fever Diarrhoea Joint pain (65.6 %) 102 (100 %) 4 (4.3) Headache Muscle pain Isolation of organism 12 (12.4%) 4(4.4%) Stool samples (5/93%) Text must be alighned to the left The table presents frequency of symmptoms Quantitave variables/other info should not be here Sort rows. Decreasing order

33 REVISED Table 2. Frequency of clinical characteristics of 102 cases of campylobacteriosis, Ireland, 2002 Symptomsn% Diarrhoea Fever6566 Headache1213 Joint pain44 Muscle pain44

34 Arranging common types of tables in epidemiology Line listing Two variable table Complex table Cohort study Case-control study Common tables

35 StateAge 1 SexDays 2 Dose New York02M031 California03M 1 Pennsylvania06M031 Pennsylvania02M041 Colorado04F 1 California07M042 Kansas02F051 Colorado03M051 New York03F051 North Carolina04F051 Missouri11M051 Pennsylvania03F071 California04F142 Pennsylvania02M291 California05M Age in months * MMWR, 48 (27): Days from dose to symptom onset Reported cases of intussusception among recipients of rotavirus vaccine, by state, United States, * a. Line listing Common tables

36 New cases of primary and secondary syphilis by age group and sex, United States, 1989 Age groupCases (100s) (years)MaleFemaleTotal Total b. Two variable table Common tables

37 Complex table Children CharacterExp % (n=205) Not exp % (n=8729)p Gestational age (weeks) at birth < NS Birthweight (kg) NS NS c. Complex table Common tables

38 ate ham did not ham illnot ill x2 table for calculation of measure of effect d. Cohort study

39 Tab. IV Fish consumption and gastro-intestinal illness among customers at Uncle Mikes Fish & Chips, Berlin, 2005 IllTotal Attack rate Relative risk Ate fish425872%9.3 (3.9-22) Did not eat fish 5648%Ref Total % d. Cohort study 2x2 table for caclulations Not for presentation

40 Exposed Exposure % Res. a Yes No RR c (95% CI d ) nAR b n Type 1 Sub Type 1-A( - ) Sub Type 1-B( - ) Sub Type 1-C( - ) Type 2( - ) Type 3( - ) Type 4: a. Res. = Responded c. RR = Risk Ratio b. AR = Attack Rate – cases per ___ d. 95% CI = 95% confidence interval of the RR d. Cohort study Risk of ______ by exposure, among #### residents of Place, time Common tables

41 Exposed ExposurenAR a RR b 95% CI c Type or Level 3 Type or Level 2 Type or Level 1 None or Level 01.0Referent b. RR = Risk Ratio c. 95% CI = 95% confidence interval of the RR a. AR = Attack Rate – cases per ___ Risk of ______ by exposure, among #### residents of Place, time d. Cohort study (reference group) Common tables

42 Exposed Not exposed Cases Controls Odds ratio Case control study a b c d Total 100

43 Exposed % (n) a ExposureCasesControlsOR b 95% CI c Type 1 (n) ( – ) Sub Type 1-A (n) ( – ) Sub Type 1-B (n) ( – ) Sub Type 1-C (n) ( – ) Type 2 (n) ( – ) Type 3 (n) ( – ) c. 95% CI = 95% confidence interval of the OR a. n = subjects respondingb. OR = Odds Ratio Exposures (%) among ### cases and ### controls, Place, Time e. Case control study Common tables

44 Table from a case control study

45 Food Specific Attack Rates, Outbreak of Salmonellosis, Prison X, Dover, Delaware, September 1992

46 REVISED for oral presentation Food specific attack rates, outbreak of Salmonellosis, prison X, Dover, Delaware, September 1992

47 Take home message Design your table around the message that is contained in your data

48 Practical 1 Spot the errors of the following tables

49 2.3. Reported laboratory diagnosis methods for chronic and acute infections Lab. methodanti-HCV + RNA-HCV RNA-HCVData missing Chronic cases (n=10403) 4084 (40.3%) 2659 (25.4%) 2057 (20%) 1603 (15%) Acute cases (n=956) 383 (40.4%) 260 (27.3%) 199 (21.2%) 114 (12.4%) SmiNet database Seroconversion could not be verified for the VHC acute cases. - Place acute and chronic vertically to facilitate comparison - Round up proportions - Add thousand dividers

50 Reported laboratory diagnosis methods for chronic and acute HCV infections, SmiNet database Seroconversion could not be verified for acute hepatitis C cases. Information available among cases Acute casesChronic cases n%n% Anti HCV4, Anti HCV + RNA2, RNA HCV2, Data missing1, Total10, Vertical comparisons - Rounded proportions - Thousand dividers

51 CMOs reporting procedures 19/21 CMOs replied the questionnaire Easy to apply case definitions? Yes (Both chronic and acute) Yes (Only chronic) Yes (Only acute) No Replies (n=19)9 (47.5%)1 (5%)09 (47.5%) Reporting instructions for labs Report after confirmation by imunoblot positive test Report after any antibody positive test Wait for RNA confirmatio n test Other Replies (n=19)12 (63%)2 (10%)1 (5%)4 (21%) - Two tables with identical structure - Incomplete title

52 Hepatitis C reporting procedures described by 19 of the 21 Chief Medical Officers (CMOs) surveyed, Sweden, 2012 ItemAnswersN% Case definition easily applicable For chronic and acute cases947 For chronic cases only15 For acute cases only00 No947 Reporting instruction for laboratory After confirmation (Iblot)1263 After any antibody test210 Wait for RNA15 Other421 Total Merged table - Time, place and person title

53 Sexually transmitted infections (STIs) Main public health concern Prevention of STI transmission is a major PH challenge Number of new STI diagnoses in , and changes in trend in , England New STI diagnoses Year% Change Chlamydia189,356189,314186,1960%-2%135% Gonorrhoea16,14416,83520,9654%25%-13% Syphilis*2,8512,6502,915-7%10%87% Herpes**27,53629,79431,1548%5%81% Warts**77,84575,41576,071-3%1%21% Total***426,735419,773426,867-2%2%49% * Syphilis: primary, secondary & early latent **Anogenital herpes / warts ***Total includes diagnoses stated in the table, plus Non-specific genital infection, Pelvic inflammatory disease & epididymitis and Other new STI diagnoses Source: Two parts in table: Values and changes - Footnote too small / detailed - Heterogeneous content indicator-wise

54 Practical 2 Prepare dummy tables for a: case-control study cross-sectional study

55 Practical 2a Prepare dummy tables for a: case-control study to identify risk factors for Campylobacter infection Exposures: travel food consumption (chicken, lettuce) domestic animals Demographics

56 Practical 2b Prepare dummy tables for a: Sero-prevalence study to identify risk factors for West Nile virus infection Exposures: rural place of residence mosquito protection employment status

57 Exposed % (n) a ExposureCasesControlsOR b 95% CI c Age>median Food (n) ( – ) Chicken (n) ( – ) Lettuce (n) ( – ) Travel abroad (n) ( – ) Domestic animal (n) ( – ) c. 95% CI = 95% confidence interval of the OR a. n = subjects respondingb. OR = Odds Ratio Exposures (%) among ### cases of campylobacter and ### controls, Place, Time

58 Exposed Exposure%P a PR b 95% CI c Population size Urban Rural 1.0Referent Mosquito protection Often Rarely Never1.0Referent b. RR = Prevalence Ratio c. 95% CI = 95% confidence interval of the RR a. P = Prevalence– cases per ___ Prevalence of West Nile virus infection by exposure, among #### residents of Place, time Common tables

59 Group ERS Group KLO Group MGI Group NHO Group NEA Group KLN Day 1-2 Day 3-4 Factory Atada NDPH 13** Factory Seuda i056943§ Factory Desda111 (56)43 (96)35 (97)46 (53)56 (75)567 (42) Factory Rioja1103 Mean age Travel hours H C AB level HIV Primary school e Secondary school

60 BACK-UP SLIDES

61 61 Results Number of cases submitted to USISS Age group Type <11 to 45 to 1415 to 4445 to 6465+Total A(H1N1) A(H3N2) A(unknown) B Total Information hard to follow as table

62 62 Number of cases submitted to USISS, by age and virus, {Place}, {Time} Data presented at as graph

63 ExposedUnexposed ExposureTotalCasesAR%TotalCases AR%RR Confidence intervalP blood glucose monitoring [3.18-]<0.001 diabetes mellitus [1.71-]0.003 insulin injection [ ]0.003 chiropody [1.01-.]0.048 upper floor57814, [0.87-]0.056 ground floor [ ]0.058 urethral catheter [ ]0.350 eye drops [ ]1.000 sex [ ]1.000 dialysis [.-.] Multivariable analysis: only blood glucose monitoring significant Results - Redundant stats - Alignment - Decimals - Neutral title

64 ExposedUnexposed ExposureTotalCasesAR%TotalCases AR% Relative risk Confidence interval Glucose monitoring Diabetes mellitus Insulin injection Chiropody Upper floor Ground floor Urethral catheter Eye drops Sex Dialysis Multivariable analysis: Only blood glucose monitoring significant Risk of hepatitis B according to selected exposures, nursing home, Saxony, Germany, Full title - Rounding off - Alignment - P values deleted


Download ppt "Designing effective tables Kostas Danis. Competency to be gained from this lecture Lay out data effectively in tables."

Similar presentations


Ads by Google