package to create descriptive tables
- Overview
- News
- Package installation
- Costumizing the table
- Visual exploration
- Exporting the table
- Stratified tables
- Odds Ratios and Hazard Ratios
- Web-based User Interface
- Citation
compareGroups is an R package available on CRAN which performs
descriptive tables displaying means, standard deviation, quantiles or
frequencies of several variables. Also, p-value to test equality between
groups is computed using the appropiate test.
With a very simple code, nice, compact and ready-to-publish descriptives
table are displayed on R console. They can also be exported to different
formats, such as Word, Excel, PDF or inserted in a R-Sweave or
R-markdown document.
You will find an extensive manual describing all compareGropus
capabilities with real examples in the
vignette.
Also, compareGroups package has been published in Journal of Statistical Software [Subirana et al, 2014 http://www.jstatsoft.org/v57/i12/.].
Version 4.9
-
new argument
nmax.methodto compute the N shown in the header. By default N is computed as the number of rows with at least one valid value in the described variables, but also N can be computed as the total number of rows in the data set or in each group regardless the available data in the described variables. -
new argument
starsto show significance levels asterisks beside p-values. -
new argument
p.trend.methodto choose between Spearman, Kendall or “Cuzick’s trend test for non-normal numerical variables.
Version 4.8
- new argument added “lab.ref” to change label for reference category.
Version 4.7
- WUI: new functionality to convert to factors integer variables. Useful to plot numeric variables with few values as bar plots.
Version 4.6
-
new function
padjustCompareGroupsto adjust p-values for multiple testing. -
new arguments
header.backgroundandheader.colorto change header colors when exporting to PDF.
Version 4.5
- new argument ‘lab.missing’ to specify label for missing category.
Version 4.4
-
new argument ‘compute.prop’ to compute proportions instead of percentages for categorical row-variables.
-
new argument ‘all.last’ added to place descriptives of the whole sample after descriptives by groups.
Version 4.3
-
export2wordsupports stratified tables -
Risk Ratios are now computed.
Version 4.2
-
flextablepackage dependency -
export2mdsupports tables and stratified tables to export to word in nicer format using flextable.
Version 4.1
-
Compute confidence intervals of means, medians, proporcions or incidences
-
Proportions can be computed by rows as well as by columns, or by combinations of rows and columns (i.e. to sum up 100%).
-
New argument “position” to place tables justified to the left, centered or to the right using Rmarkdown.
-
When exporting tables to Excel,
export2xlsno longer usesxlsxpackage and useswrite_xlsxfunction from writexl pacakge, instead. -
The web-based user interface ,
cGroupsWUI(), has been improved and updated.
Version 4.0
-
New argument
var.equalto consider unequal variances when performing ANOVA tests. -
Date variables are supported.
-
New
strataTablefunction: to create stratified tables without having to use cbind. -
package vignette improved.
-
New
descrTablefunction that builds a descriptive table in one step. -
New options added in
export2md, to export tables in nicer format. -
New options added in
compareGroupsto control permutated chisquared test.
Install the compareGroups package from CRAN and then load it by
typing:
install.packages("compareGroups")
or from github to get the latest version
library(devtools)
devtools::install_github(repo = "isubirana/compareGroups")
In the following table, some variables from the REGICOR (“Registre
Gironí del Cor”) project (www.regicor.cat)
data set available in the package are analysed. We illustrate the syntax
of compareGroups functions to display tables containing
descriptives or possible tests to compare groups.
Following, to describe all the variables of the data set just type:
library(compareGroups) # load compareGroups package
data(regicor) # load example data
descrTable(regicor)
--------Summary descriptives table ---------
_____________________________________________________________________________
[ALL] N
N=2294
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Individual id 1215817624 (1339538686) 2294
Recruitment year: 2294
1995 431 (18.8%)
2000 786 (34.3%)
2005 1077 (46.9%)
Age 54.7 (11.0) 2294
Sex: 2294
Male 1101 (48.0%)
Female 1193 (52.0%)
Smoking status: 2233
Never smoker 1201 (53.8%)
Current or former < 1y 593 (26.6%)
Former >= 1y 439 (19.7%)
Systolic blood pressure 131 (20.3) 2280
Diastolic blood pressure 79.7 (10.5) 2280
History of hypertension: 2286
Yes 723 (31.6%)
No 1563 (68.4%)
Hypertension treatment: 2251
No 1823 (81.0%)
Yes 428 (19.0%)
Total cholesterol 219 (45.2) 2193
HDL cholesterol 52.7 (14.7) 2225
Triglycerides 116 (73.9) 2231
LDL cholesterol 143 (39.7) 2126
History of hyperchol.: 2273
Yes 709 (31.2%)
No 1564 (68.8%)
Cholesterol treatment: 2239
No 2011 (89.8%)
Yes 228 (10.2%)
Height (cm) 163 (9.22) 2259
Weight (Kg) 73.4 (13.7) 2259
Body mass index 27.6 (4.56) 2259
Physical activity (Kcal/week) 399 (388) 2206
Physical component 49.6 (9.01) 2054
Mental component 48.0 (11.0) 2054
Cardiovascular event: 2163
No 2071 (95.7%)
Yes 92 (4.25%)
Days to cardiovascular event or end of follow-up 1755 (1081) 2163
Overall death: 2148
No 1975 (91.9%)
Yes 173 (8.05%)
Days to overall death or end of follow-up 1721 (1051) 2148
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Example
In the following table, variables are described by year of recruitment.
Some variables such as tryglicerides (triglyc), physical activity
(phyact), days to cardiovascular event (tocv) or days to death
(todeath) have been treated as non-normal distributed, and medians and
quantiles within square brackets instead of means and standard
deviations within round brackets are displayed. Also, individuals older
than 55 years old are selected. Appropiate tests to compare means,
medians or proportions are performed. For those binary variables of type
“yes/no”, you may desire to show only the proportion of “yes” category
without showing “yes” but only the variable name or label. For example,
for “Cholesterol treatment” you may want to see simply “Cholesterol
treatment” instead of “Cholesterol treatment: yes”. This is possible by
hide.no argument. Finally, patient id (id) has been removed using
- from the formula environment.
Note the simplicity of the syntax. Also, note the use of formula to
select the variables, and the use of subset to filter some individuals
as usual in many other R funcions.
tab <- descrTable(year ~ . - id, regicor, hide.no="no", method=c(triglyc=2, tocv=2, todeath=2),
subset=age>55)
tab
--------Summary descriptives table by 'year'---------
__________________________________________________________________________________________________________
1995 2000 2005 p.overall
N=203 N=365 N=540
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Age 65.0 (5.41) 64.7 (5.48) 64.3 (5.57) 0.235
Sex: 0.613
Male 94 (46.3%) 181 (49.6%) 251 (46.5%)
Female 109 (53.7%) 184 (50.4%) 289 (53.5%)
Smoking status: <0.001
Never smoker 127 (64.1%) 220 (63.2%) 326 (61.6%)
Current or former < 1y 29 (14.6%) 84 (24.1%) 71 (13.4%)
Former >= 1y 42 (21.2%) 44 (12.6%) 132 (25.0%)
Systolic blood pressure 142 (18.3) 144 (20.0) 137 (20.0) <0.001
Diastolic blood pressure 79.5 (9.88) 83.5 (9.93) 81.2 (10.6) <0.001
History of hypertension 80 (39.4%) 151 (41.4%) 274 (51.0%) 0.002
Hypertension treatment 57 (28.1%) 101 (27.7%) 198 (38.1%) 0.002
Total cholesterol 229 (41.8) 228 (44.4) 217 (44.3) <0.001
HDL cholesterol 52.4 (14.5) 52.2 (15.3) 53.5 (14.2) 0.403
Triglycerides 99.0 [77.0;137] 107 [82.0;136] 104 [77.0;142] 0.491
LDL cholesterol 154 (37.5) 153 (38.3) 139 (39.6) <0.001
History of hyperchol. 52 (25.6%) 150 (42.3%) 219 (40.7%) <0.001
Cholesterol treatment 22 (10.8%) 55 (15.4%) 111 (21.3%) 0.002
Height (cm) 162 (8.72) 160 (8.98) 161 (8.54) 0.002
Weight (Kg) 73.1 (11.8) 75.2 (12.9) 74.1 (12.4) 0.157
Body mass index 28.0 (4.40) 29.5 (4.21) 28.4 (4.39) <0.001
Physical activity (Kcal/week) 491 (380) 429 (317) 373 (370) <0.001
Physical component 46.9 (8.95) 45.7 (10.8) 47.6 (9.70) 0.031
Mental component 49.2 (11.6) 49.8 (11.0) 47.6 (10.9) 0.016
Cardiovascular event 6 (3.23%) 21 (6.10%) 28 (5.44%) 0.356
Days to cardiovascular event or end of follow-up 1710 [804;2769] 1577 [640;2564] 1752 [824;2739] 0.137
Overall death 13 (7.03%) 61 (17.9%) 46 (8.91%) <0.001
Days to overall death or end of follow-up 1620 [808;2631] 1483 [732;2323] 1751 [782;2640] 0.106
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Also, number of decimals and much more options can be changed to costumize the table as desired (see the package manual)
With compareGroups it is also possible to visualize the
distribution of analysed variables. This can be done by the plot
function applied on the table:
plot(tab["sex"]) # barplot
plot(tab["age"]) # histogram and normality plot
 |
 |
Once the table is created, it can be printed on the R console in a nice and compact format, or it can be exported to different formats, such as PDF, Excel, Word or LaTex code.
export2pdf(tab, file = "example.pdf")
export2xls(tab, file = "example.xlsx")
export2word(tab, file = "example.docx")
export2latex(tab, file = "example.tex")
This is how the table looks like in PDF:
Also, by using export2md function a descriptive table can be inserted
in a Rmarkdown chunk to be compiled in HTML, PDF or Word report. Here
there is an example of a Rmarkdown compiled to HTML.
export2md(tab, strip = TRUE, first = TRUE,
header.background = "blue", header.color = "white",
caption = "Description of variables by recruitment year",
size=10)
| 1995 | 2000 | 2005 | p.overall | |
|---|---|---|---|---|
| N=203 | N=365 | N=540 | ||
| Age | 65.0 (5.41) | 64.7 (5.48) | 64.3 (5.57) | 0.235 |
| Sex: | 0.613 | |||
| Male | 94 (46.3%) | 181 (49.6%) | 251 (46.5%) | |
| Female | 109 (53.7%) | 184 (50.4%) | 289 (53.5%) | |
| Smoking status: | <0.001 | |||
| Never smoker | 127 (64.1%) | 220 (63.2%) | 326 (61.6%) | |
| Current or former < 1y | 29 (14.6%) | 84 (24.1%) | 71 (13.4%) | |
| Former >= 1y | 42 (21.2%) | 44 (12.6%) | 132 (25.0%) | |
| Systolic blood pressure | 142 (18.3) | 144 (20.0) | 137 (20.0) | <0.001 |
| Diastolic blood pressure | 79.5 (9.88) | 83.5 (9.93) | 81.2 (10.6) | <0.001 |
| History of hypertension | 80 (39.4%) | 151 (41.4%) | 274 (51.0%) | 0.002 |
| Hypertension treatment | 57 (28.1%) | 101 (27.7%) | 198 (38.1%) | 0.002 |
| Total cholesterol | 229 (41.8) | 228 (44.4) | 217 (44.3) | <0.001 |
| HDL cholesterol | 52.4 (14.5) | 52.2 (15.3) | 53.5 (14.2) | 0.403 |
| Triglycerides | 99.0 \[77.0;137\] | 107 \[82.0;136\] | 104 \[77.0;142\] | 0.491 |
| LDL cholesterol | 154 (37.5) | 153 (38.3) | 139 (39.6) | <0.001 |
| History of hyperchol. | 52 (25.6%) | 150 (42.3%) | 219 (40.7%) | <0.001 |
| Cholesterol treatment | 22 (10.8%) | 55 (15.4%) | 111 (21.3%) | 0.002 |
| Height (cm) | 162 (8.72) | 160 (8.98) | 161 (8.54) | 0.002 |
| Weight (Kg) | 73.1 (11.8) | 75.2 (12.9) | 74.1 (12.4) | 0.157 |
| Body mass index | 28.0 (4.40) | 29.5 (4.21) | 28.4 (4.39) | <0.001 |
| Physical activity (Kcal/week) | 491 (380) | 429 (317) | 373 (370) | <0.001 |
| Physical component | 46.9 (8.95) | 45.7 (10.8) | 47.6 (9.70) | 0.031 |
| Mental component | 49.2 (11.6) | 49.8 (11.0) | 47.6 (10.9) | 0.016 |
| Cardiovascular event | 6 (3.23%) | 21 (6.10%) | 28 (5.44%) | 0.356 |
| Days to cardiovascular event or end of follow-up | 1710 \[804;2769\] | 1577 \[640;2564\] | 1752 \[824;2739\] | 0.137 |
| Overall death | 13 (7.03%) | 61 (17.9%) | 46 (8.91%) | <0.001 |
| Days to overall death or end of follow-up | 1620 \[808;2631\] | 1483 \[732;2323\] | 1751 \[782;2640\] | 0.106 |
After creating a table you may want to repeat the descriptives within
stratas. For example, you may want to compare the groups for men and for
women. This is very easy using the strataTable function:
# stratify by sex
tabestr <- strataTable(tab, strata="sex")
# remove sex variable from the table
tabestr[-2]
--------Summary descriptives table ---------
______________________________________________________________________________________________________________________________________________________________________
Male Female
__________________________________________________________ _________________________________________________________
1995 2000 2005 p.overall 1995 2000 2005 p.overall
N=94 N=181 N=251 N=109 N=184 N=289
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
Age 65.4 (5.36) 64.7 (5.39) 64.6 (5.62) 0.453 64.7 (5.47) 64.6 (5.58) 64.1 (5.53) 0.403
Smoking status: <0.001 0.007
Never smoker 23 (25.6%) 50 (28.9%) 70 (28.6%) 104 (96.3%) 170 (97.1%) 256 (90.1%)
Current or former < 1y 25 (27.8%) 80 (46.2%) 57 (23.3%) 4 (3.70%) 4 (2.29%) 14 (4.93%)
Former >= 1y 42 (46.7%) 43 (24.9%) 118 (48.2%) 0 (0.00%) 1 (0.57%) 14 (4.93%)
Systolic blood pressure 141 (18.0) 145 (18.8) 139 (19.3) 0.003 143 (18.6) 143 (21.1) 136 (20.4) <0.001
Diastolic blood pressure 79.8 (8.79) 84.8 (9.50) 82.5 (10.8) <0.001 79.3 (10.8) 82.2 (10.2) 80.0 (10.2) 0.028
History of hypertension 34 (36.2%) 67 (37.0%) 126 (50.6%) 0.006 46 (42.2%) 84 (45.7%) 148 (51.4%) 0.202
Hypertension treatment 25 (26.6%) 39 (21.5%) 96 (39.8%) <0.001 32 (29.4%) 62 (33.7%) 102 (36.6%) 0.398
Total cholesterol 221 (42.3) 222 (44.3) 207 (37.9) <0.001 236 (40.3) 234 (43.8) 225 (47.8) 0.035
HDL cholesterol 47.6 (14.3) 46.9 (11.9) 49.1 (12.7) 0.225 56.8 (13.4) 57.6 (16.5) 57.4 (14.4) 0.913
Triglycerides 110 [79.5;139] 112 [87.0;137] 109 [77.0;142] 0.670 95.5 [75.0;127] 104 [77.0;134] 102 [77.0;142] 0.577
LDL cholesterol 151 (38.8) 152 (39.8) 134 (34.2) <0.001 157 (36.4) 154 (36.9) 144 (43.2) 0.006
History of hyperchol. 24 (25.5%) 72 (40.4%) 90 (36.0%) 0.050 28 (25.7%) 78 (44.1%) 129 (44.8%) 0.002
Cholesterol treatment 12 (12.8%) 30 (16.9%) 44 (18.1%) 0.498 10 (9.17%) 25 (14.0%) 67 (24.2%) 0.001
Height (cm) 168 (6.78) 166 (6.36) 167 (6.92) 0.040 156 (6.27) 153 (6.27) 156 (6.36) <0.001
Weight (Kg) 76.6 (12.6) 81.1 (11.8) 78.8 (10.2) 0.005 70.1 (10.4) 69.2 (11.1) 69.9 (12.6) 0.773
Body mass index 27.1 (3.97) 29.4 (3.59) 28.2 (3.25) <0.001 28.8 (4.62) 29.6 (4.76) 28.6 (5.19) 0.141
Physical activity (Kcal/week) 499 (462) 399 (342) 492 (449) 0.054 483 (299) 458 (289) 269 (240) <0.001
Physical component 48.3 (7.03) 48.0 (10.2) 49.0 (9.03) 0.558 45.6 (10.3) 43.5 (11.0) 46.4 (10.1) 0.024
Mental component 52.6 (10.3) 52.5 (9.49) 50.1 (9.94) 0.033 46.1 (11.9) 47.2 (11.8) 45.3 (11.2) 0.263
Cardiovascular event 3 (3.33%) 14 (8.19%) 13 (5.44%) 0.257 3 (3.12%) 7 (4.05%) 15 (5.43%) 0.706
Days to cardiovascular event or end of follow-up 1606 [793;2735] 1608 [537;2492] 1882 [920;2827] 0.105 1739 [834;2768] 1573 [686;2655] 1723 [701;2673] 0.512
Overall death 9 (10.3%) 34 (20.0%) 16 (6.72%) <0.001 4 (4.08%) 27 (15.8%) 30 (10.8%) 0.013
Days to overall death or end of follow-up 1625 [1015;2655] 1442 [769;2247] 1684 [715;2518] 0.290 1501 [725;2515] 1507 [679;2408] 1811 [890;2721] 0.174
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
or when is complied in HTML
export2md(tabestr, strip = TRUE, first = TRUE,
header.background = "blue", header.color = "white", size=8)
|
|
Male |
Female |
||||||
|---|---|---|---|---|---|---|---|---|
| 1995 | 2000 | 2005 | p.overall | 1995 | 2000 | 2005 | p.overall | |
| N=94 | N=181 | N=251 | N=109 | N=184 | N=289 | |||
| Age | 65.4 (5.36) | 64.7 (5.39) | 64.6 (5.62) | 0.453 | 64.7 (5.47) | 64.6 (5.58) | 64.1 (5.53) | 0.403 |
| Sex: | . | . | ||||||
| Male | 94 (100%) | 181 (100%) | 251 (100%) | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | ||
| Female | 0 (0.00%) | 0 (0.00%) | 0 (0.00%) | 109 (100%) | 184 (100%) | 289 (100%) | ||
| Smoking status: | <0.001 | 0.007 | ||||||
| Never smoker | 23 (25.6%) | 50 (28.9%) | 70 (28.6%) | 104 (96.3%) | 170 (97.1%) | 256 (90.1%) | ||
| Current or former < 1y | 25 (27.8%) | 80 (46.2%) | 57 (23.3%) | 4 (3.70%) | 4 (2.29%) | 14 (4.93%) | ||
| Former >= 1y | 42 (46.7%) | 43 (24.9%) | 118 (48.2%) | 0 (0.00%) | 1 (0.57%) | 14 (4.93%) | ||
| Systolic blood pressure | 141 (18.0) | 145 (18.8) | 139 (19.3) | 0.003 | 143 (18.6) | 143 (21.1) | 136 (20.4) | <0.001 |
| Diastolic blood pressure | 79.8 (8.79) | 84.8 (9.50) | 82.5 (10.8) | <0.001 | 79.3 (10.8) | 82.2 (10.2) | 80.0 (10.2) | 0.028 |
| History of hypertension | 34 (36.2%) | 67 (37.0%) | 126 (50.6%) | 0.006 | 46 (42.2%) | 84 (45.7%) | 148 (51.4%) | 0.202 |
| Hypertension treatment | 25 (26.6%) | 39 (21.5%) | 96 (39.8%) | <0.001 | 32 (29.4%) | 62 (33.7%) | 102 (36.6%) | 0.398 |
| Total cholesterol | 221 (42.3) | 222 (44.3) | 207 (37.9) | <0.001 | 236 (40.3) | 234 (43.8) | 225 (47.8) | 0.035 |
| HDL cholesterol | 47.6 (14.3) | 46.9 (11.9) | 49.1 (12.7) | 0.225 | 56.8 (13.4) | 57.6 (16.5) | 57.4 (14.4) | 0.913 |
| Triglycerides | 110 \[79.5;139\] | 112 \[87.0;137\] | 109 \[77.0;142\] | 0.670 | 95.5 \[75.0;127\] | 104 \[77.0;134\] | 102 \[77.0;142\] | 0.577 |
| LDL cholesterol | 151 (38.8) | 152 (39.8) | 134 (34.2) | <0.001 | 157 (36.4) | 154 (36.9) | 144 (43.2) | 0.006 |
| History of hyperchol. | 24 (25.5%) | 72 (40.4%) | 90 (36.0%) | 0.050 | 28 (25.7%) | 78 (44.1%) | 129 (44.8%) | 0.002 |
| Cholesterol treatment | 12 (12.8%) | 30 (16.9%) | 44 (18.1%) | 0.498 | 10 (9.17%) | 25 (14.0%) | 67 (24.2%) | 0.001 |
| Height (cm) | 168 (6.78) | 166 (6.36) | 167 (6.92) | 0.040 | 156 (6.27) | 153 (6.27) | 156 (6.36) | <0.001 |
| Weight (Kg) | 76.6 (12.6) | 81.1 (11.8) | 78.8 (10.2) | 0.005 | 70.1 (10.4) | 69.2 (11.1) | 69.9 (12.6) | 0.773 |
| Body mass index | 27.1 (3.97) | 29.4 (3.59) | 28.2 (3.25) | <0.001 | 28.8 (4.62) | 29.6 (4.76) | 28.6 (5.19) | 0.141 |
| Physical activity (Kcal/week) | 499 (462) | 399 (342) | 492 (449) | 0.054 | 483 (299) | 458 (289) | 269 (240) | <0.001 |
| Physical component | 48.3 (7.03) | 48.0 (10.2) | 49.0 (9.03) | 0.558 | 45.6 (10.3) | 43.5 (11.0) | 46.4 (10.1) | 0.024 |
| Mental component | 52.6 (10.3) | 52.5 (9.49) | 50.1 (9.94) | 0.033 | 46.1 (11.9) | 47.2 (11.8) | 45.3 (11.2) | 0.263 |
| Cardiovascular event | 3 (3.33%) | 14 (8.19%) | 13 (5.44%) | 0.257 | 3 (3.12%) | 7 (4.05%) | 15 (5.43%) | 0.706 |
| Days to cardiovascular event or end of follow-up | 1606 \[793;2735\] | 1608 \[537;2492\] | 1882 \[920;2827\] | 0.105 | 1739 \[834;2768\] | 1573 \[686;2655\] | 1723 \[701;2673\] | 0.512 |
| Overall death | 9 (10.3%) | 34 (20.0%) | 16 (6.72%) | <0.001 | 4 (4.08%) | 27 (15.8%) | 30 (10.8%) | 0.013 |
| Days to overall death or end of follow-up | 1625 \[1015;2655\] | 1442 \[769;2247\] | 1684 \[715;2518\] | 0.290 | 1501 \[725;2515\] | 1507 \[679;2408\] | 1811 \[890;2721\] | 0.174 |
Using compareGroups package you can compute Odds Ratios for
transversal or case-control studies, or Hazard Ratios for cohort studies
- Example of case-control study: Odds Ratios
data(SNPs)
descrTable(casco ~ .-id, SNPs, show.ratio=TRUE, show.p.overall=FALSE)[1:4]
--------Summary descriptives table by 'casco'---------
_______________________________________________________________
0 1 OR p.ratio
N=47 N=110
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
sex:
Male 21 (44.7%) 54 (49.1%) Ref. Ref.
Female 26 (55.3%) 56 (50.9%) 0.84 [0.42;1.67] 0.619
blood.pre 13.1 (0.88) 12.9 (1.03) 0.78 [0.55;1.11] 0.174
protein 39938 (19770) 44371 (24897) 1.00 [1.00;1.00] 0.280
snp10001:
CC 2 (4.26%) 10 (9.09%) Ref. Ref.
CT 21 (44.7%) 32 (29.1%) 0.33 [0.04;1.43] 0.147
TT 24 (51.1%) 68 (61.8%) 0.60 [0.08;2.55] 0.521
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- Example of cohort study: Hazard Ratios
# create a Surv response:
library(survival)
regicor$tcv <- Surv(regicor$tocv, regicor$cv=="Yes")
# perform descriptive table placing the Surv object as the response (left side of ~):
tab <- descrTable(tcv ~ .-id-cv-tocv, regicor,
method=c(triglyc=2, tocv=2, todeath=2),
hide.no="no", ref.no="no",
show.ratio=TRUE, show.p.overall=FALSE)
# print table on R console
print(tab, header.label=c("p.ratio"="p-value"))
--------Summary descriptives table by 'tcv'---------
__________________________________________________________________________________________________
No event Event HR p-value
N=2071 N=92
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Recruitment year:
1995 388 (18.7%) 10 (10.9%) Ref. Ref.
2000 706 (34.1%) 35 (38.0%) 1.95 [0.96;3.93] 0.063
2005 977 (47.2%) 47 (51.1%) 1.82 [0.92;3.59] 0.087
Age 54.6 (11.1) 57.5 (11.0) 1.02 [1.00;1.04] 0.021
Sex:
Male 996 (48.1%) 46 (50.0%) Ref. Ref.
Female 1075 (51.9%) 46 (50.0%) 0.92 [0.61;1.39] 0.696
Smoking status:
Never smoker 1099 (54.3%) 37 (40.2%) Ref. Ref.
Current or former < 1y 506 (25.0%) 47 (51.1%) 2.67 [1.74;4.11] <0.001
Former >= 1y 419 (20.7%) 8 (8.70%) 0.55 [0.26;1.18] 0.123
Systolic blood pressure 131 (20.3) 138 (21.5) 1.02 [1.01;1.02] 0.001
Diastolic blood pressure 79.5 (10.4) 82.9 (12.3) 1.03 [1.01;1.05] 0.002
History of hypertension 647 (31.3%) 38 (41.3%) 1.52 [1.01;2.31] 0.047
Hypertension treatment 382 (18.7%) 22 (23.9%) 1.37 [0.85;2.22] 0.195
Total cholesterol 218 (44.5) 224 (50.4) 1.00 [1.00;1.01] 0.207
HDL cholesterol 52.8 (14.8) 50.4 (13.3) 0.99 [0.97;1.00] 0.114
Triglycerides 96.0 [71.0;135] 110 [87.5;161] 1.00 [1.00;1.00] 0.190
LDL cholesterol 143 (39.6) 149 (45.6) 1.00 [1.00;1.01] 0.148
History of hyperchol. 639 (31.1%) 25 (27.2%) 0.82 [0.52;1.30] 0.406
Cholesterol treatment 213 (10.5%) 6 (6.52%) 0.61 [0.27;1.39] 0.239
Height (cm) 163 (9.21) 163 (9.34) 1.00 [0.98;1.03] 0.692
Weight (Kg) 73.4 (13.7) 74.9 (12.8) 1.01 [0.99;1.02] 0.294
Body mass index 27.6 (4.56) 28.1 (4.48) 1.02 [0.98;1.07] 0.299
Physical activity (Kcal/week) 405 (397) 338 (238) 1.00 [1.00;1.00] 0.089
Physical component 49.7 (8.95) 47.4 (9.03) 0.98 [0.96;1.00] 0.023
Mental component 48.1 (10.9) 46.3 (12.2) 0.99 [0.97;1.00] 0.122
Overall death 156 (7.98%) 15 (16.9%) 2.35 [1.35;4.09] 0.003
Days to overall death or end of follow-up 1684 [789;2663] 1468 [510;2453] 1.00 [1.00;1.00] 0.298
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For those not familiar to R syntax, a Web User Interface (WUI) has been implemented using Shiny tools, which can be used remotely just accessing the compareGroups project website
Try the WUI compareGroups here
citation("compareGroups")
To cite compareGroups in publications use:
Isaac Subirana, Hector Sanz, Joan Vila (2014). Building Bivariate
Tables: The compareGroups Package for R. Journal of Statistical
Software, 57(12), 1-16. URL https://www.jstatsoft.org/v57/i12/.
A BibTeX entry for LaTeX users is
@Article{,
title = {Building Bivariate Tables: The {compareGroups} Package for {R}},
author = {Isaac Subirana and H\'ector Sanz and Joan Vila},
journal = {Journal of Statistical Software},
year = {2014},
volume = {57},
number = {12},
pages = {1--16},
url = {https://www.jstatsoft.org/v57/i12/},
}
Subirana, Isaac, Héctor Sanz, and Joan Vila. 2014. “Building Bivariate Tables: The compareGroups Package for R.” Journal of Statistical Software 57 (12): 1–16. https://www.jstatsoft.org/v57/i12/.