Hazard ratios and p-values are computed taking into account time-to cardiovascular event and censoring.

1. Install compareGroups package from CRAN and then load it by typing:

install.packages("compareGroups")
library(compareGroups)

2. Load the PREDIMED example data available in compareGroups package:

data(predimed)

3. Compute time-to-event variable

by using Surv function from survival package.

predimed$tevent <- with(predimed, Surv(toevent, event == "Yes"))
label(predimed$tevent) <- "CV event"

4. Compute all descriptives and test from selected variables by using compareGroups function.

Note the use of formula argument as usual in R, so “.” indicates all variables in the dataset while “-” sign indicates removing. Put time-to-cardiovascular event computed at previous step on left side of “~” sign. Store the results in an object that can be used afterwards to perform plots or bivariate table itself. By the argument method we set wtn and p14 varible to be reported as median and quartiles instead of mean and standard deviation.

res <- compareGroups(tevent ~ . - toevent - event, data = predimed, method = c(wtn = 2, p14 = 2))

5. Create the bivariate table by calling creaTable function

and passing the previous object computed by compareGroups function (res). Using this function you can customize how categorical variables are displayed (only percertage or absolute frequencies or both) by type argument or whether standard deviation appears inside brackets or separated by plus/minus symbol by sd.type argument. Also note the use of hide.no category which is useful to hide “no” level for those binary variables. If you only want to show “Female” category use hide argument for sex variable indicating which category is going to be hiden. This argument also applies to categorical variables with more than two categories. To show how many individuals have non-missing values in each described variable, set hide.n argument to TRUE. In order to show p-value for each category show.p.overall=FALSE. To specify the number of decimal digits to show use digitsarguments. In this example p14 have no decimals and for hormo only one digit. Finally, do not forget to type show.ratio=TRUE to display Hazard Ratio.

restab <- createTable(res, digits = c(p14 = 0, hormo=1), type = 1, sd.type = 2, hide = c(sex = "Male"), hide.no = "no", show.n = TRUE, show.ratio = TRUE, show.p.overall = FALSE)

6. Export or print the bivariate table.

This can be printed in the R console using the method print, i.e. just typing the name of the object:

restab

--------Summary descriptives table by 'CV event'---------

_________________________________________________________________________________ 
                                No event    Event          HR        p.ratio  N   
                                 N=6072     N=252                                 
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 
Intervention group:                                                          6324 
    Control                       32.0%     38.5%         Ref.        Ref.        
    MedDiet + Nuts                33.4%     27.8%   0.66 [0.48;0.89]  0.008       
    MedDiet + VOO                 34.5%     33.7%   0.70 [0.53;0.94]  0.018       
Sex: Female                       58.4%     40.1%   0.49 [0.38;0.63] <0.001  6324 
Age                             66.9±6.14 69.4±6.65 1.06 [1.04;1.09] <0.001  6324 
Smoking:                                                                     6324 
    Never                         62.2%     45.2%         Ref.        Ref.        
    Current                       13.3%     19.4%   1.96 [1.40;2.74] <0.001       
    Former                        24.5%     35.3%   2.02 [1.53;2.67] <0.001       
Body mass index                 30.0±3.81 29.8±3.92 0.99 [0.96;1.02]  0.455  6324 
Waist circumference             100±10.6  102±10.6  1.02 [1.01;1.03]  0.003  6324 
Waist-to-height ratio           0.63±0.07 0.63±0.07 5.27 [0.83;33.6]  0.079  6324 
Hypertension                      82.8%     83.3%   1.10 [0.79;1.53]  0.578  6324 
Type-2 diabetes                   46.8%     63.9%   1.88 [1.46;2.44] <0.001  6324 
Dyslipidemia                      72.9%     59.9%   0.62 [0.49;0.80] <0.001  6324 
Family history of premature CHD   22.7%     20.2%   0.93 [0.68;1.26]  0.640  6324 
Hormone-replacement therapy       1.8%      0.4%    0.29 [0.04;2.10]  0.223  5661 
MeDiet Adherence score          9 [7;10]  8 [7;10]  0.88 [0.83;0.94] <0.001  6324 
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯

Or if you want to change some bivariate table header, such “p-value” instead of “p.ratio” use header.labels argument:

print(restab, header.labels = c(p.ratio = "p-value"))

--------Summary descriptives table by 'CV event'---------

_________________________________________________________________________________ 
                                No event    Event          HR        p-value  N   
                                 N=6072     N=252                                 
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 
Intervention group:                                                          6324 
    Control                       32.0%     38.5%         Ref.        Ref.        
    MedDiet + Nuts                33.4%     27.8%   0.66 [0.48;0.89]  0.008       
    MedDiet + VOO                 34.5%     33.7%   0.70 [0.53;0.94]  0.018       
Sex: Female                       58.4%     40.1%   0.49 [0.38;0.63] <0.001  6324 
Age                             66.9±6.14 69.4±6.65 1.06 [1.04;1.09] <0.001  6324 
Smoking:                                                                     6324 
    Never                         62.2%     45.2%         Ref.        Ref.        
    Current                       13.3%     19.4%   1.96 [1.40;2.74] <0.001       
    Former                        24.5%     35.3%   2.02 [1.53;2.67] <0.001       
Body mass index                 30.0±3.81 29.8±3.92 0.99 [0.96;1.02]  0.455  6324 
Waist circumference             100±10.6  102±10.6  1.02 [1.01;1.03]  0.003  6324 
Waist-to-height ratio           0.63±0.07 0.63±0.07 5.27 [0.83;33.6]  0.079  6324 
Hypertension                      82.8%     83.3%   1.10 [0.79;1.53]  0.578  6324 
Type-2 diabetes                   46.8%     63.9%   1.88 [1.46;2.44] <0.001  6324 
Dyslipidemia                      72.9%     59.9%   0.62 [0.49;0.80] <0.001  6324 
Family history of premature CHD   22.7%     20.2%   0.93 [0.68;1.26]  0.640  6324 
Hormone-replacement therapy       1.8%      0.4%    0.29 [0.04;2.10]  0.223  5661 
MeDiet Adherence score          9 [7;10]  8 [7;10]  0.88 [0.83;0.94] <0.001  6324 
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯

Or if you want to create a PDF document with the table in a publish-ready format

export2pdf(restab, file = "example3.pdf", header.labels = c(p.ratio = "p-value"))

To create tables in PDF you must have some LaTeX compiler installed on your computer.