doc/clinreport-vignette.md

In jfrancoiscollin/ClinReport: Statistical Reporting for Scientific Publications, Epidemiological Studies and Clinical Trials

title: "ClinReport R package" author: "Jean-Francois COLLIN" date: "2019-02-28" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{ClinReport Vignette} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8}

Get started

Start by loading all usual libraries.

library(ClinReport)
library(officer)
library(flextable)
library(dplyr)
library(reshape2)
library(nlme)
library(emmeans)
library(car)

Load your data.

# We will use fake data
data(datafake)
print(head(data))
#>   y_numeric y_logistic y_poisson  baseline   VAR GROUP TIMEPOINT SUBJID
#> 1 -1.397502          0         4 -1.397502 Cat 2     A        D0 Subj 1
#> 2 -1.170587          0         4 -1.170587 Cat 2     A        D0 Subj 1
#> 3 -1.020176          1         4 -1.020176 Cat 1     A        D0 Subj 1
#> 4 -3.953050          1         1 -3.953050 Cat 1     A        D0 Subj 1
#> 5 -1.780908          1         3 -1.780908 Cat 1     A        D0 Subj 1
#> 6 -1.889678          0         3 -1.889678 Cat 1     A        D0 Subj 1

Create a statistical output for a quantitative response and two explicative variables. For example a treatment group and a time variable corresponding to the visits of a clinical trial.

For that we use the report.quanti() function:

tab1=report.quanti(data=data,y="y_numeric",
        x1="GROUP",x2="TIMEPOINT",at.row="TIMEPOINT",
        subjid="SUBJID")

tab1
#>    TIMEPOINT Statistics      A (N=30)      B (N=21)      C (N=17)
#> 1         D0          N            30            20            16
#> 2         D0  Mean (SD)   -1.01(1.22)   -1.11(0.93)   -0.51(1.27)
#> 3         D0     Median         -1.06         -0.98         -0.68
#> 4         D0    [Q1;Q3] [-1.72;-0.12] [-1.66;-0.75] [-1.67; 0.12]
#> 5         D0  [Min;Max]  [-3.95;0.85]  [-2.88;0.28]  [-2.50;2.17]
#> 6         D0    Missing             0             0             1
#> 7                                                                
#> 8         D1          N            30            20            16
#> 9         D1  Mean (SD)    1.55(0.65)    3.84(0.83)    4.70(0.95)
#> 10        D1     Median          1.71          3.97          4.62
#> 11        D1    [Q1;Q3] [ 0.87; 1.88] [ 3.10; 4.48] [ 4.16; 5.08]
#> 12        D1  [Min;Max]  [ 0.45;2.70]  [ 2.35;5.16]  [ 2.56;6.68]
#> 13        D1    Missing             0             0             0
#> 14                                                               
#> 15        D2          N            30            20            16
#> 16        D2  Mean (SD)    1.75(0.88)    4.25(1.34)    5.14(1.22)
#> 17        D2     Median          1.74          3.83          4.84
#> 18        D2    [Q1;Q3] [ 1.07; 2.47] [ 3.19; 5.05] [ 4.43; 5.79]
#> 19        D2  [Min;Max]  [-0.10;3.31]  [ 1.93;7.11]  [ 3.35;7.32]
#> 20        D2    Missing             1             0             1
#> 21                                                               
#> 22        D3          N            30            20            16
#> 23        D3  Mean (SD)    1.94(0.90)    4.05(1.16)    5.38(0.88)
#> 24        D3     Median          2.03          3.83          5.35
#> 25        D3    [Q1;Q3] [ 1.44; 2.56] [ 3.27; 4.56] [ 4.61; 6.10]
#> 26        D3  [Min;Max]  [-0.64;3.64]  [ 1.84;5.83]  [ 3.99;6.84]
#> 27        D3    Missing             2             1             0
#> 28                                                               
#> 29        D4          N            30            20            16
#> 30        D4  Mean (SD)    2.07(0.97)    3.98(1.10)    4.94(0.94)
#> 31        D4     Median          2.19          4.17          4.80
#> 32        D4    [Q1;Q3] [ 1.46; 2.64] [ 3.16; 4.47] [ 4.27; 5.27]
#> 33        D4  [Min;Max]  [-0.19;3.80]  [ 1.87;6.73]  [ 3.05;6.66]
#> 34        D4    Missing             1             0             1
#> 35                                                               
#> 36        D5          N            30            20            16
#> 37        D5  Mean (SD)    2.08(0.93)    4.21(1.03)    5.09(0.76)
#> 38        D5     Median          2.18          4.38          5.37
#> 39        D5    [Q1;Q3] [ 1.68; 2.73] [ 3.57; 4.71] [ 4.51; 5.43]
#> 40        D5  [Min;Max]  [-0.09;3.70]  [ 1.74;6.30]  [ 3.38;5.89]
#> 41        D5    Missing             2             0             0

The at.row argument is used to space the results between each visit and the subjid argument is used to add in the columns header the total number of subjects randomized by treatment group.

Generally we want also the corresponding graphics. So you can use the specific plot function to print the corresponding graphic of your table:

g1=plot(tab1,title="The title that you want to display")
print(g1)

You can modify the plot by using the following arguments of the plot.desc() function:

args(ClinReport:::plot.desc)
#> function (x, ..., title = "", ylim = NULL, xlim, xlab = "", ylab = "", 
#>     legend.label = "Group", add.sd = F, add.ci = F, add.line = T) 
#> NULL

Then we can use the report.doc() function which use the flextable package to format the output into a flextable object, ready to export to Microsoft Word with the officer package.

The table will look like this (we can have a preview in HTML, just to check):

jfrancoiscollin/ClinReport documentation built on Sept. 20, 2020, 7:33 a.m.