# Advanced user in-text tables

#### Laure Cougnaud

#### February 22, 2022

In this vignette we focus on providing more explanation on how the `inTextSummaryTable` package actually works. We would describe some of the functionalities less exposed to the users.

We assume you are already familiar on how to create and export tables, otherwise we advise to first check out the dedicated vignettes for creating and exporting tables. The vignettes are accessible with the commands below.

    vignette("inTextSummaryTable-createTables", "inTextSummaryTable")
    vignette("inTextSummaryTable-exportTables", "inTextSummaryTable")

We will first create example data sets to show how the exporting functionalities work. The data sets used are available in the `clinUtils` package.

    library(inTextSummaryTable)
    library(clinUtils)
    library(pander)
    library(tools) # toTitleCase

    # load example data
    data(dataADaMCDISCP01)

    dataAll <- dataADaMCDISCP01
    labelVars <- attr(dataAll, "labelVars")

    dataAE <-  subset(dataAll$ADAE, SAFFL == "Y" & TRTEMFL == "Y")
    dataAEInterest <- subset(dataAE, AESOC %in% c(
            "INFECTIONS AND INFESTATIONS",
            "GENERAL DISORDERS AND ADMINISTRATION SITE CONDITIONS"
        )
    )

    # ensure that order of elements is the one specified in
    # the corresponding numeric variable
    dataAEInterest$TRTA <- reorder(dataAEInterest$TRTA, dataAEInterest$TRTAN)
    dataAEInterest$AESEV <- factor(dataAEInterest$AESEV, levels = c("MILD", "MODERATE"))

    dataTotalAE <- subset(dataAll$ADSL, TRT01A != "Placebo")
    # should contain columns specified in 'colVar'
    dataTotalAE$TRTA <- dataTotalAE$TRT01A

# 1 Detailed framework of the creation of the in-text table

The `getSummaryStatisticsTable` consists of the following framework:

- computation of the summary statistics table with the `computeSummaryStatisticsTable` function
- export of the table to the required format with the `outputType` parameter

## 1.1 Computation of the summary statistics

The supporting data for the summary statistics table, is accessed via the `computeSummaryStatisticsTable`. This includes the entire set of statistics (as numeric) and combined statistic set.

The output from the `computeSummaryStatisticsTable` is equivalent of the table output by the `getSummaryStatisticsTable` function when the `outputType` is set to ‘data.frame-base’.

    summaryTable <- computeSummaryStatisticsTable(
        data = dataAEInterest,
        rowVar = c("AESOC", "AEDECOD"),
        rowVarTotalInclude = c("AESOC", "AEDECOD"),
        colVar = "TRTA",
        stats = getStats("n (%)"),
        dataTotal = dataTotalAE,
        labelVars = labelVars,
        rowVarLab = c('AESOC' = "TEAE by SOC and Preferred Term\nn (%)")
    )

    pander(head(summaryTable, 3))

Table continues below
AESOC | AEDECOD
--- | ---
GENERAL DISORDERS AND ADMINISTRATION SITE CONDITIONS | APPLICATION SITE DERMATITIS
GENERAL DISORDERS AND ADMINISTRATION SITE CONDITIONS | APPLICATION SITE ERYTHEMA
GENERAL DISORDERS AND ADMINISTRATION SITE CONDITIONS | APPLICATION SITE IRRITATION

Table continues below
TRTA | isTotal | statN | statm | statPercTotalN | statPercN
--- | --- | --- | --- | --- | ---
Xanomeline Low Dose | FALSE | 0 | 0 | 2 | 0
Xanomeline Low Dose | FALSE | 2 | 2 | 2 | 100
Xanomeline Low Dose | FALSE | 1 | 2 | 2 | 50

n (%)
0
2 (100)
1 (50.0)

Please note the presence of the `isTotal` column, which flags the records containing the number of subjects reported in the table header.

    pander(subset(summaryTable, isTotal))

Table continues below
| AESOC | AEDECOD | TRTA | isTotal | statN | statm
--- | --- | --- | --- | --- | --- | ---
13 | NA | NA | Xanomeline Low Dose | TRUE | 2 | 2
26 | NA | NA | Xanomeline High Dose | TRUE | 3 | 3

| statPercTotalN | statPercN | n (%)
--- | --- | --- | ---
13 | 2 | 100 | 2 (100)
26 | 3 | 100 | 3 (100)

## 1.2 Export table to the requested format

The summary table is exported to the format of interest with:

    export(
        summaryTable = summaryTable,
        outputType = "flextable"
    )

Please see the vignette: `inTextSummaryTable-exportTables` for more information on the different export types available.

# 2 Combine summary statistics table

Summary statistics tables can be combined with the `combine` function.

    tableDemoCat <- computeSummaryStatisticsTable(
        data = dataADaMCDISCP01$ADSL,
        var = c("SEX", "AGE"), varInclude0 = TRUE,
        colVar = "TRT01P",
        stats = getStats("n (%)", includeName = FALSE),
        labelVars = labelVars
    )
    tableDemoCont <- computeSummaryStatisticsTable(
        data = dataADaMCDISCP01$ADSL,
        var = c("HEIGHTBL", "WEIGHTBL"),
        colVar = "TRT01P",
        stats = getStats(c("n", "median (range)")),
        labelVars = labelVars
    )
    tableDemo <- combine(tableDemoCat, tableDemoCont)
    export(tableDemo)

# 3 Data pre-processing

The variables used for the row and columns of the summary statistics tables should be present in a long format in the input data for the `getSummaryStatisticsTable` function. s In case the grouping of the rows/columns is more complex and no grouping variable is yet available in the data, the function `combineVariables` offers simpler functionalities to create the input data.

The label for the grouping is extracted from the SAS dataset labels if `labelVars` is specified, or can be customized (`label` parameter).

For example, the adverse events are counted for different population set: screened population, completer population, only events with high severity, or related to the treatment and with high severity.

    # prepare the data: create grouping of interest
    dataAEGroup <- combineVariables(
        data = dataAEInterest,
        newVar = "AEGRP",
        paramsList = list(
            # for all screened patients
            list(var = "TRTA", value = "Xanomeline High Dose"),
            # for moderate severity
            list(var = "AESEV", value = "MODERATE", labelExtra = "Moderate"),
            list(var = "AENDY", label = paste("With adverse events ending date"))
        ),
        # include also counts for all records
        includeAll = TRUE,
        labelAll = "All Adverse events",
        labelVars = labelVars
    )
    labelVars["AEGRP"] <- "Patient groups of interest"

    # create the table
    getSummaryStatisticsTable(
        data = dataAEGroup,
        colVar = "TRTA",
        rowVar = "AEGRP",
        labelVars = labelVars,
        dataTotal = dataTotalAE,
        stats = list(expression(paste0(statN, " (", round(statPercN, 1), ")"))),
        title = "Table: Adverse events: counts for groups of interest",
        footer = "Statistics: n (%)"
    )

# 4 Appendix

## 4.1 Session information

R version 4.1.2 (2021-11-01)

Platform: x86_64-pc-linux-gnu (64-bit)

locale: LC_CTYPE=en_US.UTF-8, LC_NUMERIC=C, LC_TIME=en_US.UTF-8, LC_COLLATE=C, LC_MONETARY=en_US.UTF-8, LC_MESSAGES=en_US.UTF-8, LC_PAPER=en_US.UTF-8, LC_NAME=C, LC_ADDRESS=C, LC_TELEPHONE=C, LC_MEASUREMENT=en_US.UTF-8 and LC_IDENTIFICATION=C

attached base packages: tools, stats, graphics, grDevices, utils, datasets, methods and base

other attached packages: pander(v.0.6.4), clinUtils(v.0.1.1), inTextSummaryTable(v.3.1.1) and knitr(v.1.37)

loaded via a namespace (and not attached): tidyselect(v.1.1.1), xfun(v.0.29), reshape2(v.1.4.4), purrr(v.0.3.4), haven(v.2.4.3), colorspace(v.2.0-3), vctrs(v.0.3.8), generics(v.0.1.2), htmltools(v.0.5.2), viridisLite(v.0.4.0), yaml(v.2.3.5), base64enc(v.0.1-3), utf8(v.1.2.2), rlang(v.1.0.1), jquerylib(v.0.1.4), pillar(v.1.7.0), glue(v.1.6.1), gdtools(v.0.2.4), uuid(v.1.0-3), lifecycle(v.1.0.1), plyr(v.1.8.6), stringr(v.1.4.0), munsell(v.0.5.0), gtable(v.0.3.0), zip(v.2.2.0), htmlwidgets(v.1.5.4), evaluate(v.0.15), forcats(v.0.5.1), fastmap(v.1.1.0), crosstalk(v.1.2.0), fansi(v.1.0.2), Rcpp(v.1.0.8), scales(v.1.1.1), DT(v.0.20), systemfonts(v.1.0.4), ggplot2(v.3.3.5), hms(v.1.1.1), digest(v.0.6.29), stringi(v.1.7.6), dplyr(v.1.0.8), ggrepel(v.0.9.1), cowplot(v.1.1.1), grid(v.4.1.2), cli(v.3.2.0), magrittr(v.2.0.2), tibble(v.3.1.6), crayon(v.1.5.0), pkgconfig(v.2.0.3), ellipsis(v.0.3.2), data.table(v.1.14.2), xml2(v.1.3.3), rmarkdown(v.2.11), officer(v.0.4.1), flextable(v.0.6.10), R6(v.2.5.1) and compiler(v.4.1.2)