The goal of exceldata is to facilitate the use of Excel as a data entry tool for reproducible research. This package provides tools to automate data cleaning and recoding of data by requiring a data dictionary to accompany the Excel data. A macro-enabled template file has been created to facilitate clean data entry including validation rules for live data checking.
To download the Excel Template Click Here and then click the download button 
To view data in the required format without macros Click Here and download
You can install the released version of exceldata from CRAN with:
And the development version from GitHub with:
PDF Documentation: Click Here and then click on Download
Example of importing the data and producing univariate plots to screen for outliers.
library(exceldata)
exampleDataFile <- system.file("extdata", "exampleData.xlsx", package = "exceldata")
import <- importExcelData(exampleDataFile,dictionarySheet = 'DataDictionary',dataSheet = 'DataEntry')
#> No errors in data.
#> File import complete. Details of variables created are in the logfile: exampleData17Nov23.log
# The imported data dictionary
dictionary <- import$dictionary
head(dictionary)
#> # A tibble: 6 × 6
#> VariableName Description Type Minimum Maximum Levels
#> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 ID unique patient identifier character <NA> <NA> <NA>
#> 2 Age Patient's age at diagnosis numeric 40 110 <NA>
#> 3 Gender Patient's gender category <NA> <NA> m=Male,f…
#> 4 T_Stage Tumour Staging category <NA> <NA> T0,T1,T2…
#> 5 DxDate Date of Diagnosis date 2019-01-01 today <NA>
#> 6 ECOG Performance Status integer 0 5 <NA>
# The imported data, with calculated variables
data <- import$data
head(data)
#> # A tibble: 6 × 9
#> ID Age Gender T_Stage DxDate ECOG Date_Death Date_LFU T0_Stg
#> <chr> <dbl> <fct> <fct> <date> <int> <date> <date> <fct>
#> 1 1 77 Female T2 2019-06-05 4 2021-08-06 NA T1up
#> 2 2 58 Female T2 2019-09-26 2 2020-06-06 NA T1up
#> 3 3 66 Female T4 2019-07-19 0 NA 2020-07-20 T1up
#> 4 4 72 Female T4 2019-12-17 4 NA 2021-07-04 T1up
#> 5 5 52 Female T2 2019-06-07 1 2020-12-04 NA T1up
#> 6 6 72 Female T1 2021-02-10 2 2021-10-10 NA T1up
# Simple univariate plots with outliers
plots <- plotVariables(data,dictionary,IDvar = 'ID',showOutliers = T)
# Not Run: Show plots in viewer
# plots