This function creates a table that complies with the table 1 required on most of the research papers. The function create descriptive statistics for the entire population and, if a categorical variable is defined for strata, then additional descriptive statistics will be added to the table and a p-value will be calculated. Additionally, if desired, the table may be exported to an excel file, were the table could be edited to addapt to the formatting required by the journal it will be published.
Table1(x=NULL, y=NULL, rn=NULL, data=NULL, miss=3, catmiss=TRUE, formatted=TRUE,
categorize=FALSE, factorVars=NULL, maxcat=10, delzero=TRUE, decimals = 1,
messages = TRUE,excel=0, excel_file=NULL, debug = FALSE)a string vector containing the name of the variables for which descriptive statistics will be calculated.
the name of the categorical variable that defines the stratification that will be used.
a string vector containing the text that will replace variables defined in argument x. If y is not provided, the original variable name will be used.
the name of the dataset to be used.
determines if missingness will be shown in the table for the variables. The possible values are: 0=dont add missing statistics; 1=add missing statistics for contiinuous (numerical) values only; 2=add missing statistics for categorical (factor) values only;3=add missing statistics for both numerical and categorical values;
On categorical variables, adds a new category (Missing) to the available categories. Default is FALSE. For activation change this to TRUE. If TRUE, the "miss" parameter will not be used for category variables
As default, the table output is formatted as text with values that include parenthesis and percentages, e.g. 153 (26.5%). If you are interested that the table return each numeric value as aseparate cell, set this variable to FALSE.
If there are categorical variables that are defined as numeric we can force the function to take them as categorical (factor) by changing this to TRUE. Default is FALSE.
If categorize is set to TRUE, a list of variables to be considered as categoricals may be given. In this case, maxcat will not be used and only the variables in the list will be converted to factors.
If we force categorize to be TRUE, maxcat will be used to define the maximum number of unique values permited for a variable to be considered as categorical. Default is 10.
For dichotomic variables, the default behaviour is to delete the rows with the first value (0,"No","Normal",etc.). If you want that all the values are presented change it to FALSE.
Determinate the number of decimal places of numerical data. Default is 1
This switch will show the iterations of the function through the variables. In case you want to suppress those message set it to FALSE.
indicates if the table will be exported to excel. The default is not to export (excel). For exporting to excel set excel=1.
A string variable defining the name of the excel file. If the directory path is not included in the file name, the file will be saved on the current path directory.
Normally, the Table1 function will show a progress bar when running. Sometimes the command fails because some anomaly in a variable that was not detected by the function. In such case, setting debug to TRUE will print each variable that is processed. In case of error, the last printed variable must be checked. The default to this parameter is FALSE
The Table1 function returns a data frame object containing the descriptive statistics for each of the variables defined on the x parameters (if provided) or all the variables(if x was not provided). If the parameter y is not defined, only the column for the total population will be returned. If y is defined (and providing that it is categorical with less than six categories), additional columns will be added for each of the categories. If the parameter excel is true and a path/file is defined, an excell file will be generated with the data in the table.
The getTable1 function generates a descriptive statistical summary appropriate for publishing in a scientific paper.
# NOT RUN {
### get the table 1 with original variables name
rv <- names(trees)
tab1 <- Table1(x=rv, data=trees)
### get the table 1 with the specified given variables text
rv <- names(swiss)
rn <- rv
rn[6] <- "Infant Mortality"
tab1 <- Table1(x=rv, rn=rn, data=swiss)
### get the table 1 and stratify by one variable
tab1 <- Table1(data=data.frame(HairEyeColor), y="Sex")
# }
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