To upcase all character variables in a SAS dataset, you can use a DATA step with the UPCASE() function in combination with the VARNUM() and VARNAME() functions to iterate through all variables. Here’s an example:
data upcased_dataset;
set origin…
In the context of clinical trials, accurately capturing key dates related to subject participation is critical for understanding the timeline of the study. The SDTM (Study Data Tabulation Model) Demographics (DM) domain includes several variables that record these key dates, two of the most important being RFXSTDTC and RFSTDTC. Although they may seem similar, these variables have distinct meanings and uses. This article explains the difference between RFXSTDTC and RFSTDTC, with detailed examples to illustrate their appropriate use.
RFSTDTC refers to the date and time when the subject officially started participating in the study. This is usually the date of randomization, the first study-specific procedure, or the date when the subject provided informed consent, depending on the study design.
RFXSTDTC captures the date and time when the subject received their first dose of the study treatment. This date is specifically linked to the intervention being tested in the study and marks the beginning of the subject’s exposure to the treatment.
Let’s consider a clinical trial where subjects are required to give informed consent, undergo randomization, and then receive the study treatment. The timeline for each subject might look like this:
| Subject ID | Informed Consent Date | Randomization Date | First Study Drug Dose Date | RFSTDTC | RFXSTDTC |
|---|---|---|---|---|---|
| 001 | 2024-01-01 | 2024-01-05 | 2024-01-10 | 2024-01-05 | 2024-01-10 |
| 002 | 2024-01-02 | 2024-01-06 | 2024-01-08 | 2024-01-06 | 2024-01-08 |
| 003 | 2024-01-03 | 2024-01-07 | 2024-01-12 | 2024-01-07 | 2024-01-12 |
RFSTDTC = 2024-01-05: This date represents when the subject was randomized, marking the official start of their participation in the study.RFXSTDTC = 2024-01-10: This date indicates when the subject received their first dose of the study drug.RFSTDTC = 2024-01-06: The date of randomization, indicating the start of study participation.RFXSTDTC = 2024-01-08: The date when the subject first received the study drug.RFSTDTC = 2024-01-07: The randomization date, marking the start of the subject’s participation.RFXSTDTC = 2024-01-12: The date when the subject received the first dose of the study drug.
The key difference between RFSTDTC and RFXSTDTC lies in what they represent:
RFSTDTC is focused on the start of the subject’s participation in the study, often marked by randomization or the first study-specific procedure.RFXSTDTC specifically tracks when the subject first receives the study treatment, marking the start of their exposure to the intervention being tested.
Accurately capturing these dates is crucial for the integrity of the study data. The distinction between RFSTDTC and RFXSTDTC helps in:
Understanding the difference between RFSTDTC and RFXSTDTC is essential for correctly managing and analyzing clinical trial data. While both variables are related to key dates in a subject’s journey through the trial, they capture different aspects of participation and treatment. Proper use of these variables ensures that the study’s timeline is accurately documented, contributing to the overall integrity and reliability of the clinical trial data.
If you have any further questions or need additional examples, feel free to ask!
SAS Enterprise Guide (SAS EG) Tips and Techniques
SAS Enterprise Guide (SAS EG) Tips and Techniques
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Developing the DC (Demographics as Collected) SDTM Domain
Developing the DC (Demographics as Collected) SDTM Domain: Tips, Techniques, Challenges, and Best Practices
Introduction
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In data management and processing, efficiently handling directories is crucial. Whether you’re consolidating project files or reorganizing data storage, copying directories from one folder to another can streamline your workflow. In this blog post, we’ll explore a powerful SAS script that automates this task, ensuring you can manage your directories with ease and precision.
The goal of this SAS script is to copy all directories from a source folder to a target folder. This can be particularly useful for tasks such as archiving, backup, or restructuring data storage. Below, we provide a comprehensive breakdown of the SAS code used to achieve this.
%let source=/data/projects/2024/Research/Files ;
%let target=/data/projects/2024/Research/Backup ;
data source ;
infile "dir /b ""&source/"" " pipe truncover;
input fname $256. ;
run;
data target ;
infile "dir /b ""&target/"" " pipe truncover;
input fname $256. ;
run;
proc sql noprint ;
create table newfiles as
select * from source
where not (upcase(fname) in (select upcase(fname) from target ));
quit;
data _null_;
set newfiles ;
cmd = catx(' ','copy',quote(catx('/',"&source",fname)),quote("&target"));
infile cmd pipe filevar=cmd end=eof ;
do while (not eof);
input;
put _infile_;
end;
run;
This SAS script performs several key operations to ensure that directories are copied effectively from the source folder to the target folder:
infile statement with a pipe command that executes the dir /b command to retrieve directory names.newfiles containing directories that are present in the source but not in the target folder.catx function is used to build the copy command, and the infile statement with a pipe executes the command.To use this script, replace the source and target paths with your desired directories. The script will automatically handle the rest, ensuring that all directories in the source that do not already exist in the target are copied over.
%let source=/path/to/source/folder ;
%let target=/path/to/target/folder ;
/* Run the script as shown above */
Efficiently managing directories is essential for data organization and project management. This SAS script provides a robust solution for copying directories from one folder to another, helping you keep your data well-structured and accessible. By incorporating this script into your workflow, you can automate the process of directory management and focus on more critical aspects of your projects.
Feel free to customize the script to fit your specific needs, and happy coding!
Managing directories effectively is crucial for organizing and handling large volumes of files in SAS. In this article, we’ll walk through a custom SAS macro that helps you identify all folders within a specified directory. This macro is particularly useful for managing directory structures in complex projects.
The get_folders macro is designed to list all folders present in a specified directory. It verifies the existence of the directory, retrieves the names of all items within it, and outputs this information in a readable format. Below is the complete SAS code for this macro:
%macro get_folders(dir);
/*
Macro: get_folders
Purpose: Identifies all folders available within a specified directory location.
Source: Custom macro developed for directory management in SAS.
Date: September 2024
*/
/* CHECK FOR EXISTENCE OF DIRECTORY PATH */
%if %sysfunc(fileexist(&dir)) %then %do;
/* ASSIGNS THE FILEREF OF MYDIR TO THE DIRECTORY AND OPENS THE DIRECTORY */
%let filrf=mydir;
%let rc= %sysfunc(filename(filrf,&dir));
%let did= %sysfunc(dopen(&filrf));
/* RETURNS THE NUMBER OF MEMBERS IN THE DIRECTORY */
%let memcnt= %sysfunc(dnum(&did));
%put rc=&rc;
%put did=&did;
%put memcnt=&memcnt;
data Dir_Contents;
length member_name $ 32;
/* LOOPS THROUGH ENTIRE DIRECTORY */
%do i = 1 %to &memcnt;
member_name="%qsysfunc(dread(&did,&i))";
put 'member_name ' member_name;
output;
%end;
run;
TITLE "CONTENTS OF FOLDER &DIR";
proc print data=dir_contents;
run;
/* CLOSES THE DIRECTORY */
%let rc= %sysfunc(dclose(&did));
%end;
%else %do;
%put ERROR: Folder &dir Not Found;
%end;
%mend get_folders;
/* Example usage of the macro */
%get_folders('/example/directory/path');
Here’s a step-by-step breakdown of the macro:
%sysfunc(fileexist) function. If the directory does not exist, an error message is displayed.%sysfunc(filename) and %sysfunc(dopen) functions.%sysfunc(dnum).%qsysfunc(dread), and outputs this information to a dataset.PROC PRINT.%sysfunc(dclose).To use this macro, simply call it with the directory path you want to scan:
%get_folders('/example/directory/path');This will list all folders within the specified directory, making it easier to manage and organize your files.
The get_folders macro is a powerful tool for directory management in SAS. By incorporating this macro into your workflow, you can streamline the process of identifying and organizing folders within your projects. Feel free to modify and adapt the macro to suit your specific needs.
Happy coding!