**StudySAS Blog: Mastering Clinical Data Management with SAS**

Effective data management is crucial for the success of any data-driven project, especially in clinical trials and research. SAS provides a powerful toolkit for managing, cleaning, transforming, and analyzing data. This report presents essential SAS programs that can significantly improve your data management processes. 1. Data Import and Export Managing data often starts with importing datasets from various sources and exporting them for analysis or sharing. SAS offers several procedures to handle different data formats. 1.1. Importing Data from Excel To import data from an Excel file, use the PROC IMPORT procedure. This allows you to easily bring data into SAS from Excel spreadsheets. /* Importing data from an Excel file */ proc import datafile="/path/to/your/file.xlsx" out=mydata dbms=xlsx replace; sheet="Sheet1"; getnames=yes; run; 1.2. Exporting Data to Excel You can also export SAS datasets to Excel using the PROC EXPORT proce...

One of my favorite methods of exporting excel or .csv file is to use the ‘ DEXPORT ’ command-line command. This certainly reduces the amount of typing required to export the SAS dataset. Another interesting point is DEXPORT command works fine in UNIX and PC .   Syntax: dm “ DEXPORT libref.dsn 'filename.xls ' replace ;   "libref" is a library , "dsn" is the name of a SAS data set, and "filename.xls" is the name of the tab delimited text file(excel) being created. If we don’t specify the Libname or it is work then the dataset ‘dsn’ from the WORK directory is exported in a excel format to a specified location. Replace option … replaces the file if it already exists.     Use DIMPORT command-line command to convert/import a tab delimited (excel or .csv etc) into a SAS dataset. Syntax: dm “DIMPORT ‘filename.csv’ exc" replace; DIMPORT command tells SAS to import or convert the tab delimited file (filename.csv) to a SAS dataset named ‘ex...

IN SAS programming, we often require outputting the dataset in different formats like EXCEL and CSV etc and here are the five different ways to export the SAS dataset into .csv file. Example: data new ; infile datalines dsd dlm=' ' missover; input a b c d; datalines; 3 5 1 1 4 1 . . 5 8 3 2 6 0 4 4 ; run ; By putting MISSOVER in the infile statement we are telling SAS to do not look for the data in the next lane if it runs out of the data, instead keep missing values for any remaining variables. DSD and DLM options should be included always in the infile statement, if we include the dlm=’ ‘ in the infile statement then SAS will put one digit for each variable even though we haven’t assigned any length to variable. DSD option will tell SAS to consider a missing value if 2 delimiters are present side by side in any observation. When we ran the above program in SAS, we create a SAS dataset name ‘ NEW’ in the work directory and if we want to create a ...