Converting SAS datasets to SPSS

-
If you want to view SAS dataset in SPSS you can use GET SAS command of SPSS.

Here is the syntax;
get sas data='C:\data\class.sas7bdat'.

For conversion of SAS to SPSS we need to see if any formats assigned to variables in the dataset or not.
If there are no formats then we just follow following steps to convert SAS dataset to SPSS.

**STEP1: Creating .xpt file of a SAS dataset using Proc COPY.**

libname SAS 'c:\sas\data\';
libname SPSS xport 'c:\sas\data\class.xpt';

proc copy in=sas out=spss;
select class;
run;


**STEP2: Use SPSS command to convert the transport format SAS file to SPSS;**


You should use following commands to convert transport format file to SPSS data.


get sas data='c:\sas\data\class.xpt'.
execute.

*******************************************************************************************;
If there are formats then we need to convert the formats catalog to a SAS data set before converting the SAS dataset into a .XPT file. This has to be done inside SAS to use the SAS formats as the value labels for SPSS data.

**STEP1: Creating .xpt file of a SAS dataset using Proc COPY.**


libname formats 'c:\sas\catalogs';

proc format library=formats cntlout=fmts;
run;


***Transport file of SAS formats;**


libname fmt2spss xport 'c:\sas\fmts.xpt';


proc copy in=work out=fmt2spss;
select fmts;
run;

***Transport file of SAS dataset.**


libname SAS 'c:\sas\data';
libname SPSS xport 'c:\sas\data\class.xpt';


proc copy in=sas out=spss;
select class;
run;


**STEP3: Use SPSS command to convert the transport format SAS file and Formats to SPSS;**


*Use following SPSS command to convert transport format file to SPSS data;


get sas data='c:\sas\data\class.xpt' /formats='c:\sas\fmts.xpt'.
execute .

('DiggThis’)

Popular posts from this blog

SAS Interview Questions and Answers: CDISC, SDTM and ADAM etc

-
1) What do you know about CDISC and its standards? CDISC stands for Clinical Data Interchange Standards Consortium and it is developed keeping in mind to bring great deal of efficiency in the entire drug development process. CDISC brings efficiency to the entire drug development process by improving the data quality and speed-up the whole drug development process and to do that CDISC developed a series of standards, which include Operation data Model (ODM), Study data Tabulation Model (SDTM) and the Analysis Data Model ADaM ). 2) Why people these days are more talking about CDSIC and what advantages it brings to the Pharmaceutical Industry? A) Generally speaking, Only about 30% of programming time is used to generate statistical results with SAS®, and the rest of programming time is used to familiarize data structure, check data accuracy, and tabulate/list raw data and statistical results into certain formats. This non-statistical programming time will be significantly reduced...
Read more

Comparing Two Methods for Removing Formats and Informats in SAS: DATA Step vs. PROC DATASETS

-
Comparing Two Approaches to Removing Formats and Informats in SAS Comparing Two Approaches to Removing Formats and Informats in SAS When working with SAS datasets, there are times when you need to remove formats and informats that have been previously assigned to variables. Two primary approaches can be used for this task: Using the DATA Step Using the PROC DATASETS Procedure This article compares and contrasts these two approaches to help you determine which method is most appropriate for your needs. Approach 1: Using the DATA Step The DATA step is a versatile and commonly used method for removing formats and informats. By assigning variables to a null format or informat, you can effectively remove these attributes from your dataset. Example: data mydata_clean; set mydata; format _all_; informat _all_; run; In this example, the mydata dataset is processed in the DATA step, and...
Read more

Studyday calculation ( --DY Variable in SDTM)

-
USE OF THE “STUDY DAY” VARIABLES The permissible Study Day variables (--DY, --STDY, and --ENDY) describe the relative day of the observation starting with the reference date as Day 1. They are determined by comparing the date portion of the respective date/time variables (--DTC, --STDTC, and --ENDTC) to the date portion of the Subject Reference Start Date (RFSTDTC from the Demographics domain). The Subject Reference Start Date (RFSTDTC) is designated as Study Day 1. The Study Day value is incremented by 1 for each date following RFSTDTC. Dates prior to RFSTDTC are decremented by 1, with the date preceding RFSTDTC designated as Study Day -1 (there is no Study Day 0). This algorithm for determining Study Day is consistent with how people typically describe sequential days relative to a fixed reference point, but creates problems if used for mathematical calculations because it does not allow for a Day 0. As such, Study Day is not suited for use in subsequent numerical computations...
Read more