Category: SASpphire 蓝宝石

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I have met so many wonderful people along my SAS journey, they are precious like Sapphire to me.

Now I am trying to organize the common SAS functions and procedures I have used on a daily basis, summarize the different CDISC domains that I have worked on and some statistical method I have encountered.

SAS SQL Join

SAS day 24:  Proc SQL Join   Review: Last time we went to over SAS Merge, it is a SAS Merge statement used for  1 – 1 mapping or One – Many mapping, What should we do for many to many mapping?

SAS Proc SQL Count

SAS Day 23: SQL Count   Background: In order to present the data to the audience in a nice way, we often generate tables, figures, and listings from the existing datasets.  There are many data processing steps, such as Merge, Transformation. Among them, One of the most commonly used technique is Summarize the Object Count using SQL.

SAS Merge

SAS Day 22: Merge    Background: Sometimes we need to obtain information from different datasets, how do we combine two or more datasets in SAS?  Most cases, we use the “Merge” statements, however,  depends on the data structures, we need to use SQL if it is many to many mapping. P.S. regardless of Merge or SQL, we need to have…

SAS Format

SAS Day 19: Format   Background:  In clinical datasets, we usually use some shortcode to keep the data to be concise, meanwhile, we want to generate detailed table labels from the datasets so the output is reader-friendly. For example, in the dataset, we have “F, M“, and we want to show “Female, Male” in output tables.

SAS Baseline

SAS Day 21: Baseline Value Background: How do we decide if the Weight Loss program/drug is effective or the laser operation improves the vision? Usually, we compare the weights before and after a program or track the vision before and after the eye laser surgery. The Change From Baseline is a critical measurement of efficacy analysis. Therefore, it is very crucial to record the…

SAS Miss function

SAS Day 20: Miss function There are two miss functions in SAS I really like, NMISS and CMISS. Problem: if we want to calculate the duration as aendt(Adverse Event End Date) – aestdt (Adverse Event Start Date). Ideally, we can use adurn=aendt-aestdt +1. However, in reality, we know there are high probabilities with missing AE dates.

SDTM.VS

SDTM day 6: Vital Sign Introduction: the Vital Sign domain captures all the measurements of body’s most basic functions, such as height, weight, blood pressure, heart rate… VS is a critical dataset in Drug Safety Analysis.

SDTM.EX

SDTM Day 5: SDTM.EX   Introduction: Exposure dataset contains the details of subjects’ study treatment information, it is one of the key safety datasets, and it is critical to efficacy analysis. The EX domain is intended for “protocol-specified study treatments” including placebo dosing. The EX dataset would present a complete and accurate of subjects’ exposure in one record per constant dosing to the reviewers.

SDTM.AE

SDTM Day 4 : SDTM.AE Adverse Event is an event that results in unintended harm to the patient by an act of commission or omission rather than by the underlying disease or condition of the patient, thus AE Dataset is very important to Safety analysis for drug testing. It captures Adverse Event dates and various Adverse Event information for each patient. The…

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