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I have met so many wonderful people along my SAS journey, they are precious like Sapphire to me. Thanks to Wan, 0, Renee5, 77, 99, Little Rain family, David, Yue, Vincent, Mounika, Jie Chen, Charlie, Lemeng. P, June, Tony.L, Bonnie.B, Kevin Gu, Shirish. N, XueyingJ, Jillian. P, Steve, Ocean, Jenny, Daniel.H, John W, Henry G, Xu lan, Ju Zhang, Yao Lei, Joe Wang …. :)
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 Day 24: Space Trick Background: My boss has a motto “Devil in the details“. I think all the Space- Related issues are the “Devil” in SAS. Today, we will go over the function and tricks I used to deal with Space. Remove Space: Compress, Compbl, Strip, Trim Concatenate with Remove Space: ||, CAT, CATS, CATX, CATT
Today I will share some Basic Oncology Knowledge I found in my old notebook: RECIST 1.1: Complete Response (CR): Disappearance of all non-nodal target lesion Partial Response (PR) : At least 30% decrease in the sum of diameters of target lesions compared with the baseline sum diameters.
Background Story: Once my friend said her team members cried during a meeting, i thought it was funny then. However, when I started to work in their team, I wanted to cry, too. What was the challenge? It was ISS/ ISE related work!
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 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 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 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 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 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.