Thoughts of a Crime Show Junkie: Inadmissible Evidence
Recent Library Articles
Recently in the SAS Community Library: SAS' @RhondaWilliams reveals how SAS Law Enforcement Intelligence helps law enforcement agencies expedite detailed data entry using the Evidence Creation feature.
Please help me with error: Error: The connection could not be established to a SAS Workspace Server named 'Local' running on port on host 'localhost'. Please verify the following: - The correct hostname and port number were specified. - If a firewall is present, it is correctly configured to allow this access. - An object spawner has been started on the server. - The SETINIT on the server is not expired. Please contact your SAS Administrator if the problem persists. Server response: Server execution failed
... View more
I am currently analyzing the impact of an intervention on medication numbers using difference-in-difference analysis, but I have encountered several challenges. Following the SAS support instructions, I conducted the difference-in-difference analysis. However, I noticed a discrepancy between my results and SAS's example (Usage Note 61830: Estimating the difference in differences of means). In the example, the value of 'Mean Estimate' in 'Contrast Estimate Results' is identical to the 'Estimate' in 'Least Squares Means Estimate'. However, in my case, these values were different. I suspect this could be due to my use of the negative binomial distribution with a log link, resulting in exponential values. Consequently, I am unsure whether to rely on the 'Mean Estimate' in 'Contrast Estimate Results' or the 'Estimate' in 'Least Squares Means Estimate', and how to interpret the results." Contrast Estimate Results Label Mean Estimate Mean Confidence Limits L'Beta Estimate Standard Error diff in diff 1.51 1.49 0.41 0.0051 a*b Least Squares Means a b Estimate Standard Error z value Pr > |z| 1 1 0.77 0.00434 178.19 <.0001 1 0 0.03 0.00508 6.5 <.0001 0 1 0.72 0.00408 177.71 <.0001 0 0 0.40 0.00426 93.11 <.0001 Least Squares Means Estimate Effect Label Estimation Standard Error z value Pr > |z| time*hospitalize diff in diff 0.41 0.00509 81.01 <.0001
... View more
Hi, I think it would be beneficial to have Generation Data group like dataset in SAS similar to the format used in Mainframe. Generation Data Groups (GDGs) are group of datasets related to each other by a common name. The common name is referred as GDG base and each dataset associated with the base is called a GDG version. You can set the limit of the related files(generations). We can easily keep track of all generation of data sets. Any particular generation can be referred easily. We use lot of datasets which regenerates daily , monthly , yearly etc.. Consider I need to create daily transaction data for the month of May. If Generation Data Group is available, I would define the base like "Tran_May2024". Then I would just create dataset daily in the below way. Data Tran_May2024(+1); -- This will create the next available version. set work_tran_table; run; If need to point current or earlier version i would use the dataset below. Tran_May2024(0) - Latest Version Tran_May2024(-1) - Previous Version Tran_May2024(-2) - 2 versions back If I need the whole month data , i just refer the base Data work_tran_may; set Tran_May2024; --This would all the version available in the base run; you can have options like below LIMIT – To limit the maximum number of generations. NOEMPTY – Uncatalog only the oldest generation in GDG when the limit is reached. EMPTY – Uncatalog all the generations when a limit is reached. SCRATCH -Physically delete the dataset(generation) which is uncataloged. NOSCRATCH – Don’t Physically delete the dataset(generation) which is uncataloged. This would help a lot when we create lot of datasets which are created in a repeatable fashion. Thank Ravi
... View more