About pink_poodle

pink_poodle · ‎01-24-2025

Have you also installed SASPy, Ram? SASPy is a Python package that provides part of the underlying communication between Jupyter and SAS when using the SAS kernel.

pink_poodle · ‎01-23-2025

To find the standard difference, you can use a formula. For example, there are two buckets “1” and “2” with some stuff. What is standard difference between stuff in bucket “2” vs “1”? To standardize relative to bucket #1, we need to divide by the amount of stuff in this bucket. So, the standard difference is the amount in bucket “2” minus “1” divided by “1”. For example, the standard difference in the amount of 🥔 🥔 (potatoes) between buckets # 2 and # 1 is 0.2, meaning that bucket 2 has 20% more potatoes relative to bucket #1: Std_diff_2_to_1 = (b2 - b1)/b1; We can multiply by 100 to get the percent.

pink_poodle · ‎01-23-2025

Your model is an equation used to predict the response. This equation is calculated here inside the probit step. You can see the resulting parameters of the equation in table ttt, but you do not really have to see them to score new data. The computer will score new data by applying this equation to new data to predict the new response. That, like @PaigeMiller said, it done using PROC plm.

pink_poodle · ‎04-08-2024

Great, thank you! Happy Solar Eclipse!

pink_poodle · ‎04-08-2024

I have following statements in PROC PHREG (please see below), the meaning does not matter. The purpose is so the output shows hazard ratio for, say, ost_q 2 vs. 1 (since '1' is the reference level), but instead the output from hazardratio statement shows ost_q 1 vs. 2. How to modify this code? Many thanks! class ost_q (ref='1')/ PARAM = REF; model hosp*hosp_bin(0) = ost_q; hazardratio ost_q /cl = wald ;

pink_poodle · ‎03-08-2024

This solved the error for me :).

pink_poodle · ‎03-02-2024

Break dataset AIR into 10 chunks (_imputation 1-10, 11-20, 21-30, etc.) and feed them to a macro: /*Define macro named arbitrarily, e.g., "piggie" */ %macro piggie (chunk); %DO I = 1 %TO 10; --- your code here --- --- done on chunk&i --- %END; %mend piggie; /*Call macro piggie*/ %piggie(chunk1) %piggie(chunk2) ... %piggie(chunk10)

pink_poodle · ‎03-02-2024

R is a free software that may show it nicer: https://search.r-project.org/CRAN/refmans/Hmisc/html/rcspline.plot.html If you install R, their forum is this: https://community.rstudio.com/

pink_poodle · ‎03-02-2024

I am assuming you have SAS 9.4. If you want to save the log, right-click in the log window during the SAS session and select "File" -> "Save as" from the drop-down list. You can save the log to any location. It will appear as a text file.

pink_poodle · ‎02-22-2024

DATA demo; LENGTH a b c d ac bc cc dc 8.; RETAIN a ; *same as RETAIN a .; RETAIN b 0; RETAIN c 10; *NOTE: doing nothing to variable d (default); /* Initialization proceeds as follows */ ac = a + 1; *_N_ = 1: a = . (the value you provided initially); *_N_ = 2: a = . (the value retained from previous step); *_N_ = 3: a = 5 (the value retained from previous step); bc = b + 1; *_N_ = 1: b = 0 (the value you provided initially); *_N_ = 2: b = . (the value retained from previous step); *_N_ = 3: b = 5 (the value retained from previous step); cc = c + 1; *_N_ = 1: c = 10 (the value you provided initially); *_N_ = 2: c = . (the value retained from previous step); *_N_ = 3: c = 5 (the value retained from previous step); dc = d + 1; *_N_ = 1: d = . (default behavior: initialized to . beginning every step); *_N_ = 2: d = . (default behavior: initialized to . beginning every step); *_N_ = 3: d = . (default behavior: initialized to . beginning every step); INPUT a b c d; DATALINES; . . . . 5 5 5 5 . . . . ; RUN; PROC PRINT DATA = demo NOOBS; RUN;

pink_poodle · ‎02-22-2024

I get this in the log: NOTE: Variable x is uninitialized. NOTE: Variable z is uninitialized. x= y=0 z=.

pink_poodle · ‎02-21-2024

Can someone please explain nicely and with examples the difference between RETAIN and RETAIN 0? For example, RETAIN var1; vs. RETAIN var1 0; Many thanks!

pink_poodle · ‎02-13-2024

1) Chi-square test of difference (chisq option in proc freq) 2) P value will decrease with greater sample size 3) P value < 0.05 means all groups are not equal in response rate. Right now the T groups stand out a little from the C group.

pink_poodle · ‎02-06-2024

@Ksharp , thank you, this is very helpful! I would like to have "ABB" group for duplicates, could you please advice?: data want; input patient time drug $ group $; datalines; 1 1 A ABB 1 2 B ABB 1 3 B ABB 2 1 B BA 2 2 A BA ; run;

pink_poodle · ‎02-06-2024

@rvikram, it should work, please give it a try :).

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Date Last Visited	‎01-24-2025 02:20 PM

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