About braam

braam · ‎10-20-2019

I have a macro variable, ID_LIST, that has a value of "1 2 3 4 6 8". This macro is generated from a dataset (using PROC SQL SELECT). I would like to parse them into each number, and generate another macro variable that is "contrast id1 1, id2 1, id3 1, id4 1, id6 1, id8 1" so that I can use this to perform wald test when I use PROC SURVEYREG. Thanks in advance. What I have: a macro variable having "1 2 3 4 6 8" What I would like to have: a macro variable having "contrast id1 1, id2 1, id3 1, id4 1, id6 1, id8 1"

braam · ‎10-19-2019

Dear Tom, could you explain the logic behind """ (three times)? Any link/document would be appreciated as well. I have no clue to dig in.

braam · ‎10-19-2019

Thanks. I would like to have 09, but could you please let me know both?

braam · ‎10-19-2019

Thanks. So, do I have to use %sysfunc for every nested function?

braam · ‎10-19-2019

I would like to have hour (hh format) and minute (mm format) parts of the current time into two macro variables. I know how to take date and time (as below), but how can I take hour and minute parts from &time? Example 1) if time has 20:30, then I would like to have 20 for hh and 30 for mm. Example 2) if time has 7:30, then I would like to have 7 for hh and 30 for mm. %let date=%sysfunc(today(), yymmdd6.); %let time=%sysfunc(time(), hhmm); %put &time;

braam · ‎10-18-2019

This is the code that you requested. In this example, having too many values for Origin would make this type of regression really inefficient, which takes more than several hours for my case/data. The below is GLM code where I cannot cluster standard errors. I also absorb Origin, rather than estimating its fixed effects. I actually expected the same coefficients on Cylinders from these two approaches, but they are not, which is strange to me. proc surveyreg data= sashelp.cars; cluster Origin; class Origin Type; model EngineSize= Cylinders Origin Type/ solution; run; proc glm data= sashelp.cars; absorb Origin; class Type; model EngineSize= Cylinders Type/ solution; run; SURVEYREG RESULT Estimated Regression Coefficients Parameter Estimate Standard Error t Value Pr > |t| Intercept -0.2423962 0.24823069 -0.98 0.4318 Cylinders 0.6195316 0.03299998 18.77 0.0028 Origin Asia -0.2473363 0.02963121 -8.35 0.0141 Origin Europe -0.4510775 0.00538821 -83.72 0.0001 Origin USA 0.0000000 0.00000000 . . Type Hybrid -0.1485498 0.10737472 -1.38 0.3007 Type SUV 0.2723754 0.09245885 2.95 0.0985 Type Sedan -0.0206628 0.05296500 -0.39 0.7341 Type Sports 0.1480223 0.17265540 0.86 0.4816 Type Truck 0.5319361 0.11385004 4.67 0.0429 Type Wagon 0.0000000 0.00000000 . . GLM RESULT Parameter Estimate Standard Error t Value Pr > |t| Cylinders 0.6292556337 0.01473441 42.71 <.0001 Type Hybrid -.1535480401 B 0.23825545 -0.64 0.5196 Type SUV 0.2436920500 B 0.08982120 2.71 0.0070 Type Sedan -.0144629620 B 0.07368536 -0.20 0.8445 Type Sports 0.0949267303 B 0.09199753 1.03 0.3028 Type Truck 0.4970593441 B 0.10899489 4.56 <.0001 Type Wagon 0.0000000000 B . . .

braam · ‎10-18-2019

Sorry for the confusion. Yes, I would like to 1) have clustered standard errors and 2) include individual-fixed effects.

braam · ‎10-18-2019

I'm not sure if I understand your suggestion. What I would like to do is to include IDs as fixed effects and get standard errors clustered by IDs at the same time. I know it's possible with PROC SURVEYREG, but when I have many ID values, it's practically impossible. So I'm looking for another procedure.

braam · ‎10-18-2019

Isn't WLS about heteroscedasticity (i.e., variance) while clustering standard errors is about covariance within a unit (having multiple observations)? I think they are two different issues.

braam · ‎10-18-2019

Dear All, I was wondering how I can run a fixed-effect regression with standard errors being clustered. I have a panel data of individuals being observed multiple times. I would like to run the regression with the individual fixed effects and standard errors being clustered by individuals. Since I have more than several thousands of individuals, CLASS statement with PROC SURVEYREG is really inefficient, and SAS says insufficient memory. So I don't think I can use PROC SURVEYREG. Can I achieve this using proc glm or proc model? I searched, but didn't find a clear way to do so. Thanks in advance.

braam · ‎10-17-2019

I would like to add an empty line when a specified condition is met. I have a column, NO, that looks below. Obs. NO 1 1 2 2 3 3 4 4 5 5 6 1 7 2 8 3 9 4 10 5 11 1 12 2 Then I would like to add a blank line that follows the observation whose NO is 5. What I would like to have looks below. Obs. NO 1 1 2 2 3 3 4 4 5 5 6 7 1 8 2 9 3 10 4 11 5 12 13 1 14 2 So, the lines 6 and 12 are blank. Can anybody help me with this?

braam · ‎10-16-2019

This is the last step to report my final data. What I expect from the code with sashelp.cars is: Acura1 Acura2 Acura3.... Acura7 Audi1 .... Audi11..... Asia Asia 3.5 2.0 The first row contains variable names while the second and third rows are the Origin and Enginesize columns of the original dataset.

braam · ‎10-16-2019

Thanks for your willingness to help. I used sashelp.cars to describe what you would like to have. The below code doesn't work because MAKE isn't unique. As provided, Acura appears seven times. When using proc transpose, I would like to generate Acura1-Acura7 variables automatically in the transposed set. Similarly, I'd like to make several Audi variables and BMW ones. option notes; data temp; set sashelp.cars; keep make origin enginesize; if _n_ <= 40; if enginesize= 3 then delete; run; proc print data= temp; run; * Obs Make Origin EngineSize 1 Acura Asia 3.5 2 Acura Asia 2.0 3 Acura Asia 2.4 4 Acura Asia 3.2 5 Acura Asia 3.5 6 Acura Asia 3.5 7 Acura Asia 3.2 8 Audi Europe 1.8 9 Audi Europe 1.8 10 Audi Europe 2.7 11 Audi Europe 4.2 12 Audi Europe 4.2 13 Audi Europe 4.2 14 Audi Europe 4.2 15 Audi Europe 1.8 16 Audi Europe 1.8 17 Audi Europe 3.2 18 Audi Europe 4.2 19 BMW Europe 4.4 20 BMW Europe 2.5 21 BMW Europe 2.5 22 BMW Europe 2.5 23 BMW Europe 2.5 24 BMW Europe 2.5 25 BMW Europe 4.4 26 BMW Europe 4.4 ; proc transpose data= temp out= temp_tr; id make; var _all_; run;

braam · ‎10-16-2019

I would like to run the following code, but the ID variable is not unique. What I would like to achieve is that SAS automatically assigns a number from 1 to N to new variables in the transposed data. Let's say, my ID includes CAR three times. Then I would like to have CAR1, CAR2, CAR3 as variables in the transposed data. Can it be done by SAS automatically? Many thanks. proc transpose data= w_ name= model out= w_2 (drop= _label_); id RowName model; var _all_; run;

braam · ‎10-15-2019

@ghosh Thanks. It's an intuitive solution. I have some follow-up questions. 1. Is there a simple way to revise many character variables without listing them all? (I'm thinking of something like _char_,. char*, but didn't find anything). 2. Or something like char1 (starting character variable in my list) -char10 (ending character variable)? I don't think there is something like this in SQL.... 3. The code that you share with me assigns 10 to length of a variable. Extending this, I'm wondering if it can be the same as the maximum length of the variable. Well, some of my character variables use less than 10 characters while others use more than 10. Thanks again for your help.

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