Is there a default map for SAS that projects states like AK,HI, and PR in a more US-centric manner without the need for code workarounds as seen in this.
Alternatively, is there a simpler way to perform this than in the link provided above? Seems like a lot of code for what would seem to be a relatively common task...
The output I'm looking for would be something similar to this:
Ah I found one...
proc gmap data=mapsgfk.us map=mapsgfk.us ;
id statecode;
choro segment / levels=1 nolegend coutline=gray99 des='' name="blah";
run;
Produces the below image. It's missing PR but I can get by with this for the time being.
Related
When using R markdown for making statistical reports, I have the ability to echo the R code in my output document. I'm learning SAS and I was wondering if it was possible to highlight or echo the SAS code in my final ODS report ? I'm using a dirty hack right know to display the code in my document, which is using "ods text = ", but it seems quite redundant. Plus it doesn't add syntax highlighting.
That feature does not exist in the SAS language right now, but it has been mentioned in several talks by Amy Peters, principal product manager of the SAS programing environments, as a planned feature for a near-future SAS release (with no specific date yet, but hopefully in the next 2 years). It would likely be implemented in a similar fashion to Jupyter Notebooks, in that you write your code and get your output inline.
That said, SAS does support Jupyter Notebooks, which is the best current (third party) solution. Contact your SAS administrator for more information.
I have an idea here, I'm the type of guy who dosent take no for answer and find a way to fiddle and get it done... but i think this is abit far fetch... you can try still I think it will work with mostly evrything but may have a hard time to play with quotes when you have multiple semi colomns....
Check:
I started by creating a dumbass dataset :
data tata;
x=1;
run;
then we do the following:
%let code= select * from tata;
proc sql;
create table report as
&code.;
quit;
proc print data=report;
footnote "&code.";
run;
The rationale:
I think it you put your code in macrovariables and then execute those macro variables you would be able to print show the code after by printing the macrovariable following your text...
See the sample
I have a SAS data set with missing data in multiple columns. I would like replace the missing data with a prediction based on the other data in the data set. Here a link that describes the method but doesn't show me how to do it. How do I replace the missing values with a prediction?
EDIT:
The method I had in mind was just using Proc Reg then apply the coefficents to the missing data to generate the estimate. Does this answer your question?
PROC STDIZE, PROC EXPAND, and PROC MI are all capable of performing different kinds of imputations on your data depending on exactly how you want do determine the 'prediction'.
For simple things like replacing with the mean, PROC STDIZE is the way to go. PROC MI is the most advanced - it performs multiple imputation. PROC EXPAND is appropriate if you have time-series data, as it will try to work out what the correct value is for that point in the time series.
If you have missing data in multiple columns you'll require multiple regressions. This probably isn't a good way to do this, but to answer the question - what you're requesting is called scoring a dataset and you can use PROC SCORE.
An alternative method is in your regression procedure request an OUTPUT data set that contains the predicted values for that regression.
output out=predicted1 p=pred_var_missing;
As a matter of methodology, I recommend #Joe's method instead.
Adding to #Joe 's answer, if you tell us why you want to do this imputation, we can provide better advice. I wrote a blog post called How to Ask a Statistics Question that may help.
However, often, single imputation is a bad method. More particularly, if you are going to do further analysis on this data (with the imputed values) then single imputation will underestimate the variability of the data and give wrong results.
PROC MI is usually a better approach.
I have a time series dataset with serious serial correlation problem, so I adopted Prais-Winsten estimator with iterated estimates to fix that. I did the regressions in Stata with the following command:
prais depvar indepvar indepvar2, vce(robust) rhotype(regress)
My colleague wanted to reproduce my results in SAS, so she used the following:
proc autoreg data=DATA;
model depvar = indepvar indepvar2/nlag=1 iter itprint method=YW;
run;
For the different specifications we ran, some of them roughly match, while others do not. Also I noticed that for each regression specification, Stata has many more iterations than SAS. I wonder if there is something wrong with my (or my colleague's) code.
Update
Inspired by Joe's comment, I modified my SAS code.
/*Iterated Estimation*/
proc autoreg data=DATA;
model depvar = indepvar indepvar2/nlag=1 itprint method=ITYW;
run;
/*Twostep Estimation*/
proc autoreg data=DATA;
model depvar = indepvar indepvar2/nlag=1 itprint method=YW;
run;
I have a few suggestions. Note that I'm not a real statistician and am not familiar with the specific estimators here, so this is just a quick read of the docs.
First off, the most likely issue is that it looks like SAS uses the OLS variance estimation method. That is, in your Stata code, you have vce(robust), which is in contrast to what I read SAS as using, the equivalent of vce(ols). See this page in the docs which explains how SAS does the Y-W method of autoregression, compared to this doc page that explains how Stata does it.
Second, you probably should not specify method=YW. SAS distinguishes between the simple Y-W estimation ("two-step" method) and iterated Y-W estimation. method=ITYW is what you want. You specify iter, so it may well be that you're getting this anyway as SAS tends to be smart about those sorts of things, but it's good to verify.
I would suggest actually turning the iterations off to begin with - have both do the two-step method (Stata option twostep, SAS by removing the iter request and specifying method=YW or no method specification). See how well they match there. Once you can get those to match, then move on to iterated; it's possible SAS has a different cutoff than Stata and may well not iterate past that.
I'd also suggest trying this with only one independent and dependent variable pair first, as it's possible the two programs handle things differently when you add in a second independent variable. Always start simple and then add complexity.
I have a single continuous variable with highly skewed distribution. I have log transformed it for normalization. while creating a histogram of the variable with PROC UNIVARIATE (SAS 9.3), is there a way by which I can plot the transformed variable, but keep the values of original variable on x axis ?
if this topic has been already discussed then, I would really appreciate if someone can provide a link. Thank You.
You could use the SAS Graph Template Language (GTL) to do this. The documentation contains plenty of examples that you should be able to change and modify to your needs. The output from PROC UNIVARIATE is produced by the GTL so you should be able to generate something similar.
Take the output dataset from proc univariate and base the plot off that. You will need to reverse the transformations first.
Documentation for the GTL:
http://support.sas.com/documentation/cdl/en/grstatgraph/65377/HTML/default/viewer.htm#p1sxw5gidyzrygn1ibkzfmc5c93m.htm
I have a large SAS dataset and I would like to make a series of tables and charts using by value processing. I am outputing these to a PDF.
Is there any way to get SAS to alternate between the table and the chart as it goes through the data? Right now, I have to print all of the tables first and then print the charts. If it were just 4 tables/charts, then I would be ok writing
Here is a simple example:
data sample;
input byval $ item $ amount;
datalines;
A X 15
A Y 16
A Z 12
B X 25
B Y 10
B Z 18
;
run;
symbol1 i=j;
proc print data=sample;
by byval;
var item amount;
run;
proc gplot uniform data=sample;
by byval;
plot amount*item;
run;
This prints 2 tables, followed by 2 charts.
I would like the Chart for "A" to come after the table for "A" so that the reader can flip through the pdf and always see the associated charts and tables together.
I could write separate procs for each one, but then the gplot won't have a uniform axis (and it gets messy if I have 100 different groups instead of 2).
I thought about pumping them into greplay but then you can't use titles with "#BYVAL1".
Is there any easy way to do this?
I've never used it, but it may be worth checking out ODS DOCUMENT. This allows you to store the output of all your procedures and then reference specific items from them using PROC DOCUMENT.
Below is a link to the SAS website with useful information about this, in particular the paper by Cynthia Zender for the SAS Global Forum 2009.
http://support.sas.com/rnd/base/ods/odsdocument/index.html
Cynthia also regularly contributes to the SAS Support Communities website (https://communities.sas.com/community/support-communities), so it may be worth asking on there if you are still stuck.
Good luck
I don't know of any way to do what you ask directly. GREPLAY is probably the closest you'll come; the primary problem is that SAS processes the PROCs linearly, first processing the entire PROC PRINT, then the entire PROC GPLOT. GREPLAY would allow you to redisplay the output, but if that doesn't work for your needs due to the #BYVAL issue, I'm not sure there's a better solution. Perhaps you can modify the title afterwards (not sure if GREPLAY allows this)?
You could try using ODS LAYOUT, but I don't think that would be any better. The one way it could be better is if you can work out having two columns on a 'page', one column being the PROC PRINT outputs, one the PROC GPLOT, and then print the columns one page than the other. I don't think this is possible, but it might be worth exploring.
You might also try setting up a macro to do each BYVAL separately, defining the axis in a uniform manner manually (ie, defining it based on your own calculation of the correct axis parameters, as an argument to the macro). That is probably the easiest solution that might still allow #BYVAL to work properly.
You might also try browsing about Richard DeVenezia's site (http://www.devenezia.com/downloads/sas/samples/ ) which has a lot of examples of SAS/GRAPH solutions. He also posts on SAS-L (sasl#listserv.uga.edu) sometimes, not sure if I've seen him on StackOverflow. He's probably the person most likely to be able to answer the question that I know of.