What exactly is the difference between Proc Means and Proc Summary? Many sites state that both these are the same, but unless each has something unique will SAS create it?
#cmjohns gives the biggest difference...and from SAS discussion forum
"In earlier versions of SAS (SAS 5 and 6) PROC MEANS and PROC SUMMARY were separate procedures. Over time, by version 8, the code for the 2 procedures was standardized and "melded" together. There are essentially no differences except that MEANS creates output in the LISTING window or other open destinations, while SUMMARY creates an output dataset by default." (use the PRINT option in the Proc Summary statement to generate output)
Check the link Here
My understanding is that the PROC SUMMARY code for producing an output data set is exactly the same as the code for producing an output data set with PROC MEANS. The difference between the two procedures is that PROC MEANS produces a report by default, whereas PROC SUMMARY produces an output data set by default. So if you want a report printed to the listing - use proc means - if you want the info passed to a data set for further use - proc summary may be a better choice.
I have come across situations in SAS 9.1.3 where proc means has had "out of memory" problems yet proc summary will still run the equivalent request just fine. Something to keep in mind if you ever run into this problem.
**Proc Means**
->By Default Print the Output.
->By default gives variable name,
label name(if any), mean, no of non-
missing values, std dev, min and max.
->By default take all the numeric
variables in to analysis.
**Proc Summary**
-> By default does not print the output.
-> By default gives only no of non-missing values.
-> If specifying statistics function then have to specify the variable name with Var statement.
proc means : 1) The print option is set by default which displays output .
2) Omitting the var statement analyses all the numeric variable.
Proc Summary : 1) No print option is set by default,which displays no output.
2) Omitting the variable statement produces a simple count of observation.
Proc Means requires at least one numeric variable while proc FREQ has no such limitations.
Related
SAS has several forms it uses to create output data sets from within a procedure. It is not always clear whether or not a particular procedure can generate a data set and, if it seems to be able to, it's not always clear how.
Off the top of my head, here are some examples of how widely the syntax can differ.
Example 1
proc sort data = sashelp.baseball out = baseball_sorted;
by
league
division
;
run;
Example 2
proc means noprint data = baseball_sorted;
by
league
division
;
var nHits;
output
out = baseball_avg_hits (drop = _TYPE_ _FREQ_)
mean = mean_hits
;
run;
Example 3
ods exclude all;
ods output
statistics = baseball_statistics
equality = baseball_ftest
;
proc ttest data = baseball_sorted;
class league;
var nHits;
run;
ods exclude none;
Example 4
The PROC ANOVA OUTSTAT= option.
It seems almost as if SAS has implemented each of these willy-nilly. Is the SAS syntax dictating how to create a data set directed by some consistent approach I am not seeing or is it truly capricious and arbitrary?
For PROC code, the syntax for outputting data is often specific to that procedure, which often feels willy-nilly. (Your examples 1, 2, 4) I think PROC developers are given a lot of freedom, and remember that many of these PROCS are 30+ years old.
The great thing about the Output Delivery System (ODS, your example 3) is it provides a single syntax for outputting data, regardless of the procedure. So you can use the ODS OUTPUT statement with (almost?) any PROC. The names and structures of the output objects will of course vary between PROCs. So if you are looking for a consistent approach, I would focus on using ODS OUTPUT. ODS was added in V7 (I think).
It would be interesting to try to find an example of an output dataset which could be made by a PROC but could not be made by ODS OUTPUT. I hope there aren't any. If that is the case, you could consider the range of OUTPUT statements/options within PROCs as legacy code.
Agree with Quentin. You have to remember that there are SAS systems out there running code written in the 80s. SAS would have a huge headache if they forced every team to rewrite all the procedures and then forced their customers to change all their code. SAS has been around since the 60s and the organic growth of the syntax is to be expected.
FWIW, having an OUT= statement makes sense on things with no graphical output. I.E. PROC SORT or PROC TRANSPOSE.
The way I see it there are four main ways to specify the output data sets.
In the PROC statement you may be able to specify some type of output statements or options, such as OUT= OUTEST=.
In the main statement of the procedure, ie MODEL/TABLE can have options that allow for output. ie PROC FREQ has an OUT= on the TABLE statement.
An explicit OUTPUT statement within a procedure. These are typically from older procedures. ie PROC MEANS
ODS tables which are relatively newer method, more frequently used these days since the format aligns with what you'd expect to see.
Yes, there are multiple places to check, but fortunately the SAS documentation for procedures is relatively clear with the options and how to use/specify the outputs.
If I've missed anything that seems different post in the comments and I can update this.
PS. Although SAS is definitely bad, trying to navigate different packages/modules in Python to export an XLSX file isn't straight forward either. Some packages support some options others don't. I've given up on asking why these days and just accept it as peculiarities of the different languages at this point.
In R I could just write something like model$deviance and model$df.residual, but I can't seem to find any way of doing this in SAS.
Whereas R functions produce an object that has sub-objects that you can extract into a variable, SAS procedures create tables. If you see a statistic in some table that you want to use in another part of your program, you can use the Output Delivery System (ODS) to write that table to a data set, as follows:
1) Use the ODS TRACE ON statement to discover the name of the table (or look it up in the documentation)
2) Use the ODS OUTPUT statement to write the table to a data set.
For example, if you are interested in the many goodness-of-fit diagnostic statistics (including the statistics for deviance and chi-square residuals), you can discover that the "Criteria for Assessing Goodness of Fit" table has the name ModelFit. Therefore, putting
ODS OUTPUT ModelFit=FitStatistics;
inside your PROC GENMOD call will create a data set called "FitStatistics" that contains the statistics you want.
I try to use the proc transreg procedure in SAS, to transform one of my variables in a dataset (var1). The var1 variable has values >=0.
My code is:
proc transreg data=data1 details;
model boxcox(var1/lambda=-1 to 1 by 0.125 convenient parameter=1)=identity(var2);
output out=BoxCox_Out;
run;
However I get the following error message:
"observation of nonblank TYPE not equal 'Score ' are excluded from the analysis and the output data set.
Could anyone help me?
_TYPE_ can be used for TRANSREG to allow you to take datasets with multiple kinds of rows and only use the SCORE rows (or whichever ones you choose), often outputs from earlier TRANSREG procedures.
However, _TYPE_ is also a common variable added by procedures like PROC MEANS to indicate which class combinations apply to the row. In this case, TRANSREG is getting confused and thinking you want something different.
Drop the _TYPE_ variable in the TRANSREG data source statement, and it should use all rows.
proc transreg data=data1(drop=_type_) details;
This might be a weird question. I have a data set contains data like agree, neutral, disagree...for many questions. There is not so many observations so for some question, one or more options has frequency of 0, say neutral. When I run proc freq, since neutral shows up in that variable, the table does not contain a row for neutral. I end up with tables with different number of rows. I would like to know if there is a option to show these 0 frequency rows. I will also need to run proc gchart for the same data set, and I will run into the same problem for having different number of bars. Please help me on this. Thank you!
This depends on how exactly you are running your PROC FREQ. It has the sparse option, which tells it to create a value for every logical cell on the table when creating an output dataset; normally, while you would have a cell with a missing value (or zero) in a crosstab, if that is output to a dataset (which is vertical, ie each combination of x and y axis value are placed in one row) those rows are left off. Sparse makes sure that doesn't happen; and in a larger (n-dimensional) crosstab, it creates rows for every possible combination of every variable, even ones that don't occur in the data.
However, if you're just doing
proc freq data=mydata;
tables myvar;
run;
That won't help you, as SAS doesn't really have anything to go on to figure out what should be there.
For that, you have to use a class variable procedure. Proc Tabulate is one of such procedures, and is similar to Proc Freq in its syntax (sort of). You need to either use CLASSDATA on the proc statement, or PRINTMISS on the table statement. In the former case, you do not need to use a format, I don't believe. In the latter case (PRINTMISS), you need to create a format for your variable (if you don't already have one) that contains all levels of the data that you want to display (even if it's just an identity format, e.g. formatting character strings to identical character strings), and specify PRELOADFMT on the proc statement. See this man page for more details.
Could anybody tell me why does the compiler gives me an error - "ERROR: Insufficient page size to print frequency table." while running proc freq in sas.
I am trying to run a very simple peice of code.
proc freq data = seaepi;
tables trt* sex/ out = temp;
run;
I really appreciate your effort involved.
Thanks in advance.
> crossposted from SAS-L
I have had this problem before. This literally means that you have too many columns or you columns are too wide to fit on the page and so it will not print. Try to reduce the font size or reduce the number columns to see if you still have the problem.
Sometimes the way you handle a problem like this depends on your output destination. It would be helpful to know if you are using ODS PDF, or HTML or are just writing to the output window.
Run it with
option pagesize=max;
and see what that looks like. As mentioned already, the result will depend on what kind of output you are using. At least you can look at this output and see what it needs for a page.
If you have not tried, have a look at the options statement in SAS SAS Options Statement. There is a PageSize option which can be set.
In this case, since you've already requested that the frequency table is written to an output dataset, you could disable printing it in the results tab:
proc freq data = seaepi noprint;
tables trt* sex/ out = temp;
run;
If necessary, you could then export your output dataset or chop it into smaller bits for viewing via proc print.