I can see in sas there is a logistic() function that calculates the inverse-logit(x).
logistic(x) = exp(x)/(exp(x)+1)
Is there a function that calculates logit(x)?
logit(x) = log(p/1-p)
There is not, but proc fcmp lets you create functions.
options cmplib=work.funcs;
proc fcmp outlib=work.funcs.stats;
function logit(p);
if(0 < p < 1) then do;
result = log(p/(1-p));
return(result);
end;
else put "ERROR: Invalid argument to logit function.";
endsub;
run;
data _null_;
logit = logit(0.2);
put logit;
run;
A breakdown of how to save and load custom functions:
options cmplib=work.funcs;
Load custom functions from the dataset work.funcs, if it exists.
proc fcmp outlib=work.funcs.stats;
Output and append custom functions to a dataset named funcs. The 3-level outlib statement is a bit confusing since it's actually creating a hierarchical dataset.
The Three-Level Name
one.two.three
one: Output library name
two: Dataset name to hold custom functions
three: An identifier package name to be added to the dataset. We're calling this the stats package.
If you open up the dataset work.funcs, you will see the stats package within the column labeled _Key_.
Related
I have multiple SAS dataset in single location(folder) with two columns and name of the SAS dataset seems to be Diagnosis_<diagnosis_name>.
Here I want to load all dataset and combine all together like below,
Sample data set
File Location: C:\Users\xyz\Desktop\diagnosis\Diagnosis_<diagnosis_name>.sas7bdat
1. Dataset Name : Diagnosis_Diabetes.sas7bdat
2. Dataset Name : Diagnosis_Obesity.sas7bdat
Ouput which I expect like this
Could you please help me on this.
You can just combine the datasets using SET statement. If want all of the datasets with names that start with a constant prefix you can use the : wildcard to make a name list.
First create a libref to reference the directory:
libname diag 'C:\Users\xyz\Desktop\diagnosis\';
Then combine the datasets. If the original datasets are sorted by the PersonID then you can add a BY statement and the result will also be sorted.
data tall;
set diag.diagnosis_: ;
by person_id;
run;
If want to generate that wide dataset you could use PROC TRANSPOSE, but in that case you will need some extra variable to actually transpose.
data tall;
set diag.diagnosis_: ;
by person_id;
present=1;
run;
proc transpose data=tall out=want(drop=_name_);
by person_id;
id diagnosis;
var present;
run;
My question is about the append of two different tables that are supposed to have the same name/format/type/length variables.
I am trying to create a step in my SAS program where I don't allow my program to be executed if the format/type/length of variables with the same name is not the same.
For example, when in one table I have a date in type string "dd-mm-yyyy" and in the other table I have the "yyyy-mm-dd" or "dd-mm-yyyy hh:mm:ss". After the append, our daily executions based on these input tables didn't work as expected. Sometimes the values come up as missing or out of order, since the formats are different.
I tried using the PROC COMPARE statement, which allowed me to check which variables have Differing Attributes (Type, Length, Format, InFormat and Labels).
proc compare base = SAS-data-set
compare = SAS-data-set;
run;
However, I only got the info on which variables have differing atributes (listing of common variables with differing attributes), not being able to do anything with/about it.
On the other hand, I would like to know if there's a chance to have a structured output table with this information, in order to use it as a control statement.
Creating an automatic task to do it would save me a lot of time.
Screenshot of an example:
You can use Proc CONTENTS to get information about a data sets variables. Do that for both data sets, and then you can use Proc COMPARE to create a data set informing you of the variable attributes differences.
data cars1;
set sashelp.cars (obs=10);
date = today ();
format date date9.;
cars1_only = 1;
x = 1.458; label x = "x-factor";
run;
data cars2;
length type $50;
set sashelp.cars (obs=10);
format date yymmdd10.;
cars2_only = 1;
X = 1.548; label x = "X factor to apply";
run;
proc contents noprint data=cars1 out=cars1_contents;
proc contents noprint data=cars2 out=cars2_contents;
run;
data cars1_contents;
set cars1_contents;
upName = upcase(Name);
run;
data cars2_contents;
set cars2_contents;
upName = upcase(Name);
run;
proc sort data=cars1_contents; by upName;
proc sort data=cars2_contents; by upName;
run;
proc compare noprint
base=cars1_contents
compare=cars2_contents
outall
out=cars_contents_compare (where=(_TYPE_ ne 'PERCENT'))
;
by upName;
run;
There is also an ODS table you can capture directly without having to run Proc CONTENTS, but the capture is not 'data-rific'
ods output CompareVariables=work.cars_vars;
proc compare base=cars1 compare=cars2;
run;
I want to count the number of records in a dataset in SAS. There is a function the make this thing in a simple way? I used R ed for obtain this information there was the length() function. Morover I need the number of record to compute some percetages so I need this value not in a table but in a value that can be used for other data step. How can I fix?
Thanks in advance
Here is another solution, using SAS dictionaries,
proc sql;
select nobs into: num_obs
from dictionary.tables
where libname = "WORK" and memname = "A"
;
quit;
It is easy to get the size of many datasets by modifying the above code,
proc sql;
create table test as
select memname, nobs
from dictionary.tables
where libname = "WORK" and memname like "A%"
;
quit;
data _null_;
set test;
call symput(memname, nobs);
run;
The above code will give you the sizes of all data sets with name starting with "a" in the temporary/work library.
Assuming this is a basic SAS table that you've created, and not modified or appended to, the best way is to use the meta data held in a dataset (the Number of tries is held in a piece of meta data called "nobs"), without reading through the dataset its self and place it in a macro variable. You can do this in the following way:
Data _null_;
i=1;
If i = 0 then set DATASETTOCOUNT nobs= mycount;
Call symput('mycount', mycount);
Run;
%put &mycount.;
You will now have a macro variable that contains the number of rows in your dataset, that you can call on in other data steps using &mycount.
I have a table with postings by category (a number) that I transposed. I got a table with each column name as _number for example _16, _881, _853 etc. (they aren't in order).
I need to do the sum of all of them in a proc sql, but I don't want to create the variable in a data step, and I don't want to write all of the columns names either . I tried this but doesn't work:
proc sql;
select sum(_815-_16) as nnl
from craw.xxxx;
quit;
I tried going to the first number to the last and also from the number corresponding to the first place to the one corresponding to the last place. Gives me a number that it's not correct.
Any ideas?
Thanks!
You can't use variable lists in SQL, so _: and var1-var6 and var1--var8 don't work.
The easiest way to do this is a data step view.
proc sort data=sashelp.class out=class;
by sex;
run;
*Make transposed dataset with similar looking names;
proc transpose data=class out=transposed;
by sex;
id height;
var height;
run;
*Make view;
data transpose_forsql/view=transpose_forsql;
set transposed;
sumvar = sum(of _:); *I confirmed this does not include _N_ for some reason - not sure why!;
run;
proc sql;
select sum(sumvar) from transpose_Forsql;
quit;
I have no documentation to support this but from my experience, I believe SAS will assume that any sum() statement in SQL is the sql-aggregate statement, unless it has reason to believe otherwise.
The only way I can see for SAS to differentiate between the two is by the way arguments are passed into it. In the below example you can see that the internal sum() function has 3 arguments being passed in so SAS will treat this as the SAS sum() function (as the sql-aggregate statement only allows for a single argument). The result of the SAS function is then passed in as the single parameter to the sql-aggregate sum function:
proc sql noprint;
create table test as
select sex,
sum(sum(height,weight,0)) as sum_height_and_weight
from sashelp.class
group by 1
;
quit;
Result:
proc print data=test;
run;
sum_height_
Obs Sex and_weight
1 F 1356.3
2 M 1728.6
Also note a trick I've used in the code by passing in 0 to the SAS function - this is an easy way to add an additional parameter without changing the intended result. Depending on your data, you may want to swap out the 0 for a null value (ie. .).
EDIT: To address the issue of unknown column names, you can create a macro variable that contains the list of column names you want to sum together:
proc sql noprint;
select name into :varlist separated by ','
from sashelp.vcolumn
where libname='SASHELP'
and memname='CLASS'
and upcase(name) like '%T' /* MATCHES HEIGHT AND WEIGHT */
;
quit;
%put &varlist;
Result:
Height,Weight
Note that you would need to change the above wildcard to match your scenario - ie. matching fields that begin with an underscore, instead of fields that end with the letter T. So your final SQL statement will look something like this:
proc sql noprint;
create table test as
select sex,
sum(sum(&varlist,0)) as sum_of_fields_ending_with_t
from sashelp.class
group by 1
;
quit;
This provides an alternate approach to Joe's answer - though I believe using the view as he suggests is a cleaner way to go.
I have a SAS dataset which has 20 character variables, all of which are names (e.g. Adam, Bob, Cathy etc..)
I would like a dynamic code to create variables called Adam_ref, Bob_ref etc.. which will work even if there a different dataset with different names (i.e. don't want to manually define each variable).
So far my approach has been to use proc contents to get all variable names and then use a macro to create macro variables Adam_ref, Bob_ref etc..
How do I create actual variables within the dataset from here? Do I need a different approach?
proc contents data=work.names
out=contents noprint;
run;
proc sort data = contents; by varnum; run;
data contents1;
set contents;
Name_Ref = compress(Name||"_Ref");
call symput (NAME, NAME_Ref);
%put _user_;
run;
If you want to create an empty dataset that has variables named like some values you have in a macro variables you could do something like this.
Save the values into macro variables that are named by some pattern, like v1, v2 ...
proc sql;
select compress(Name||"_Ref") into :v1-:v20 from contents;
quit;
If you don't know how many values there are, you have to count them first, I assumed there are only 20 of them.
Then, if all your variables are character variables of length 100, you create a dataset like this:
%macro create_dataset;
data want;
length %do i=1 %to 20; &&v&i $100 %end;
;
stop;
run;
%mend;
%create_dataset; run;
This is how you can do it if you have the values in macro variable, there is probably a better way to do it in general.
If you don't want to create an empty dataset but only change the variable names, you can do it like this:
proc sql;
select name into :v1-:v20 from contents;
quit;
%macro rename_dataset;
data new_names;
set have(rename=(%do i=1 %to 20; &&v&i = &&v&i.._ref %end;));
run;
%mend;
%rename_dataset; run;
You can use PROC TRANSPOSE with an ID statement.
This step creates an example dataset:
data names;
harry="sally";
dick="gordon";
joe="schmoe";
run;
This step is essentially a copy of your step above that produces a dataset of column names. I will reuse the dataset namerefs throughout.
proc contents data=names out=namerefs noprint;
run;
This step adds the "_Refs" to the names defined before and drops everything else. The variable "name" comes from the column attributes of the dataset output by PROC CONTENTS.
data namerefs;
set namerefs (keep=name);
name=compress(name||"_Ref");
run;
This step produces an empty dataset with the desired columns. The variable "name" is again obtained by looking at column attributes. You might get a harmless warning in the GUI if you try to view the dataset, but you can otherwise use it as you wish and you can confirm that it has the desired output.
proc transpose out=namerefs(drop=_name_) data=namerefs;
id name;
run;
Here is another approach which requires less coding. It does not require running proc contents, does not require knowing the number of variables, nor creating a macro function. It also can be extended to do some additional things.
Step 1 is to use built-in dictionary views to get the desired variable names. The appropriate view for this is dictionary.columns, which has alias of sashelp.vcolumn. The dictionary libref can be used only in proc sql, while th sashelp alias can be used anywhere. I tend to use sashelp alias since I work in windows with DMS and can always interactively view the sashelp library.
proc sql;
select compress(Name||"_Ref") into :name_list
separated by ' '
from sashelp.vcolumn
where libname = 'WORK'
and memname = 'NAMES';
quit;
This produces a space delimited macro vaiable with the desired names.
Step 2 To build the empty data set then this code will work:
Data New ;
length &name_list ;
run ;
You can avoid assuming lengths or create populated dataset with new variable names by using a slightly more complicated select statement.
For example
select compress(Name)||"_Ref $")||compress(put(length,best.))
into :name_list
separated by ' '
will generate a macro variable which retains the previous length for each variable. This will work with no changes to step 2 above.
To create populated data set for use with rename dataset option, replace the select statement as follows:
select compress(Name)||"= "||compress(_Ref")
into :name_list
separated by ' '
Then replace the Step 2 code with the following:
Data New ;
set names (rename = ( &name_list)) ;
run ;