How does PROC STDIZE METHOD = RANGE work?
I thought that it would work like this:
Score = (Observation - Min) / ( Max - Min)
However, the range is [1,100] and there is never a 0 i.e. when you would substract the min observation from itself on the numerator.
I've tried reading the SAS documentation and running some trials in an excel workbook
PROC STDIZE
DATA = SASHELP.BASEBALL
METHOD = RANGE
OUT = BASEBALL_STDIZE
;
VAR CRHITS;
RUN;
range [0,100] expected, range [1,100] found
Obs _TYPE_ crhit2
1 LOCATION 34
2 SCALE 4222
3 ADD 0
4 MULT 1
5 N 322
6 NObsRead 322
7 NObsUsed 322
8 NObsMiss 0
Related
I'm working in SAS as a novice. I have two datasets:
Dataset1
Unique ID
ColumnA
1
15
1
39
2
20
3
10
Dataset2
Unique ID
ColumnB
1
40
2
55
2
10
For each UniqueID, I want to subtract all values of ColumnB by each value of ColumnA. And I would like to create a NewColumn that is 1 anytime 1>ColumnB-Column >30. For the first row of Dataset 1, where UniqueID= 1, I would want SAS to go through all the rows in Dataset 2 that also have a UniqueID = 1 and determine if there is any rows in Dataset 2 where the difference between ColumnB and ColumnA is greater than 1 or less than 30. For the first row of Dataset 1 the NewColumn should be assigned a value of 1 because 40 - 15 = 25. For the second row of Dataset 1 the NewColumn should be assigned a value of 0 because 40 - 39 = 1 (which is not greater than 1). For the third row of Dataset 1, I again want SAS to go through every row of ColumnB in Dataset 2 that has the same UniqueID as in Dataset1, so 55 - 20 = 35 (which is greater than 30) but NewColumn would still be assigned a value of 1 because (moving to row 3 of Datatset 2 which has UniqueID =2) 20 - 10 = 10 which satisfies the if statement.
So I want my output to be:
Unique ID
ColumnA
NewColumn
1
15
1
1
30
0
2
20
1
I have tried concatenating Dataset1 and Dataset2 into a FullDataset. Then I tried using a do loop statement but I can't figure out how to do the loop for each value of UniqueID. I tried using BY but that of course produces an error because that is only used for increments.
DATA FullDataset;
set Dataset1 Dataset2; /*Concatenate datasets*/
do i=ColumnB-ColumnA by UniqueID;
if 1<ColumnB-ColumnA<30 then NewColumn=1;
output;
end;
RUN;
I know I'm probably way off but any help would be appreciated. Thank you!
So, the way that answers your question most directly is the keyed set. This isn't necessarily how I'd do this, but it is fairly simple to understand (as opposed to a hash table, which is what I'd use, or a SQL join, probably what most people would use). This does exactly what you say: grabs a row of A, says for each matching row of B check a condition. It requires having an index on the datasets (well, at least on the B dataset).
data colA(index=(id));
input ID ColumnA;
datalines;
1 15
1 39
2 20
3 10
;;;;
data colB(index=(id));
input ID ColumnB;
datalines;
1 40
2 55
2 30
;;;;
run;
data want;
*base: the colA dataset - you want to iterate through that once per row;
set colA;
*now, loop while the check variable shows 0 (match found);
do while (_iorc_ = 0);
*bring in other dataset using ID as key;
set colB key=ID ;
* check to see if it matches your requirement, and also only check when _IORC_ is 0;
if _IORC_ eq 0 and 1 lt ColumnB-ColumnA lt 30 then result=1;
* This is just to show you what is going on, can remove;
put _all_;
end;
*reset things for next pass;
_ERROR_=0;
_IORC_=0;
run;
I have a sample that include two variables: ID and ym. ID id refer to the specific ID for each trader and ym refer to the year-month variable. And I want to create a variable that show the number of years over the 10 years period prior month t as shown in the following figure.
ID ym Want
1 200101 0
1 200301 1
1 200401 2
1 200501 3
1 200601 4
1 200801 5
1 201201 5
1 201501 4
2 200001 0
2 200203 1
2 200401 2
2 200506 3
I attempt to use by function and fisrt.id to count the number.
data want;
set have;
want+1;
by id;
if first.id then want=1;
run;
However, the year in ym is not continuous. When the time gap is higher than 10 years, this method is not working. Although I assume I need to count the number of year in a rolling window (10 years), I am not sure how to achieve it. Please give me some suggestions. Thanks.
Just do a self join in SQL. With your coding of YM it is easy to do interval that is a multiple of a year, but harder to do other intervals.
proc sql;
create table want as
select a.id,a.ym,count(b.ym) as want
from have a
left join have b
on a.id = b.id
and (a.ym - 1000) <= b.ym < a.ym
group by a.id,a.ym
order by a.id,a.ym
;
quit;
This method retains the previous values for each ID and directly checks to see how many are within 120 months of the current value. It is not optimized but it works. You can set the array m() to the maximum number of values you have per ID if you care about efficiency.
The variable d is a quick shorthand I often use which converts years/months into an integer value - so
200012 -> (2000*12) + 12 = 24012
200101 -> (2001*12) + 1 = 24013
time from 200012 to 200101 = 24013 - 24012 = 1 month
data have;
input id ym;
datalines;
1 200101
1 200301
1 200401
1 200501
1 200601
1 200801
1 201201
1 201501
2 200001
2 200203
2 200401
2 200506
;
proc sort data=have;
by id ym;
data want (keep=id ym want);
set have;
by id;
retain seq m1-m100;
array m(100) m1-m100;
** Convert date to comparable value **;
d = 12 * floor(ym/100) + mod(ym,10);
** Initialize number of previous records **;
want = 0;
** If first record, set retained values to missing and leave want=0 **;
if first.id then call missing(seq,of m1-m100);
** Otherwise loop through previous months and count how many were within 120 months **;
else do;
do i = 1 to seq;
if d <= (m(i) + 120) then want = want + 1;
end;
end;
** Increment variables for next iteration **;
seq + 1;
m(seq) = d;
run;
proc print data=want noobs;
I tried searching multiple places but have not been able to find a solution yet. I was wondering if someone here would be able to please help me?
I am trying to calculate a median value (with Q1 and Q3) across multiple rows and columns in SAS 9.4 The dataset I am working with looks like the following:
Obs tumor_size_1 tumor_size_2 tumor_size_3 tumor_size_4
1 4 1.5 1 1
2 2.5 2 . .
3 3 . . .
4 4 . . .
5 3.5 1 . .
The context is this is for a medical condition where a person may have 1 (or more) tumors. Each row represents 1 person. Each person may have up to 4 tumors. I would like to determine the median size of all tumors for the entire cohort (not just the median size for each person). Is there a way to calculate this? Thank you in advance.
A transpose of the data will yield a data structure (form) that is amenable to median and quartile computations, at a variety of aggregate combinations, made with PROC SUMMARY and a CLASS statement.
Example:
data have;
input
patient tumor_size_1 tumor_size_2 tumor_size_3 tumor_size_4; datalines;
1 4 1.5 1 1
2 2.5 2 . .
3 3 . . .
4 4 . . .
5 3.5 1 . .
;
proc transpose data=have out=new_have;
by patient;
var tumor:;
run;
proc summary data=new_have;
class patient;
var col1;
output out=want Q1=Q1 Q3=Q3 MEDIAN=MEDIAN N=N;
run;
Results
patient _TYPE_ _FREQ_ Q1 Q3 MEDIAN N
. 0 20 1 3.50 2.25 10
1 1 4 1 2.75 1.25 4
2 1 4 2 2.50 2.25 2
3 1 4 3 3.00 3.00 1
4 1 4 4 4.00 4.00 1
5 1 4 1 3.50 2.25 2
The _TYPE_ column describes the ways in which the CLASS variables are combined in order to achieve the results for the requested statistics. The _TYPE_ = 0 case is for all values, and, in this problem, the _FREQ_ = 20 indicates 20 inputs went into the computation consideration, and that N = 10 of those were non-missing and were involved in the actual computation. The role of _TYPE_ becomes more obvious when there is more than one CLASS variable.
From the Output Data Set documentation:
the variable _TYPE_ that contains information about the class variables. By default _TYPE_ is a numeric variable. If you specify CHARTYPE in the PROC statement, then _TYPE_ is a character variable. When you use more than 32 class variables, _TYPE_ is automatically a character variable.
and
The value of _TYPE_ indicates which combination of the class variables PROC MEANS uses to compute the statistics. The character value of _TYPE_ is a series of zeros and ones, where each value of one indicates an active class variable in the type. For example, with three class variables, PROC MEANS represents type 1 as 001, type 5 as 101, and so on.
A far less elegant way to compute the median of all is to store all the values in an oversized array and use the MEDIAN function on the array after the last row is read in:
data median_all;
set have end=lastrow;
array values [1000000] _temporary_;
array sizes tumor_size_1-tumor_size_4;
do sIndex = 1 to dim(sizes);
/* if not missing (sizes[sIndex]) then do; */ %* decomment for dense fill;
vIndex + 1;
values[vIndex] = sizes[sIndex];
/* end; */ %* decomment for dense fill;
end;
if lastrow then do;
median_all_tumor_sizes = median (of values(*));
output;
put (median:) (=);
end;
keep median:;
run;
-------- LOG -------
median_all_tumor_sizes=2.25
I want to recode the max value of a variable as 1 and 0 when it is not. For each variable, there may be multiple observations with the max value. The max value for each value is not fixed, i.e. from cycle to cycle the max value for each variable may change. And there are hundreds of variables, cannot "hard-code" anything.
The final product would have the same dimensions as the original table, i.e. equal number of rows and columns as a matrix of 0s and 1s.
This is within SAS. I attempted to calculate the max of each variable and then append these max as a new observation into the data. Then comparing down the column of each variable against the "max" observation... looking into examples of the following did not help:
SQL
Array in datastep
proc transpose
formatting
Any insight would be much appreciated.
Here is a version done with SQL:
The idea is that we first calculate the maximum. The Latter select. Then we join the data to original and the outer the case-select specifies if the flag is set up or not.
data begin;
input var value;
cards;
1 1
1 2
1 3
1 2.5
1 1.7
1 3
2 34
2 33
2 33
2 33.7
2 34
2 34
; run;
proc sql;
create table result as
select a.var, a.value, case when a.value = b.maximum then 1 else 0 end as is_max from
(select * from begin) a
left join
(select max(value) as maximum, var from begin group by var) b
on a.var = b.var
;
quit;
To avoid "hard-code" you need to use some code generation.
First let's figure out what code you could use to solve the problem. Later we can look into ways to generate that code.
It is probably easiest to do this with PROC SQL code. SAS will allow you to reference the MAX() value of a variable. Also note that SAS evaluates boolean expressions to 1 (TRUE) or 0 (FALSE). So you just want to generate code like:
proc sql;
create table want as
select var1=max(var1) as var1
, var2=max(var2) as var2
from have
;
quit;
To generate the code you need a list of the variables in your source dataset. You can get those with PROC CONTENTS but also with the metadata table (view) DICTIONARY.COLUMNS (also accessible as SASHELP.VCOLUMN from outside PROC SQL).
If the list of variables is small then you could generate the code into a single macro variable.
proc sql noprint;
select catx(' ',cats(name,'=max(',name,')'),'as',name)
into :varlist separated by ','
from dictionary.columns
where libname='WORK' and memname='HAVE'
order by varnum
;
create table want as
select &varlist
from have
;
quit;
The maximum number of characters that will fit into a macro variable is 64K. So long enough for about 2,000 variables with names of 8 characters each.
Here is little more complex way that uses PROC SUMMARY and a data step with a temporary array. It does not really need any code generation.
%let dsin=sashelp.class(obs=10);
%let dsout=want;
%let varlist=_numeric_;
proc summary data=&dsin nway ;
var &varlist;
output out=summary(drop=_type_ _freq_) max= ;
run;
data &dsout;
if 0 then set &dsin;
array vars &varlist;
array max [10000] _temporary_;
if _n_=1 then do;
set summary ;
do _n_=1 to dim(vars);
max[_n_]=vars[_n_];
end;
end;
set &dsin;
do _n_=1 to dim(vars);
vars[_n_]=vars[_n_]=max[_n_];
end;
run;
Results:
Obs Name Sex Age Height Weight
1 Alfred M 0 1 1
2 Alice F 0 0 0
3 Barbara F 0 0 0
4 Carol F 0 0 0
5 Henry M 0 0 0
6 James M 0 0 0
7 Jane F 0 0 0
8 Janet F 1 0 1
9 Jeffrey M 0 0 0
10 John M 0 0 0
I have a situation where I would like to put the value of a variable in the label in SAS.
Example: Median for Total_Days is 2. I would like to put this value in Days_Median_Split label. The median keeps on changing with varying data, so I would like to automate it.
Phy_Activity Total_Days "Days_Median_Split: Number of Days with Median 2"
No 0 0
No 0 0
Yes 2 1
Yes 3 1
Yes 5 1
Sample Dataset
Thanks so much!
* step 1 create data;
data have;
input Phy_Activity $ Total_Days Days_Median_Split;
datalines;
No 0 0
No 0 0
Yes 2 1
Yes 3 1
Yes 5 1
run;
*step 2 sort data on Total_days;
proc sort data = have;
by Total_days;
run;
*step 3 get count of obs;
proc sql noprint;
select count(*) into: cnt
from have;quit;
* step 4 calulate median;
%let median = %sysevalf(&cnt/2 + .5);
*step 5 get median obsevation;
proc sql noprint;
select Total_days into: medianValue
from have
where monotonic()=&median;quit;
*step 6 create label;
data have;
set have;
label Days_Median_split = 'Days_Median_split: Number of Days with Median '
%trim(&medianValue);
run;