I have data which looks like following.
I was wondering how to run a t-test when variables that I want to compare are in different columns
+---------+------------+----------+-------------+-------------+----------------+
| Case_id | Control_id | case_age | control_age | case_result | control_result |
+---------+------------+----------+-------------+-------------+----------------+
| 1 | 50 | 24 | 24 | 23 | 12 |
| 1 | 52 | 24 | 24 | 23 | 10 |
| 2 | 65 | 27 | 27 | 24 | 15 |
| 2 | 70 | 27 | 27 | 24 | 14 |
+---------+------------+----------+-------------+-------------+----------------+
The SAS tutorials indicate the following syntax for running a t-test. But in my case I do not have a class variable to distinguish between cases and control. Is there a way to tell SAS to compare two variables case_result and control_result.
proc ttest data;
class Gender;
var Score;
run;
If you would like to compare two variables, it can be done this way:
proc compare base=libname.dataset allstats briefsummary;
var var1;
with var2;
title 'Comparison two variables';
run;
To run ttest on difference b/w two variables (paired comparison),
proc ttest data=libname.dataset;
paired var1*var2;
run;
Related
How do you extract all values containing part of a particular number and then delete them?
I have data where the ID contains different lengths and wants to extract all the IDs with a particular number. For example, if the ID contains either "-00" or "02" or "-01" at the end, pull to be able to see the hit rate that includes those—then delete them from the ID. Is there a more effecient way in creating this code?
I tried to use the substring function to slice it to get the result, but there is some other ID along with the specified position.
Code:
Proc sql;
Create table work.data1 AS
SELECT Product, Amount_sold, Price_per_unit,
CASE WHEN Product Contains "Pen" and Lenghth(ID) >= 9 Then ID = SUBSTR(ID,1,9)
WHEN Product Contains "Book" and Lenghth(ID) >= 11 Then ID = SUBSTR(ID,1,11)
WHEN Product Contains "Folder" and Lenghth(ID) >= 12 Then ID = SUBSTR(ID,1,12)
...
END AS ID
FROM A
Quit;
Have:
+------------------+-----------------+-------------+----------------+
| ID | Product | Amount_sold | Price_per_unit |
+------------------+-----------------+-------------+----------------+
| 123456789 | Pen | 30 | 2 |
| 63495837229-01 | Book | 20 | 5 |
| ABC134475472 02 | Folder | 29 | 7 |
| AB-1235674467-00 | Pencil | 26 | 1 |
| 69598346-02 | Correction pen | 15 | 1.50 |
| 6970457688 | Highlighter | 15 | 2 |
| 584028467 | Color pencil | 15 | 10 |
+------------------+-----------------+-------------+----------------+
Wanted the final result:
+------------------+-----------------+-------------+----------------+
| ID | Product | Amount_sold | Price_per_unit |
+------------------+-----------------+-------------+----------------+
| 123456789 | Pen | 30 | 2 |
| 63495837229 | Book | 20 | 5 |
| ABC134475472 | Folder | 29 | 7 |
| AB-1235674467 | Pencil | 26 | 1 |
| 69598346 | Correction pen | 15 | 1.50 |
| 6970457688 | Highlighter | 15 | 2 |
| 584028467 | Color pencil | 15 | 10 |
+------------------+-----------------+-------------+----------------+
Just test if the string has any embedded spaces or hyphens and also that the last word when delimited by space or hyphen is 00 or 01 or 02 then chop off the last three characters.
data have;
infile cards dsd dlm='|' truncover ;
input id :$20. product :$20. amount_sold price_per_unit;
cards;
123456789 | Pen | 30 | 2 |
63495837229-01 | Book | 20 | 5 |
ABC134475472 02 | Folder | 29 | 7 |
AB-1235674467-00 | Pencil | 26 | 1 |
69598346-02 | Correction pen | 15 | 1.50 |
6970457688 | Highlighter | 15 | 2 |
584028467 | Color pencil | 15 | 10 |
;
data want;
set have ;
if indexc(trim(id),'- ') and scan(id,-1,'- ') in ('00' '01' '02') then
id = substrn(id,1,length(id)-3)
;
run;
Result
amount_ price_
Obs id product sold per_unit
1 123456789 Pen 30 2.0
2 63495837229 Book 20 5.0
3 ABC134475472 Folder 29 7.0
4 AB-1235674467 Pencil 26 1.0
5 69598346 Correction pen 15 1.5
6 6970457688 Highlighter 15 2.0
7 584028467 Color pencil 15 10.0
There may be other solutions but you have to use some string functions. I used here the functions substr, reverse (reverting the string) and indexc (position of one of the characters in the string):
data have;
input text $20.;
datalines;
12345678
AB-142353 00
AU-234343-02
132453 02
221344-09
;
run;
data want (drop=reverted pos);
set have;
if countw(text) gt 1
then do;
reverted=strip(reverse(text));
pos=indexc(reverted,'- ')+1;
new=strip(reverse(substr(reverted,pos)));
end;
else new=text;
run;
I have the following table
+-------+--------+---------+
| group | item | value |
+-------+--------+---------+
| 1 | a | 10 |
| 1 | b | 20 |
| 2 | b | 30 |
| 2 | c | 40 |
+-------+--------+---------+
I would like to group the table by group, insert the grouped sum into value, and then ungroup:
+-------+--------+
| item | value |
+-------+--------+
| 1 | 30 |
| a | 10 |
| b | 20 |
| 2 | 70 |
| b | 30 |
| c | 40 |
+-------+--------+
The purpose of the result is to interpret the first column as items a and b belonging to group 1 with sum 30 and items b and c belonging to group 2 with sum 70.
Such a data transformation can be indicative of a reporting requirement more than a useful data structure for downstream processing. Proc REPORT can create output in the form desired.
data have;
infile datalines;
input group $ item $ value ##; datalines;
1 a 10 1 b 20 2 b 30 2 c 40
;
proc report data=have;
column group item value;
define group / order order=data noprint;
break before group / summarize;
compute item;
if missing(item) then item=group;
endcomp;
run;
I assume that both group and item are character variables
data have;
infile datalines firstobs=4 dlm='|';
input group $ item $ value;
datalines;
+-------+--------+---------+
| group | item | value |
+-------+--------+---------+
| 1 | a | 10 |
| 1 | b | 20 |
| 2 | b | 30 |
| 2 | c | 40 |
+-------+--------+---------+
;
data want (keep=group value);
do _N_=1 by 1 until (last.group);
set have;
by group;
v + value;
end;
value = v;output;v=0;
do _N_=1 to _N_;
set have;
group = item;
output;
end;
run;
I am trying to run a code that should work on tables created considering different factors. As these factors can be more than 1, I decided to create a macro %let to list them:
%let list= factor1 factor2 ...;
What I would like to do is run a code to create these tables using different factors. For each factor, I computed using proc means the mean and the standard deviation, so I should have the variables &list._mean and &list._stddev in the table created by the proc means for each factor. This table is labelled as t2 and I need to join to another table, t1. From t1 I am considering all the variables.
My main difficulties are, therefore, in the proc sql:
proc sql;
create table new_table as
select t1.*
, t2.&list._mean as mean
, t2.&list._stddev as stddev
from table1 as t1
left join table2 as t2
on t1.time=t2.time
order by t2.&list.
quit;
This code is returning an error and I think because I am considering t2.factor1 factor2, i.e. t2 is only applied to the first factor, not to the second one.
What I would expect is the following:
proc sql;
create table new_table as
select t1.*
, t2.factor1._mean as mean
, t2.factor1._stddev as stddev
from table1 as t1
left join table2 as t2
on t1.time=t2.time
order by t2.factor1.
quit;
and another one for factor2.
UPDATE CODE:
%macro test_v1(
_dtb
,_input
,_output
,_time
,_factor
);
data &_input.;
set &_dtb..&_input.;
keep &_col_period. &_factor.;
run;
proc sort data = work.&_input.
out = &_input._1;
by &_factor. &_time.;
run;
%put ERROR: 2
proc means data=&_input._1 nonobs mean stddev;
class &_time.;
var &_factor.;
output out=&_input._n (drop=_TYPE_) mean= stddev= /autoname ;
run;
%put ERROR: 3
proc sql;
create table work.&_input._data as
select t1.*
,t2.&_factor._mean as mean
,t2.&_factor._stddev as stddev
from &_input. as t1
left join &_input._n as t2
on t1.&_time.=t2.&_time.
order by &_factor.;
quit;
%mend test_v1;
Then my question is on how I can consider multiple factors, defined into a macro as a list, as columns of tables and as input data into a macro (for example: %test(dataset, tablename, list).
I suspect that trying to use PROC SQL is what is making the problem hard. If you stick to just using normal SAS syntax your space delimited list of variable names is easy to use.
So taking your code and tweaking it a little:
%macro test_v1
(_dtb /* Input libref */
,_input /* Input member name */
,_output /* Output dataset */
,_time /* Class/By variable(s) */
,_factor /* Analysis variable(s) */
);
proc sort data= &_dtb..&_input. out=_temp1;
by &_time. ;
run;
proc means data=_temp1 nonobs mean stddev;
by &_time.;
var &_factor.;
output out=_temp2 (drop=_TYPE_) mean= stddev= /autoname ;
run;
data &_output. ;
merge _temp1 _temp2 ;
by &_time.;
run;
%mend test_v1;
We can then test it using SASHELP.CLASS by using SEX as the "time" variable and HEIGHT and WEIGHT as the analysis variables.
%test_v1(_dtb=sashelp,_input=class,_output=want,_time=sex,_factor=height weight);
You can try to add macro loop to your macros by scanning list of factors. It could look like:
%macro test(list);
%do i=1 to %sysfunc(countw(&list,%str( )));
%let factorname=%scan(&list,&i,%str( ));
/* if macro variable list equals factor1 factor2 then there would be
two iterations in loop, i=1 factorname=factor1 and i=2 factorname=2*/
/*your code here*/
%end
%mend test;
UPDATE:
%macro test(_input, _output, factors_list); %macro d; %mend d;
%do i=1 %to %sysfunc(countw(&factors_list,%str( )));
%let tfactor=%scan(&factors_list,&i,%str( ));
proc sort data = work.&_input.
out = &_input._1;
by &factors_list. time;
run;
proc means data=&_input._1 nonobs mean stddev;
class time;
var &tfactor.;
output out=&_input._num (drop=_TYPE_) mean= stddev= /autoname ;
run;
proc sql;
create table &_output._&tfactor as
select t1.*
, t2.&tfactor._mean as mean
, t2.&tfactor._stddev as stddev
from &_input as t1
left join &_input._num as t2
on t1.time=t2.time
order by t1.&tfactor;
quit;
%end;
%mend test;
%test(have,newdata,factor1 factor2);
Have dataset:
+------+---------+---------+
| time | factor1 | factor2 |
+------+---------+---------+
| 1 | 12345 | 1234 |
| 2 | 123 | 12 |
| 3 | 1 | -1 |
| 4 | -12 | -123 |
| 5 | -1234 | -12345 |
| 6 | 9876 | 987 |
| 7 | 98 | 8 |
| 8 | 9 | 7 |
| 1 | 1234 | 123 |
| 2 | 12 | 1 |
| 3 | 12 | -12 |
| 4 | -123 | -1234 |
| 5 | -12345 | -123456 |
| 6 | 987 | 98 |
| 7 | 9 | -9 |
| 8 | 1234 | 1234 |
+------+---------+---------+
NEWDATA_FACTOR1:
+------+---------+---------+---------+--------------+
| time | factor1 | factor2 | mean | stddev |
+------+---------+---------+---------+--------------+
| 5 | -12345 | -123456 | -6789.5 | 7856.6634458 |
| 5 | -1234 | -12345 | -6789.5 | 7856.6634458 |
| 4 | -123 | -1234 | -67.5 | 78.488852712 |
| 4 | -12 | -123 | -67.5 | 78.488852712 |
| 3 | 1 | -1 | 6.5 | 7.7781745931 |
| 7 | 9 | -9 | 53.5 | 62.932503526 |
| 8 | 9 | 7 | 621.5 | 866.20580695 |
| 3 | 12 | -12 | 6.5 | 7.7781745931 |
| 2 | 12 | 1 | 67.5 | 78.488852712 |
| 7 | 98 | 8 | 53.5 | 62.932503526 |
| 2 | 123 | 12 | 67.5 | 78.488852712 |
| 6 | 987 | 98 | 5431.5 | 6285.472178 |
| 1 | 1234 | 123 | 6789.5 | 7856.6634458 |
| 8 | 1234 | 1234 | 621.5 | 866.20580695 |
| 6 | 9876 | 987 | 5431.5 | 6285.472178 |
| 1 | 12345 | 1234 | 6789.5 | 7856.6634458 |
+------+---------+---------+---------+--------------+
NEWDATA_FACTOR2:
+------+---------+---------+----------+--------------+
| time | factor1 | factor2 | mean | stddev |
+------+---------+---------+----------+--------------+
| 5 | -12345 | -123456 | -67900.5 | 78567.341564 |
| 5 | -1234 | -12345 | -67900.5 | 78567.341564 |
| 4 | -123 | -1234 | -678.5 | 785.5956339 |
| 4 | -12 | -123 | -678.5 | 785.5956339 |
| 3 | 12 | -12 | -6.5 | 7.7781745931 |
| 7 | 9 | -9 | -0.5 | 12.02081528 |
| 3 | 1 | -1 | -6.5 | 7.7781745931 |
| 2 | 12 | 1 | 6.5 | 7.7781745931 |
| 8 | 9 | 7 | 620.5 | 867.62002052 |
| 7 | 98 | 8 | -0.5 | 12.02081528 |
| 2 | 123 | 12 | 6.5 | 7.7781745931 |
| 6 | 987 | 98 | 542.5 | 628.61792847 |
| 1 | 1234 | 123 | 678.5 | 785.5956339 |
| 6 | 9876 | 987 | 542.5 | 628.61792847 |
| 1 | 12345 | 1234 | 678.5 | 785.5956339 |
| 8 | 1234 | 1234 | 620.5 | 867.62002052 |
+------+---------+---------+----------+--------------+
I am trying to merge two tables. table A has an id column, a date column, and an amount value for every date in a period
Table B has both id and date, but also other columns with details. However, there is only one entry any time there is a change in the details, so I do not know how to merge with normal joins. I want that for every entry in A, the details are populated as of the latest day available in B for that ID before the date in A.
Table A
| ID | date | amount |
| 1 | 01JAN| 56 |
| 1 | 02JAN| 54 |
| 1 | 03JAN| 23 |
| 1 | 04JAN| 43 |
Table B
| ID | date | details|
| 1 | 01JAN| x |
| 1 | 03JAN| y |
Wanted Output
Table A
| ID | date | amount | details |
| 1 | 01JAN| 56 | x |
| 1 | 02JAN| 54 | x |
| 1 | 03JAN| 23 | y |
| 1 | 04JAN| 43 | y |
for the jan2 entry, the latest available details as of that date is 'x', for jan3 it is y
Thank you in advance for any guidance you could provide
This will work for the question you have asked literally:
data want;
retain details_last;
merge table1 table2;
by ID date;
if not missing(details) then details_last = details;
else details = details_last;
drop details_last;
run;
But this will only work if your data meets the conditions that you have presented like the date ranges in table B should always fall within the date ranges in table A and not outside (i.e. only interpolation, no extrapolation).
I am trying to perform a chi-square test on my data using SAS University Edition.
Here is the strucure of my data
+----------+------------+------------------+-------------------+
| study_id | Control_id | study_mortality | control_mortality |
+----------+------------+------------------|-------------------+
| 1 | 50 | Alive | Alive |
| 1 | 52 | Alive | Alive |
| 2 | 65 | Dead | Dead |
| 2 | 70 | Dead | Alive |
+----------+------------+------------------+-------------------+
I am getting different results when I do the test with SAS Vs when I do it manually using an online calculator. I used the values from 'PROC FREQ' to calculate the Chi-Sq using online calculator. Here are the outputs of frequencies and the Chi-sq test. Can someone point where the issue is.
proc freq data = mydata;
tables study_mortality control_mortality;
where type=1;
run;
+-----------------+-------------------+
| study_mortality | Frequency |
+-----------------+-------------------
| Alive | 7614 |
| Dead | 324 |
+-----------------+-------------------+
+----------------- +-------------------+
| control_mortality| Frequency |
+----------------- +-------------------
| Alive | 6922 |
| Dead | 159 |
+----------------- +-------------------+
proc freq data = mydata;
tables study_mortality*control_mortality/ CHISQ;
where type=1;
run;
+-----------------+-------------------+---------+-------+
| | Control_mortality | | |
+-----------------+-------------------+---------+-------+
| Study_mortality | Alive | Dead | Total |
| Alive | 5515 | 134 | 5649 |
| Dead | 249 | 5 | 254 |
| Total | 5764 | 139 | 5903 |
+-----------------+-------------------+---------+-------+
Statistic DF Value Prob
Chi-Square 1 0.1722 0.6782
Likelihood Ratio Chi-Square 1 0.1818 0.6699
Continuity Adj. Chi-Square 1 0.0414 0.8388
Mantel-Haenszel Chi-Square 1 0.1722 0.6782
Phi Coefficient -0.0054
Contingency Coefficient 0.0054
Cramer's V -0.0054
You have missing data. Look at the N's on those tables.
Study Mortality is around 8000 and Control Mortality is around 7000 but when you cross them you only have 5903 records. This means that certain records are excluded. There should be a line in the output saying N missing somewhere. Not sure if SAS didn't put it there or you only pasted selected output. The P value matches exactly when I use an online calculator and also match your output.
data have;
infile cards;
input Study Control N;
cards;
1 1 5515
1 0 134
0 1 249
0 0 5
;
run;
proc freq data=have;
table study*control / chisq;
weight N;
run;