About stat_sas

stat_sas · ‎09-10-2014

Try this. data WANT; set Data; M1=input(InterestFrequency,8.); M2=input(MaturityDate,date9.); M3=input(FirstCpnDt,date9.); run;

stat_sas · ‎09-10-2014

data have; input Date $ Id $ machine $; datalines; 08/01/14 G A1 08/01/14 B A2 08/01/14 L A3 08/01/14 G A4 08/01/14 B A5 08/01/14 G A6 ; proc tabulate data=have; class date id machine; table date,id=' '*n=' '; run;

stat_sas · ‎09-10-2014

I think you have to adjust your sample counts based on census data. If you are taking gender and age_group as startification factors then use somthing like this. if gender='M' and age_group='18-25' then wt=1.2; if gender='F' and age_group='18-25' then wt=1.3; wt is the weight variable

stat_sas · ‎09-10-2014

For this you have to calculate your weight variable depending on stratification factors.

stat_sas · ‎09-10-2014

Use proc contents to check variable types. if ac.invoice_number is char then try this. ON input(ac.invoice_number,8.) = ATSo.odr_number ;

stat_sas · ‎09-10-2014

Hi, There are few things that might be helpful in your design. 1. If your variables have lot of missing values let us 50% or more then it's better to drop those variable for further analysis. We can't generalize all the time that missing will always be 'No'. 2. Not sure what do you mean by drop missing values using impute node.? 3. After oversampling you will have a clustered data based on your target variable. You can perform cluster analysis for two clusters solution based on independent variables and correlate target and non-target customers within each cluster. This will give you an idea how significant are the independent variables in clustering target and non- target customers.

stat_sas · ‎09-09-2014

Are you putting obstats in model options? MODEL Y=X / D=B OBSTATS;

stat_sas · ‎09-09-2014

proc sql; create table want as select * from have group by grp having count(distinct type)=3 or type ne 'All' order by grp, type; quit; proc print data=want; run;

stat_sas · ‎09-09-2014

Hi, You need to use ods with obstats option something liket this. ods output obstats=obstats; PROC GENMOD DATA=have; MODEL Y=X / D=B OBSTATS; RUN; proc print data=obstats; run;

stat_sas · ‎09-09-2014

Not sure, If you can share some data then it would be more clear.

stat_sas · ‎09-09-2014

data want(keep=x1-x5); set have; array x{*} x1-x5; sum_neg=0; sum_pos=0; do i=1 to dim(x); if x{i}<0 then sum_neg+x{i}; else sum_pos+x{i}; if x{i}<0 then x{i}=0; end; do i=1 to dim(x); x{i} = x{i} + sum_neg*x{i}/sum_Pos; end; run;

stat_sas · ‎09-09-2014

If I understand it correctly you are looking for a cross tab like this data have; input var1 $ var2; datalines; a 1 b 2 c 3 ; proc freq data=have; table var1*var2/nocol norow nopercent ; run;

stat_sas · ‎09-09-2014

If you are looking for correlation of one variable with remaining variables. This may be helpful. proc corr data=have; var checking saving mortgage credit_card; run;

stat_sas · ‎09-08-2014

data want; set have(in=a) have(in=b); if b then var2=var3; drop var3; run;

stat_sas · ‎09-08-2014

You have no observation for letters='E' in your dataset. Where clause in proc tabulate will return nothing.

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