I'm trying to export quartile information on a grouped dataset as a dataset in SAS but when I run this code my output is a table with the correct information displayed but the dataset WORK.TOP_1O_PERC is only summary statistics of the set (no quartiles). Does anyone know how I can export this as the CLASS (PDX) and its 25th and 75th percentiles? Thanks!
PROC MEANS DATA=WORK.TOP_10_DX P25 P75;
CLASS PDX;
VAR AmtPaid;
OUTPUT OUT = WORK.TOP_10_PERC;
RUN;
I like the STACKODS output that is a data set which is like the default printed output.
proc means data=sashelp.class n p25 p75 stackods;
ods output summary=summary;
run;
proc print;
run;
You can use output statement with <statistics>= options.
PROC MEANS DATA=WORK.TOP_10_DX NOPRINT;
CLASS PDX;
VAR AmtPaid;
OUTPUT OUT = WORK.TOP_10_PERC P25=P25 P75=P75;
RUN;
Compared to ods output, output statement is much faster but less flexible with multiple analysis variables or by statement specified situation.
Related
I have run a regression on a data set. I would like to then add the predicted values into the original data set table. I would like the PredictedMS_Diff values to be added to the PROPreg_CSR_final dataset.
proc reg data=PROPreg_CSR_final outest=outest_model_1 covout plots=diagnostics(stats=(default aic
sbc));
title "CSR Final";
FinalCSR:MODEL MS_Diff_CSR=Rank_Delta_prop;
Output PREDICTED=PredictedMS_Diff
run;
title;
Your output statement does not have an OUT= option so the data set is named by SAS. Also missing a semicolon.
Output PREDICTED=PredictedMS_Diff
If that has worked it would have been a copy of the input data with PredictedMS_Diff added.
proc reg data=sashelp.class;
model weight=height;
output out=pred predicted=p residual=r;
run;
I have approximately 1,000,000 rows and 25 columns of data and I'm trying to return a list of column names, the number of distinct values and whether there are missing values.
I am not able to directly code in column names in PROC SQL and count distinct as I have numerous data sets with different column names and I'm trying to automatically return the desired outcome for all tables with one piece of code.
I've tried running the following code
proc freq nlevels data= &DATASET_NAME;
ods output nlevels=nlevels ;
tables _all_ NOPRINT;
run;
This returns an out of memory error. Is there another way to achieve the result, avoiding the out of memory error.
It is unnecessary to input column name by table _all_, but it possibly makes out of memory by inputting all columns at the same time, try to separate column to do proc freq and then combine results:
proc sql;
create table name as
select name from dictionary.columns where libname='SASHELP' and memname='CLASS';
quit;
data want;
run;
data _null_;
set name;
call execute(
'proc freq data=class nlevels;
table '||name||';
ods output nlevels=nlevels;
run;
data want;
set want nlevels;
run;'
);
run;
This question is very similar to SAS summary statistic from a dataset
The answers cover techniques for
transpose + freq
hash
freq w/ ODS exclude+output
I have the following problem. I need to run PROC FREQ on multiple variables, but I want the output to all be on the same table. Currently, a PROC FREQ statement with something like TABLES ERstatus Age Race, InsuranceStatus; will calculate frequencies for each variable and print them all on separate tables. I just want the data on ONE table.
Any help would be appreciated. Thanks!
P.S. I tried using PROC TABULATE, but it didn't not calculate N correctly, so I'm not sure what I did wrong. Here is my code for PROC TABULATE. My variables are all categorical, so I just need to know N and percentages.
PROC TABULATE DATA = BCanalysis;
CLASS ERstatus PRstatus Race TumorStage InsuranceStatus;
TABLE (ERstatus PRstatus Race TumorStage) * (N COLPCTN), InsuranceStatus;
RUN;
The above code does not return the correct frequencies based on InsuranceStatus where 0 = insured and 1 = uninsured, but PROC FREQ does. Also doesn't calculate correctly with ROWPCTN. So any way that I can get PROC FREQ to calculate multiple variables on one table, or PROC TABULATE to return the correct frequencies, would be appreciated.
Here is a nice image of my output in a simplified analysis of only ERstatus and InsuranceStatus. You can see that PROC FREQ returns 204 people with an ERstatus of 1 and InsuranceStatus of 1. That's correct. The values in PROC TABULATE are not.
OUTPUT
I'll answer this separately as this is answering the other possible interpretation of the question; when it's clarified I'll delete one or the other.
If you want this in a single printed table, then you either need to use proc tabulate or you need to normalize your data - meaning put it in the form of variable | value. PROC FREQ is not capable of doing multiple one-way frequencies in a single table.
For PROC TABULATE, likely your issue is missing data. Any variable that is on the class statement will be checked for missingness, and if any rows are missing data for any of the class variables, those rows are entirely excluded from the tabulation for all variables.
You can override this by adding the missing option on the class statement, or in the table statement, or in the proc tabulate statement. So:
PROC TABULATE DATA = BCanalysis;
CLASS ERstatus PRstatus Race TumorStage InsuranceStatus/missing;
TABLE (ERstatus PRstatus Race TumorStage) * (N COLPCTN), InsuranceStatus;
RUN;
This will result in a slightly different appearance than on your table, though, as it will include the missing rows in places you probably do not want them, and they'll be factored against the colpctn when again you probably don't want them.
Typically some manipulation is then necessary; the easiest is to normalize your data and then run a tabulation (using PROC TABULATE or PROC FREQ, whichever is more appropriate; TABULATE has better percentaging options though) against that normalized dataset.
Let's say we have this:
data class;
set sashelp.class;
if _n_=5 then call missing(age);
if _n_=3 then call missing(sex);
run;
And we want these two tables in one table.
proc freq data=class;
tables age sex;
run;
If we do this:
proc tabulate data=class;
class age sex;
tables (age sex),(N colpctn);
run;
Then we get an N=17 total for both subtables - that's not what we want, we want N=18. Then we can do:
proc tabulate data=class;
class age sex/missing;
tables (age sex),(N colpctn);
run;
But that's not quite right either; I want F to have 8/18 = 44.44% and M 10/18 = 55.55%, not 42% and 53% with 5% allocated to the missing row.
The way I do this is to normalize the data. This means you get a dataset with 2 variables, varname and val, or whatever makes sense for your data, plus whatever identifier/demographic/whatnot variables you might have. val has to be character unless all of your values are numeric.
So for example here I normalize class with age and sex variables. I don't keep any identifiers, but you certainly could in your data, I imagine InsuranceStatus would be kept there if I understand what you're doing in that table. Once I have the normalized table, I just use those two variables, and carefully construct a denominator definition in proc tabulate to have the right basis for my pctn value. It's not quite the same as the single table before - the variable name is in its own column, not on top of the list of values - but honestly that looks better in my opinion.
data class_norm;
set class;
length val $2;
varname='age';
val=put(age,2. -l);
if not missing(age) then output;
varname='sex';
val=sex;
if not missing(sex) then output;
keep varname val;
run;
proc tabulate data=class_norm;
class varname val;
tables varname=' '*val=' ',n pctn<val>;
run;
If you want something better than this, you'll probably have to construct it in proc report. That gives you the most flexibility, but is the most onerous to program in also.
You can use ODS OUTPUT to get all of the PROC FREQ output to one dataset.
ods output onewayfreqs=class_freqs;
proc freq data=sashelp.class;
tables age sex;
run;
ods output close;
or
ods output crosstabfreqs=class_tabs;
proc freq data=sashelp.class;
tables sex*(height weight);
run;
ods output close;
Crosstabfreqs is the name of the cross-tab output, while one-way frequencies are onewayfreqs. You can use ods trace to find out the name if you forget it.
You may (probably will) still need to manipulate this dataset some to get the structure you want ultimately.
I have the following statement
Proc Freq data =test;
tables gender;
run;
I want this to generate an output based on a condition applied to the gender variable. For example - if count of gender greater than 2 then output.
How can I do this in SAS?
Thanks
If you mean an output dataset, you can put a where clause directly in the output dataset options.
Proc Freq data =sashelp.class;
tables sex/out=sex_freq(where=(count>9));
run;
I'm not aware of how you can accomplish this only using proc freq but you can redirect the output to a data set and then print the results.
proc freq data=test;
tables gender / noprint out=tmp;
run;
proc print data=tmp;
where count > 2;
run;
Alternatively you could use proc summary, but this still requires two steps.
proc summary data=test nway;
class gender;
output out=tmp(where=(_freq_ > 2));
run;
proc print data=tmp;
run;
I want to calculate the 95th percentile of a distribution. I think I cannot use proc means because I need the value, while the output of proc means is a table. I have to use the percentile to filter the dataset and create another dataset with only the observations greater than the percentile.
Clearly I don't want to use the numeric value..because I want to use it in a macro.
Don't put summary statistics into macro variables. You risk loss of precision.
This is based on your cryptic description of the problem.
proc means...
output out=pct95 pct95=
run;
data subset;
if _n_ eq 1 then set pct95;
set data;
if value < pct95;
run;
You can suppress proc means from outputting your results in a new tab using the noprint option. Try this:
proc means data = your_data noprint;
var variable_name;
output out = your_data2 p95= / autoname;
run;