I have a data set that looks like below. I have to find if the scores are different across the four days. I understand I need to run a Two Way ANOVA for this test. I'm quite new to SAS if anyone could help me how to go about this? Should I be rearranging my data?
Yes you can use PROC TRANSPOSE
proc transpose out=...;
by player;
var round:;
run;
Related
I am analyzing a temporal trend(yr) of certain chemicals(a b & c).
I use proc sgplot and series statement to draw a plot and found there was a decreasing trend.
Becuase the data is right-skewed, I used the median concentration of each year to draw the plot.
Now I would like to conduct a statistical test on the trend. My data came from the NHANES and need to use the proc survey** to perform analysis. I know I can do an ANOVA test based on proc surveyreg and use ANOVA option in the MODELstatement.
proc suveyreg data=a;
stratum stra;
cluster clus;
weight wt;
model a=yr/anova;
run;
But since the original data is right-skewed, I think maybe it is better to use Kruskal-Wallis test on the original data. But I don't know how to write a code in SAS and I didn't find information in proc survey**-related document.
My plan B is to use the log-transformed data and ANOVA test. But I am not sure if that is an appropriate approach. Can somebody tell me how to get the normality test of the residual in ANOVA while using proc surveyreg? I would also like to know if I can test a b & c in one procedure or I should write multiple procedures with changes in MODEL statement.
Looking forward to your engagement.Thank you!
Proc MI is used to impute missing values in a SAS dataset. Is there a way to obtain a SAS code from Proc MI procedure, so that we can score datasets with missing value without having to use Proc MI procedure? This is needed so that dataset in production environment can be score consistently. I dont want to use Proc MI in production environment.
Thanks!
I don't believe this is possible, at least not in the way that it is for proc import. If you want to use a purely deterministic imputation algorithm, you will need to write your own data step to do it.
I don't know how complicated your data set is, but if you score a data set that covers all the possibilities you will see in the production data, then you can use your scored data set as a lookup table for the production data.
I'm sorry if I'm asking a stupid question, I have some experience in R and am just starting to learn SAS. In enterprise guide I'm trying to compute a correlation matrix (cramv only) for categorical variables. The problem is that explanatory variables are on dataset1 while my objective variable is on dataset2. I cannot append the obj var column to dataset one for external reasons.
Is there a way to perform the procedure without having to create another dataset?
Thank you in advance!
this is how I imagine it would work out:
ods output ChiSq=CRAMV;
%put &charvar;
proc freq
data= dataset1 dataset2
tables (&charvar) * (objvar) / chisq;
run;
SAS procedures only operate against a single dataset or view. If you didn't want to create another dataset then you could create a view that appends the objvar column to dataset one.
Creating a view can be done with either proc sql; create view x as... or in a data step, data x / view=x...
I want to split by large dataset randomly into two new dataset in the ratio of 70% - 30%.
Basically I need to allocate 70% of random values from large dataset to the newdataset1 and 30% of the random values from largedataset to the newdataset2.
Can you please help with a SAS code that will help me achieve it.
A dummy code will really help..
Proc SQl or SAS statement. Anything will work with me.
For complex sample design (like stratified randomization, e. g.) PROC SURVEYSELECT is a way to go, as #Keith said.
But for just a simple random splitting RANTBL-function will do the trick:
data newdataset1 newdataset2;
set have;
flag=rantbl(-1, 0.7, 0.3);
if flag=1 then output newdataset1;
else output newdataset2;
run;
I'm totally new to SAS so please be patient. :) I have a Data Job that is producing two data sets that contain a field. I need to compare these two data sets and then output only the rows that do not match, but I'm struggling. Is there a way to accomplish this in SAS? I've tried using "Match Codes", but I couldn't get that to work. I also tried "Cluster Diff", but that didn't work either.
What we have been doing is running two SQL queries and then comparing them in Excel and taking the records that do not match.
Any suggestions would be greatly appreciated.
You need to use PROC COMPARE for this kind of task.
proc compare base=<main dataset> compare=<other dataset> outdif out=<output dataset>;
by <id variables?>;
var <variables to compare, or leave this off for all variables>;
run;
That's the basic structure; read the documentation for more details.
You could do this in the datastep using merge. The below will give you anything in dataset_A that is not in dataset_B
data output_dataset;
merge dataset_A (in=a)
dataset_B (in=b)
;
by <variable>;
if a and not b;
run;