About sasnewbie12

sasnewbie12 · ‎12-03-2017

Just want to make sure, will observations that are missing a value for a variable that is not included in your model as a independant or dependant variable also be excluded?

sasnewbie12 · ‎12-02-2017

Dear all, I am running a multivariate logistic regression model assessing for occurrence of dependant event X (0-didn't occur 1-occurred) with about 200,00 weighted observations using survey data. I have multiple independant variables, (both continuous and a few categorical). Many of the independant variables are missing in about 5% of the data observations (the same 5% of observations are missing data). Will this make my conclusion inaccurate? I am not sure of how this will effect the overall model, and how it will effect the variables that do not have missing information. Please clarify if I can run the analysis, or will it cause a major issue. I would prefer to include those 5% of observations if possible, because they have information for some variables. Thank You

sasnewbie12 · ‎11-18-2017

Dear community, I am running a study over five years with survey data, and the weighted number of patients included is about 30 million in total. I will assess for a relationship between two variables. When does the number of observations become so large that everything starts to show significance (as I have heard)? I am subsetting the observations by a classification variable which includes about 20 subsets, and so the numbers will be smaller ultimately, but I would still like to know how I should interpret results with larger data in the millions, or does this issue happen when we go into the billions? Thanks

sasnewbie12 · ‎11-14-2017

proc surveyreg data=mydata; stratum str; cluster clstr; domain set; weight wt; model age=index; model height = index; model color = index; run; I ran the above statement. The log states: Multiple model statements. only the first model statement will be used.

sasnewbie12 · ‎11-13-2017

Hi When running proc survey means or proc survey freq, we can check multiple variable means/frequencies/chi squares by listing them out in the vars or tables statement. Proc Surveyfreq data=sample; cluster clstr; stratum str; weight wt; tables subset*color* (shape size weight number location)/ chisq; run; Is there anything similar I can do with a proc surveryreg or proc surveylogistic to run multiple univariate regression or logistic models by way of the same proc without having to write the proc again ? Thank you

sasnewbie12 · ‎11-13-2017

Thanks for the responses I think I should explain more clearly what I want to do, I may have not been clear before. I am replicating a study that was previously done with a different and more comprehensive dataset. This will be a cross-sectional study. We will look for cases of complication X that occurred during clinical operations A, B and C from a large data set of millions of cases. Then we will have to compare these cases of complication X with controls who underwent operations A, B and C but did not have complication X (from the same dataset). We will assess to which types of patients are more likely to have complication X during operations A, B and C. I can identify the cases. However, I am not sure how to go back and randomly select controls from the same population. Is Proc Surveyselect what I need? Thanks

sasnewbie12 · ‎11-13-2017

Hi, Using survey data, I am trying to compare patients who have a disease to a random number of equal controls from the same dataset who do not have the disease. I am assuming that I can select controls at random from the population, as I will use a multivariate analysis later on to asses for my outcomes, and I will control for age, gender, etc. at that time. I need to know what is the syntax for finding random observations from SAS survey data; furthermore, please clarify if I am ok in selecting random controls, or should I match by age and gender during selection of controls (if so, I will need the syntax for matching). Thank you

sasnewbie12 · ‎11-13-2017

Hi I am conducting a study comparing two treatments. What difference will it make if I use age in the multivariate analysis to control for any confounding effects age (<=18 or >18) will have versus doing two different studies (one in adult patients only and one in pediatrics patients only). Thank you

sasnewbie12 · ‎10-30-2017

Thanks for your inputs. Just to clarify, the variable names are unrelated and not in any kind of order. I know that we can do this with a macro or code; is there any way to do this quickly, I find myself coming across this issue frequently; if it's not 5000, I still may have a hundred variables and it doesn't look clean to have a long linear list within my code syntax.

sasnewbie12 · ‎10-30-2017

I have a long list of variables up to 5000. I want to include these in a sas proc. However, how can I paste these from word or excel into sas without having a long linear list where i have to scroll down for a long time to see. I would like to have it spread out over multiple rows (without having to manually go in and rearrange it). In other words, I want to make this: 1 2 3 4 5 6 7 8 into this: 1 2 3 4 5 6 7 8 so it can be easier to manage.

sasnewbie12 · ‎10-29-2017

This is also survey data. I don' t think there is any proc for PLS with survey data.

sasnewbie12 · ‎10-29-2017

I have run a huge logistic regression with about 900 independant variables in the model. All variable sin the model, including the dependant are binary 1 or 0. The log states that: WARNING: The information matrix is singular and thus the convergence is questionable. while also stating that: NOTE: Convergence criterion (GCONV=1E-8) satisfied. I am just using this model to identify potentially significant independant factors that predict the dependant outcome; I will then use those significant variables in further modeling with other covariates not included in this model. Therefore, do I have to fix this issue by potentially removing variables (perhaps there is collinearity?), or can I rely on the model? It would be difficult to try and pick and choose from 900 variables.

sasnewbie12 · ‎10-29-2017

Great, you guys solved it. The issues were: 1) using " " instead of ' ' in order to put the macro value inside of quotes. 2) not starting a variable name with numbers Shmuel, you put var before the variable name _&a; is it necessary to put var before adressing a variable? Seems it worked fine after I added the _

sasnewbie12 · ‎10-29-2017

Please elaborate how I should fix the syntax within parenthesis. I added a _ before the variable name (then _&a=1) and it created the variable. However, the '&a' within parenthesis is still not being read as 122. Thank you

sasnewbie12 · ‎10-29-2017

So its not reading the &a within ' ' . However, it needs to be within quotations because it is a categorical variable observation. How do I reconcile that?

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