Welcome to clinical data management program using SAS. In this video we will be discussing about the concept of preparing data. And our first topic that we will be dealing today is computing new columns, basically computing new variables in our data. So at first, you know that your prefers to access your data in your SAS environment or your forget your SAS datasets in SAS environment for that you have to run the live name statement. So the live name statement is first executed. This is lignum CD and we are given the path where our data sets are present.

So let's execute the live name statements. So these are the data sets we are going to use it in our session. So first, we are going to compute a new column. So we are going to deal with a data set called disease. So let me first open the data set for you all and show you all diseases A rated data set which we have worked before also, but just let me give you a quick recap of the data set. We are going to work with in our session.

So, this data set has got a number of observations we have got around 2000 observations and there are numerous number of variables like ID, gender, date of birth, zip code, employment status, education, marital status, children ancestry, average commute, daily interviews, available vehicles, military service and then the diseases that each patients are suffering from. So these IDs are basically patient IDs. Now, let us first set the objective Our objective is that we are going to calculate the age of different patients to see the data of both of the patients are given now we are going to calculate the age which is the difference between the date of birth that is given this data set and the current date. So let's do it. This total concept of computing columns will be done in DATA step. So we will be forming a dataset and output data set named disease for you can give any name to your output dataset.

We are forming the output data set inside work now it's up to you. Where do you want to create your output dataset you can create it either in your public library or in worklet. So data disease for business core is the name of our data set set CDM that the CDM is will have renamed CDM dot disease diseases may input data set which is located inside the CDM library. Now I'm going to calculate each age is equal to in I'm going to extract the initial component of the difference between the ages so that's why I've given the INT function, then the function which would be used to calculate the difference between the two years that function is your diff function, you will be using your diff function. My starting date first you have to give that is my deal of what my ending date will be the date, that is the current date, the current date is silent.

2018 You know that whenever we have to specify any date in SAS for any condition operators or for computing columns for any source of data manipulation, we generally use the date or we present the data in form of SAS date constant. To see how do we represent a date in form of sass date constant here we'll be writing the ending date that is the current date that is second August 2019. Again, this was zero to August, it was meant to be when we write B that means it says it constant. Next we have to give the basis basis means on what base this year difference will be calculated. There are a number of types of bases like act way act, act with 360 activate 365 30 by 360. But we are going to take a look at vi F stands for actual by actual because that will consider 365 days as well.

Oh euros as well as 366 days or you will be taking app by app basis, then let's close the brackets you have to use a semicolon after every statement and run. So now let's run the code. So let's check on what library your disease for will be covered in Rob library. See, this is your data book. So let's scroll towards the right side. So this is the age so these are the age of the patients.

So in this way, you can compute a new column here h was a new column that we have computed using the year difference function and we have also used the INT function to extract the individual component from the year difference because when we are calculating your difference, we will be displaying the values in decimal points, but we only want the integer part of our year difference. That's where we have used the function in so This video we'll be doing till here. In my next video we'll be starting with condition processing. Thank you Goodbye and see you all for the next video.