Welcome to clinical data management programs using SAS In this video we will be discussing about how to create frequency reports. So we will be using the procedure called proc freak that is proc freak data equals CDM is my library name we'll be using the same data set that is disease which is located in the CDM library I have access I have peignoir disease data set by executing Millenium statement and then run proc freak generates the frequency distribution table for any data set. So as many variables are there in the data set the frequency distribution table for all the variables precedent that data set will be displayed in the result viewer or it will be displayed in our report. So let's run this code. So this is my frequency report. As many variables are there in the disease data set those number of frequency tables the frequency distribution table will be displayed.

So, this is a frequency table the frequency response distribution table is described with respect to ID then with respect to date of birth average commute that is with respect to all the variables that is there in the disease data set. Now, we are we are going to filter that is in my frequency distribution report I do not want all the variables in my report I do not want a frequency table with respect to all the variables I want to filter. So, I will be specifying that which variables are with respect to which variables the frequency table should be displayed. So, for that again the same procedure will be using a dystrophic data equals to CDM dot disease tables tables is a keyword to specify that with respect to which variable the frequency input should be displayed. So, I have given tables disease that I want to frequency table with respect to the disease variable and then run.

So, let's run this code So, this is the frequency procedure for the frequency table with respect to the disease column you got the frequency and it is the individual frequency of each of the diseases the percent the frequency percent the cumulative frequency that is the cumulative total of the frequency content the cumulative percentage is the cumulative total of the frequency percent these all these columns are displayed for all the frequency tables that you generate. To see in a previous report also when I did the frequency table I was the same columns. Here the frequency is coming as one because every patient there is only one patient, the patient IDs are not repeated. That's why the frequency mostly is one you are getting these four columns there is a frequency frequency percent curative frequency interpretive percent. The next thing another type of frequency procedure that we will be doing is we'll be using the concept of excellence that is profit free data equals CDM dot disease we are going to use the keyword called n levels and levels is a keyword which is mostly applicable when your variable is categorical in nature.

So, how many categories of the variable is there that will be displayed tables will be disease as I know disease is a categorical variable. And then you can use any level with any sorts of variable but it is mostly applicable it is mostly useful if you use it with respect to a categorical variable. So, use the concept of n levels that is number of levels the number of categories there in that particular variable a number of unique values there in particular variable and tables disease means I want to display the frequency table with respect to the variable disease. And then I'm using the same procedure called property data. To see the number of levels over here is 13. That is in my data.

I've got 14 sorts of diseases that is Alzheimer's disease, HIV or AIDS breast cancer. Diabetes, endometriosis, gastritis heart disease hypertension kidney disease, multiple sclerosis prostate cancer histories of rhenium in gas So, these are the types of research these are the 13 types of diseases that are there in my data and with respect to these diseases I got the frequency table also that is a frequency frequency percent cumulative frequency and now I'll show you how to do cross frequency tabulation. So for this again we are going to use the proc click procedure. There is profit data equals CDM dot disease tables disease. Start gender when we write disease or gender This is used to display across frequencies. And then this was the cross frequency table between disease and gender from the CDM disease data set that is run this code chiama diseases in the rows and the gender is main main column the four values that waters first is a frequency that is there are 162 patients female patients who are suffering from Alzheimer's diseases the frequency percent is 8.10%.

So, out of the total number of patients that that are there 8.19% are suffering from Alzheimer's diseases represent row percent is 47.79 that is this that is out of the 339 patients who are suffering from Alzheimer's disease 47.7% are female and column percentage out of 975 female patients 16.62% that there was suffering from Alzheimer's disease. So, these are the interpretations This is the frequency This is a frequency percent these are the this is row percent and this is column percent. These are the interpretations of frequency frequency percent row percent and column percent frequencies the individual column This is the frequency percent row percenters that is out of a proposal is only 47 cents. That is out of the 339 patients who are suffering from us Davis disease focusing on 70% of female and column percenters out of 975 female patients 16.62% is suffering from Alzheimer's disease This is the concept of cross tabulation here I have displayed all the four values frequency frequency to zero percent column percent.

Suppose if you only want the frequency and you do not want the row or column and the percentage then how will you do it? We'll be using the same procedure that is prop free data equals CDM dot disease tables disease start gender now we'll be using the key word called neuro because we do not hundred percent know call because we do not want to call them percent no percent because we do not want frequency descent. And then, huh so let's run this code. Seeing only the frequencies displayed rows in column percent and frequency percent all got removed because we have used the key word no roll call and no percentage. Now we'll be using the concept of cross lists this cross tabulation frequency report will be displayed in a different format or a different way. We'll be using the same procedure called property data equals CDM.

Dot disease tables. Disease start gender showing cross tabulation slash processed. processes the key word This is going to be use to display the same customer ID report will be displayed but in a different format. My frequency if you can see the zero percent column percent the block was shown before who here here it was shown this was me actually report before in this way this was me actually last updated report. Now when I do cross test the format of this presentation changes. So this is my frequency, mid frequency percent this is zero percent and this is a column I get the same values which I was getting before see 162 8.101 0.79 60.6 I was getting it vertically but now I'm getting it presently.

So this is about my frequency report. This is how you generate different sorts of frequency reports. So in this video we'll be doing till here. In my next video I'll be discussing about creating summary statistics reports. Thank you. Good advice you are for the next week.