Welcome to clinical data management program using SAS In this video we will be discussing about one way ANOVA. Now, what is one way ANOVA a one way ANOVA is a technique where we use one continuous variable in one categorical variable and the categorical variable has got more than two categories or more than two levels. And we basically use this technique to check whether the means of the continuous variable which we are taking whether they are same across all the levels of the categorical variable or not. And for this we use F distribution or F test. So one way ANOVA requires one continuous variable in one categorical variable. The categorical variable must have more than two categories or more than two levels using one way ANOVA we check that whether the means of the continuous variable are the means the same across all groups or not all groups means all the levels are not so far one way ANOVA is a technique that can be used to compare means of Two or more samples.

So, for this we use the F distribution, the hypothesis one way ANOVA is h notice there is no difference in the means among the groups H naught is no difference in the means and each one is there is a difference in the means. Now let's move to the case study 100 and over that is the case study that we are going to do using SAS to explain one way ANOVA so it's a case study the case studies the Hamilton anxiety rating scale that is how is given for different patients suffering from anxiety now we have to check that among different dosage of medicines given to patients for anxiety so anxiety dosages high, medium or low. This is a categorical variable, whether mean changes or not. So how am i is my continuous variable hammer rating and my categorical variable over here is the dosage group. There are three groups that is high, medium, or low.

So now let's move to SAS. And let's do this the solve this case study using one way ANOVA. Let's first know how to proceed with one way ANOVA. First, we have to get our data sets into SAS. For that we To create a live name statement so we'll do live name CDM will give double quotes will give the path here are my data sets which are present. Let's run the librium statement.

These are my data sets now let's run and Werner will be using the procedure called proc ANOVA that is proc ANOVA data equals CDM dot dat God is my data set that we are going to use before I run the code first let me show you another data set this is the get data set which consists of rotation number or you can see patient ID This is the dosage group that is low elements low HIV is high and me demons medium and this is hammer. It is Hamilton scape for anxiety proc and our data equals to CDM dot Gad Then we'll mention or specify the class statement in the class statement we'll be mentioning a categorical variable our categorical variable is the variable name then model my dependent variable is hammer. So dependent variable will mean the alleges the dependent variable equals to the independent variable.

That is those good. And then so let's run this code. Before I run the code at explaining all the code it is like proc ANOVA data equals two CDM my library name dot gadot Veritas admin class those group those group is my categorical variable model hammer hammer is my dependent variable and those groups and other categorical variable that is the independent variable and then let's run this code to see we have to see the p value as we know that we do f test for an alarm a p value is 0.00 to three that means I will be rejecting my null hypothesis that means the me hammer for all the groups that is high high doses group patients and low dosage group patients that medium dosage group patients, the Nina hammer, or the mean Hamilton Rita Hamilton rating scale for anxiety for the high dosage group patients and low doses to patients and medium doses for patients are not seen.

There is a difference because my I have to reject my null hypothesis as my P value is less than the level of significance. Which is 0.05 I will reject my null hypothesis. And therefore, I will accept the alternative hypothesis and the alternative hypothesis is that there is a significant difference between the means among the groups. That is there is a significant difference between however, or there is significant difference of hammer or Hamilton ratings for anxiety among the three doses group of individuals that is high, medium and low dosage group of made individuals So, there is a difference. So, this is the concept of your one way ANOVA So, we'll be doing here and we'll be ending this video over here in my common video at explaining you all the concept of two way ANOVA Thank you. Goodbye.

See you for the next video.