# Need help choosing a statistical method/model

#### brittany

##### New Member
Hello,

I am currently doing a study on the defensive behavior of the European Grass Snake, and I was hoping someone could help me figure out which model to use to analyze my data.

I have 3 categories of dependent variables - 1) Pre-Capture Behavior 2) Post-Capture Behavior 3) Post-Release Behavior. Within these groups there are 7 different antipredator tactics that were measured (y/n)- these include Flee, Stay, DF, Writhe, Head Triangulation/Flattened Body, Hiss, and Strike.

**Note: At first I ranked these 7 behaviors upon 'intensity' - giving passive values a negative score and active values a positive score, and since snakes exhibited more than one behavior I added the values up for each category (Pre, Post, Release) and gave them a final behavioral score. However, I think it would be more insightful to rank each behavior as y/n (say, in a logistic regression) because there are many ways to rank the 'intensity' of behaviors in snakes and I think I could face issues of subjective influence when presenting my data in this way.**

I have a multitude of independent variables- Date, Time, Location, Temperature, Body Mass, SVL, Gender, Fed (y/n), Afflictions (y/n), Mating (y/n)... etc..

I have been reading many papers all of which seem to use a logistic regression as a common method, however none of them have the data organized into the 3 categories which they scored the behavior under...So I'm not sure if this is the best method.

What correlation matrix should I use? I was thinking Spearmans...And what type of statistical test should I use? Logistic Regression? Nested Anova? Any help would be great!

#### Karabiner

##### TS Contributor
Well, you could perhaps first tell us your research questions.

With kind regards

k.

#### bugman

##### Super Moderator
We have a some resource for this problem. you may contact any of the expert for the probability and statistics.
You are repeating posts to different problems. This is not helpful to the OP.