I have survey data about injuries occurring to athletes over the span of their careers. Many of the athletes suffered multiple injuries (the most any athlete reported was five and this did not occur very often). While I can see that injuries within an athlete may be dependent on a previous injury, in the data, many within-athlete injuries involved different body parts with different mechanisms and types, occurring years apart.

My interest is in the characteristics of the injury itself not the athlete. I am looking to see if any one particular mechanism of injury was prevalent in the sport. And with that information, look at possible modifications to the equipment or rules to improve the safety.

I used a Pearson Chi square test to see if Anatomical site of injury was distributed evenly across mechanism of injury (e.g. contact with opponent, quick turn, etc.); and the type of injury (e.g., strain, sprain, etc.) across mechanism, too.

My original intent for this data was to present descriptives and some graphs contrasting the different mechanisms and the parts injured or the types of injury, however, I was asked by a reviewer to perform some statistical analyses to show that, for example, shoulder strains occurred more frequently than shoulder lacerations.

Now I have a concern about the independence of the observations. Since I'm looking at injury level variables and each injury is only included once in each analysis, I don't think I'm violating that assumption despite several athletes being in the analysis multiple times. Is this correct? Or do I have to worry about independence.

There are a number of pieces of equipment that can be modified and this will be the next project once "high risk" equipment is identified. With this project I was hoping to get evidence that would justify targeting those pieces of equipment with some data that reflect higher injury rates when using specific equipment and thus avoid altering equipment that did not have a high incidence of injury associated with it.

Thoughts and advice appreciated.

-John

I have survey data about injuries occurring to athletes over the span of their careers. Many of the athletes suffered multiple injuries (the most any athlete reported was five and this did not occur very often). While I can see that injuries within an athlete may be dependent on a previous injury, in the data, many within-athlete injuries involved different body parts with different mechanisms and types, occurring years apart.

My interest is in the characteristics of the injury itself not the athlete. I am looking to see if any one particular mechanism of injury was prevalent in the sport. And with that information, look at possible modifications to the equipment or rules to improve the safety.

I used a Pearson Chi square test to see if Anatomical site of injury was distributed evenly across mechanism of injury (e.g. contact with opponent, quick turn, etc.); and the type of injury (e.g., strain, sprain, etc.) across mechanism, too.

My original intent for this data was to present descriptives and some graphs contrasting the different mechanisms and the parts injured or the types of injury, however, I was asked by a reviewer to perform some statistical analyses to show that, for example, shoulder strains occurred more frequently than shoulder lacerations.

Now I have a concern about the independence of the observations. Since I'm looking at injury level variables and each injury is only included once in each analysis, I don't think I'm violating that assumption despite several athletes being in the analysis multiple times. Is this correct? Or do I have to worry about independence.

There are a number of pieces of equipment that can be modified and this will be the next project once "high risk" equipment is identified. With this project I was hoping to get evidence that would justify targeting those pieces of equipment with some data that reflect higher injury rates when using specific equipment and thus avoid altering equipment that did not have a high incidence of injury associated with it.

Thoughts and advice appreciated.

I have survey data about injuries occurring to athletes over the span of their careers. Many of the athletes suffered multiple injuries. My interest is in the injury itself. I used a Pearson Chi square test to see if Anatomical site of injury was distributed evenly across mechanism of injury (e.g. contact with opponent, quick turn, etc.); and the type of injury (e.g., strain, sprain, etc.) across mechanism, too.

Now I have a concern about the independence of the observations. Since I'm looking at injury level variables and each injury is only included once in each analysis, I don't think I'm violating that assumption despite several athletes being in the analysis multiple times. Is this correct? Or do I have to worry about independence.

Any thoughts or advice is appreciated.

-John

I have survey data about injuries occurring to athletes over the span of their careers. Many of the athletes suffered multiple injuries (the most any athlete reported was five and this did not occur very often). While I can see that injuries within an athlete may be dependent on a previous injury, in the data, many within-athlete injuries involved different body parts with different mechanisms and types, occurring years apart. 

My interest is in the characteristics of the injury itself not the athlete. I am looking to see if any one particular mechanism of injury was prevalent in the sport. And with that information, look at possible modifications to the equipment or rules to improve the safety. 

I used a Pearson Chi square test to see if Anatomical site of injury was distributed evenly across mechanism of injury (e.g. contact with opponent, quick turn, etc.); and the type of injury (e.g., strain, sprain, etc.) across mechanism, too.

My original intent for this data was to present descriptives and some graphs contrasting the different mechanisms and the parts injured or the types of injury, however, I was asked by a reviewer to perform some statistical analyses to show that, for example, shoulder strains occurred more frequently than shoulder lacerations.

Now I have a concern about the independence of the observations. Since I'm looking at injury level variables and each injury is only included once in each analysis, I don't think I'm violating that assumption despite several athletes being in the analysis multiple times. Is this correct? Or do I have to worry about independence.

There are a number of pieces of equipment that can be modified and this will be the next project once "high risk" equipment is identified. With this project I was hoping to get evidence that would justify targeting those pieces of equipment with some data that reflect higher injury rates when using specific equipment and thus avoid altering equipment that did not have a high incidence of injury associated with it.

Thoughts and advice appreciated.

-John