Start Page     
Methodology     
Lexicon / Basics     
Personality Scales     

RL Demographics     
Game Demographics     
Meta-Game     
Meta-Character     
Relationships     
In-Game Dynamics     
Guilds
     
Gender-Bending     
Romantic Partner     
Parent / Child     
Men and Women      
Growth and Change     
What About ... ?     
Addiction     
Virtual Skinner Box     

      Download PDF     
Related Studies     
Recent Findings     
About Me     

More recent findings     
can be found at     
the Daedalus Project     




Quicklinks:

Overview
Participant Recruitment
Exclusion Criteria
On Representativeness

Overview

This project propelled itself in one-month cycles. Each phase involved gathering both quantitative and qualitative data pertaining to questions generated from the previous phase, analyzing the data, and thengenerating new paths to explore in the next phase. Each phase usually consisted of about 4 questionnaires focused on different aspects of the game. Data from different phases was linked using a participant's email address so that important data, such as a participant's scores on a set of personality scale, need only be gathered once. More importantly, data gathered separately could be analyzed together. The resulting database of information is useful because it allows access to both the big numerical picture and individual qualitative responses. Participants were encouraged to complete as many questionnaires as they felt comfortable doing, and the underlying database structure was described to them briefly so that they understood their continued participation was important.


Participant Recruitment

Participants were recruited over the Internet for this project. At the beginning of each phase, participants already in the database were invited to participate in the new phase through email. At the same time, a standardized message was posted in online message boards and forums that are frequented by EverQuest players.

Participants were also encouraged to tell their fellow EverQuest gamers about the project and to spread the link to the project main page. It is not known however whether this helped with recruitment significantly.

This project collected data from 5 phases in the period between September 5th 2000 and May 5th 2001. These included 13 multiple-choice forms, 7 free-response forms, and 3 Flash-implemented experimental designs. Approximately 4000 individuals participated in the study, and filled out about 25,000 forms altogether. These estimates are generated after the exclusion criteria have been applied. Most multiple-choice forms had at least 1500 responses. There was a participant carry-over rate of about 25% from one phase to the next.


Exclusion Criteria

Below are the criteria used for excluding submissions from the analysis:

--Blank submission
--Duplicated/Repeated submission, by comparing the email address field
--Submission with missing email address field, even if all other fields are completed
--Submission with more than 20% of fields left blank
--Submission with obviously impossible information, ie. age=2, email=anon@anon.com


On Representativeness

Sampling biases and representativeness are important issues to consider in any kind of empirical research. In the months since the first release of this report, I have noticed concerns about representativeness surfacing in several message boards which linked to this study, and also in several email correspondences. One individual presented a well-articulated critique of the representativeness of my sample:

When referring to the results of your study, you say "x% of EQ players are <blank>". However, in reading your methodology, I notice that your study does not choose EQ players via a random sampling method. Instead, you primarily rely on EQ websites and to a lesser extent word of mouth to find your study's participants.

It seems to me that this skews the data heavily in favor of the most devoted EQ players. The casual EQ population who don't bother to read EQ websites will be almost entirely overlooked in your data, even though I'm sure they represent a significant portion of the EQ population. Also, by using the volunteer method to get your participants, you automatically filter out all the EQ players who don't bother to fill out surveys.

Thus I find it odd to derive from your study any implications about the EQ populous as a whole. So the phrase "x% of EQ players" simply doesn't apply; rather, your results reflect "x% of EQ players who read EQ websites and who like to fill out surveys". There are probably some big differences between those two statements.

I would answer this particular critique and similar ones with the following arguments:

1) EQ is one of the few games where going to these websites will help a lot, to the extent where a lot of casual gamers probably frequent these sites as well. For example, consider scheduled server downtime, quest info, class strategies etc. So it's not clear whether this creates a heavy skew at all. In fact, since playing the game necessitates a connection to the Internet on a decent computer, it is probably only a tiny percentage of players who have never gone to an EQ website.

2) Through a correspondence with Sony Online/Verant, I found that my basic demographics match theirs very closely. For example, the percentage of players who are female was 16% for both our data. And average playtime per week was "around 20" for them and mine was 22.

3) Gender and age differences probably don't interact with whether someone goes to an EQ website or not. So we know that female players are more likely to feel that their EQ friendships are comparable to their RL friendships, but this difference probably doesn't only occur among people who go to EQ websites. And in a sense, these age and gender differences are the more important part of the study.

4) And the same for people who don't bother to fill out surveys. They probably don't differ in important ways from people who fill out surveys, in the sense that almost all of the findings would remain the same even if we did somehow take them into account.

5) Finally, since "hours played per week" was one of the collected variables, I can check whether this impacts the other variables I am measuring. So even if my sampling included a very skewed proportion of heavily-devoted EQ players, I am not oblivious to the effects of this skew. On the contrary, I have a good way of determining how severe these effects are.

In essence, I feel that most EQ gamers frequent EQ websites, and that a non-random sampling of these gamers who go to websites does a good enough, though clearly not perfect, job of representing the entire EQ player population. And that while slight skews do exist, that my findings would not differ significantly from a study that was able to take random samples.