#5190 | AsPredicted

As Predicted:Ultimate Ref-Friz Frames (#5190)

Created:       08/18/2017 07:21 AM (PT)

This is an anonymized version of the pre-registration.  It was created by the author(s) to use during peer-review.
A non-anonymized version (containing author names) should be made available by the authors when the work it supports is made public.

1) Have any data been collected for this study already?
No, no data have been collected for this study yet

2) What's the main question being asked or hypothesis being tested in this study?
We will test the hypothesis that individual differences in preference for reference frames is common across domains. To test this hypothesis, we will conduct an online study in which participants who are familiar with the sport ultimate frisbee will complete two sets of tasks. For both tasks, they will respond as quickly and accurately as possible to indicate a direction (right or left). Schematic images and stick figures will be used to show the environment. The stick figure can be facing "toward" the participant or away. In the ultimate frisbee task, they will respond according to which way a person would be forced to throw the frisbee (either home/away or forehand/backhand). In the road intersection task, they will respond according to which a person should travel (either home/away, or left/right). We predict that a preference for home/away on one task will correlate with a preference for home/away on the other task. We will also look at the strength of this correlation as a function of ultimate frisbee experience and navigation ability. Task order will be counter-balanced across participants.

3) Describe the key dependent variable(s) specifying how they will be measured.
We will measure the reaction time for each trial, excluding incorrect trials, and excluding trials which have reaction time > 2SD of each participant's mean reaction time.

4) How many and which conditions will participants be assigned to?
We will use a within-subjects design. All participants will take part in all conditions. For the ultimate frisbee and road intersection tasks, we will vary the orientation of the stick figure (facing away or toward), the direction of "home" (left or right), and the prompt (home/away, and forehand/backhand for ultimate frisbee; home/away and left/right for road intersection). The combination of these leads to 16 trial types. We will generate four random sequences of these 16 trials per task per subject, leading to a total of 64 trials per task.

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
To test our main hypothesis, we will subtract each participant's average reaction time for home/away trials from the average reaction time for forehand/backhand trials. We will then subtract each participant's average reaction time for home/away from the average reaction time for left/right trials. We will correlate these two differences to measure how reference frame correlates across the ultimate frisbee and navigational domains

6) Any secondary analyses?
We will analyze individual differences in ultimate frisbee experience and navigation ability (as measured by a self-report measure: the Santa Barbara Sense of Direction; in particular, we are interested in the item about preference for North/East/South/West).
We will also investigate differences at the group level for home faster or slower than away, forehand faster or slower than backhand, and facing the participant faster or slower than facing away from the participant.

7) How many observations will be collected or what will determine sample size?
No need to justify decision, but be precise about exactly how the number will be determined.

We will conduct a sequential analysis, as recommended in Albers and Lakens (2017) pre-print and Lakens (2014). As suggested by Lakens, our smallest effect size of interest is chosen as the minimum effect size detectable with the maximum number of subjects we are willing to run (150), with 80% power, which is the correlation r = .22. We will thus run analyses after every 50 subjects and stop if we have p < .0221 (as determined by the Pocock correction), or if correlation r < .22.

8) Anything else you would like to pre-register?
(e.g., data exclusions, variables collected for exploratory purposes, unusual analyses planned?)

Because this study is being collected online, we will exclude subjects who have highly inaccurate results (either below chance, or below 2SD's below the group mean on either task). We will also look at participant de-briefing questions for exploratory purposes.