'WhiteSclera'
(AsPredicted #77174)
Created: 10/17/2021 02:04 PM (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? Reconstructed hominin faces with a white sclera will be judged as
(H1) less aggressive
(H2) more attractive
(H3) more trustworthy
(H4) healthier
(H5) younger
than the same faces with a dark sclera.
3) Describe the key dependent variable(s) specifying how they will be measured. Perceived aggressiveness
Perceived attractiveness
Perceived health
Perceived trustworthiness
Perceived age
All measured with a 1 to 100 VAS by adjusting the position of the slider between the left ("very unattractive"... etc.) to right ("very attractive"... etc.)
4) How many and which conditions will participants be assigned to? 2 conditions - white sclera vs dark sclera.
STIMULUS: 20 faces, each one in a white sclera and a dark sclera version (= 40 images in total)
Each participant will see all 20 faces, 10 of them in the white sclera and the remaining 10 in the dark sclera condition, i.e. all 20 faces will be shown, but each face only once and in only one condition. The order of the faces and the order of the conditions for each face (i.e. 'white' vs 'dark') will be random, but balanced so that each participant rates 10 dark sclera and 10 white sclera faces.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. A GLMM for each of our dependent variables, with "dark sclera" and "white sclera" as IV. Stimuli and participants would be added as random effects to the models.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. EXCLUSIONS.
We will exclude observations from any participant who
- does not move the slider on any 4 or more consecutive ratings
- completes the study in time that is shorter that Q1 - 1.5x IQR for completion time in our sample.
Interquartile range (IQR) is defined as the difference between the third (Q3) and first (Q1) quartile calculated for the analysed data.
OUTLIERS.
Observations that fall outside Q1 − 1.5 x IQR (lower bound) or above Q3 + 1.5 x IQR (upper bound) will be considered outliers
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. 250 participants on Prolific (users that have supplied a range of demographic information, have completed at least two previous Prolific studies
with an approval rate of 100%, and have normal or corrected to normal vision and are fluent in English).
Existing studies suggest sample sizes of that order for rating images remotely, where display conditions vary between the participants
8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) We will gather a variety of demographic data that could then be used for exploratory post-analyses
