Exclusion criteria:
- Participants under the age of 18 years.
- Participants who do not rate all 90 faces.
- Where participants repeat the study, only the first set of ratings per participant will be used.
Sibling and couple judgment scores will be analyzed using **generalized linear mixed effects models**.
Hypotheses 2 and 4 (both couple and sibling judgments):
glmer(score ~ judgment type * sim * pair type +
(1 + sim * pair type || user_id) +
(1 + judgment type || pair_id),
data = data.sib.cpl, family = binomial)
Hypothesis 1 (only couple judgements):
glmer(score ~ pair type +
(1 + pair type || user_id) +
(1 | pair_id),
data = data.cpl, family = binomial)
Hypothesis 3 (only sibling judgements):
glmer(score ~ sim +
(1 + sim || user_id) +
(1 | pair_id),
data = data.sib, family = binomial)
Dependent variable:
- Sibling and couple judgment scores (no: 0 / yes: 1)
Independent variables:
- Perceived similarity rating (scale 0 - 10; not similar: 0, very similar: 10)
- Pair type (foil: 0 / couple: 1)
- Judgment type (sibling: 0 / couple: 1)
Perceived similarity ratings will be analyzed in an intercept-only linear mixed effects model and the random intercepts will be computed for each pair to be used as their perceived similarity scores (see 'Analysis: Generate similarity scores').
