#25642 | AsPredicted

'Surprise & Probability: Happy first'
(AsPredicted #25642)

Created:       07/10/2019 12:01 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?
Previous research has found that infants look longer at events that violate their expectations than those that do not. In this study, we ask whether observing someone else’s emotional expressions modulates infants’ looking time at expected vs. unexpected events. Infants will observe a sampling event (adapted from Xu & Garcia, 2008) and see the experimenter expressing an unsurprised happy expression (or a surprised expression) at the outcome before it is revealed to the infants. After the outcome is revealed, we will measure infants’ looking time. Along with another preregistered study that focuses on surprised expression (AsPredicted#19904), the current study focuses on the effect of happy expression on the first trial (four trials in total). Our main hypotheses are that 1) infants will look longer at the improbable outcome than the probable outcome following an unsurprised happy expression; 2) when data from AsPredicted#19904 are combined with the current data, we would find an interaction between Emotion and Outcome Probability.

3) Describe the key dependent variable(s) specifying how they will be measured.
Infants’ looking time at an event outcome.

4) How many and which conditions will participants be assigned to?
There are four conditions, crossing two factors: outcome probability (Probable vs. Improbable) and the experimenter’s emotional response to the outcome (Happy vs. Surprise), and each participant will see all 4 trials. However, as in AsPredicted#19904, we are primarily interested in analyzing the first trial, across two Happy conditions. Thus infants will first see the Happy-Probable and Happy-Improbable trials (order counterbalanced), and then the Surprise-Probable and Surprise-Improbable trials (order counterbalanced). We use this order because the first-trial data from this dataset will be combined with first-trial data from another study where infants saw the two surprise conditions first (AsPredicted#19904).

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Our main analyses will focus on the first test trial. We will use two-sample t-test to compare infants’ looking time between the Happy-Probable and Happy-Improbable conditions. If the data violates assumptions of Student’s t-test (e.g., homoscedasticity, normal distribution), we will use appropriate alternative tests such as Welch t-test or Mann-Whitney U test.
We will also combine this dataset with another dataset that started with the Surprise-Probable and Surprise-Improbable conditions (AsPredicted#19904); consistent with our main analysis, only the data from the first trial will be analyzed. We will use ANOVA to test the interaction between Emotion (Happy vs. Surprise) and Outcome Probability (Probable vs. Improbable). If the assumptions of ANOVA tests are violated, we will use appropriate alternative tests such as Welch’s F-test or Kruskal-Wallis ANOVA.

6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
We will exclude data points (i.e., looking time on a given trial) if the following happens: infant fussiness, parental or sibling interference, distraction (by e.g., museum noise), experimenter error, or infant looking time over 3 standard deviations of the mean. Data from an infant will be excluded (and replaced) if the first test trial is excluded, or if more than two of the four test trials are excluded.

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 plan to test 64 12-17-month-olds. Half will start with the Happy-Probable condition; the other half will start with the Happy-Improbable condition.

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

Exploratory analyses based on this dataset:
* We will run the analyses with data from the first two test trials (two datapoints per infant) using paired t-test, because the effect may be present even in the second trial and within-subject comparison offers more power.
* We will also look at the last two test trials, testing if infants look longer at the Surprise-Probable than Surprise-Improbable outcomes using paired t test.
* We will use data from all four trials, looking at the interaction between outcome probability and emotion using mixed-effects model.
Exploratory analyses combining this dataset with another one (AsPredicted#19904) started with Surprise conditions?
* Because our previous data suggests a stronger effect when an emotional expression appears the first time than the second time, we will look at data from the third trial, in which an emotional expression different from the first two trials appears the first time. We will test the interaction between outcome probability and emotion using ANOVA test, and test the simple effect of emotion using two-sample t-test.
* We will also look at the interaction between outcome probability and emotion using mixed-effect model and the simple effect of emotion using paired t-test, based on data from the first two trials, the last two trials, and all four trials.