'Modal amodal (WP 2, Study 3, Exp. 3.1)' (AsPredicted #167,600)
Author(s) This pre-registration is currently anonymous to enable blind peer-review. It has 5 authors.
Pre-registered on 2024/03/22 13:31 (PT)
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? While confidence is often measured alongside accuracy in event perception research, to our knowledge, the concepts of accuracy and confidence were never put into relation. Leveraging Signal-Detection Theory (SDT) measures, we thus investigate whether people have an accurate insight into their accuracy within the event completion paradigm.
We will replicate the first experiment from Papenmeier et al., (2019) - delayed response with a between causality design - with a higher number of trials (n = 52) that will ensure accurate measurement of metacognitive efficiency (Mratio).
H1: We expect that detection accuracy is lower in the causal than in the non-causal condition.
H2: We expect metacognitive efficiency to be lower in the causal compared to the non-causal condition.
3) Describe the key dependent variable(s) specifying how they will be measured. DV:
Contact detection: Participants will indicate whether they have seen the moment of ball contact for each trial. Responses will be dichotomous (yes/no).
Confidence assessment: Participants will rate how confident they were in their response on a 6-point Likert scale ranging from 50% I guessed to 100% I am certain.
We will use methods from Signal-Detection Theory (SDT) to calculate:
Task sensitivity: To measure the accuracy of contact detection we determine the task sensitivity d' as specified in a Signal Detection Theory (SDT) framework by calculating the difference of the Z-standardized False Positive, and the Z-standardized True Positive rate; with Z being the inverse cumulative density function of the normal distribution. To account for false positive rates/true positive rates of 0 or 1 we will apply the loglinear approach of Hautus (1995).
Metacognitive efficiency: To measure metacognitive efficiency, we determine the ratio of meta-d' and task sensitivity d' (Mratio = meta-d'/d'). To compute Mratio, we use a hierarchical Bayes procedure (Fleming, 2017). This approach has the advantage of providing an accurate estimation of Mratio in cases of low trial numbers.
4) How many and which conditions will participants be assigned to? Participants will watch soccer clips consisting of two camera shots. In the first shot participants will see a player who prepares for the shot and finally shoots the ball.
There will be two conditions:
(a) Causal continuation: participants will see the ball flying
(b) Non-causal continuation: participants will see an unrelated scene (e.g., cheering supporters)
In half of the trials, we will omit the moment of ball contact. After each trial, participants will indicate whether they have seen the moment of ball contact and rate how confident they were in their response.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. H1: We will run a t test to investigate whether contact-detection performance (d') differs between the causal continuation and the non-causal continuation group. Additionally, we will run a mixed analysis of variance (ANOVA) containing the factors contact (present, absent; within) and causality (causal, non-causal; between) and the dependent-measure proportion of contact responses.
H2: We are comparing Mratio between the causal and non-causal group by calculating the difference between the group posteriors using the code provided here: https://github.com/smfleming/HMeta-d.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. Requirements for inclusion:
- at least 18 years old
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 are aiming to sample N = 112 valid cases. This sample size is based on two power analyses: First, assuming an effect size of d = 0.69 for the effect of causal continuation on contact detection performance (see Papenmeier et al., 2019; note: as a conservative estimate, we used the lower of the two effect sizes associated with the two experimental versions of Experiment 1 of Papenmeier et al., 2019), 112 participants are needed to achieve a power of 95% for the planned t test. Furthermore, simulations showed that ~100 subjects are needed to achieve a power of at least 90% for the planned Mratio analysis.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) Note that we preregistered this study already under https://aspredicted.org/BK7_XH9. We decided to upload a new version with an adjusted number of trials (based on simulations) as well as a focus on metacognitive efficiency. Importantly, the present version of the preregistration is also uploaded prior to data collection.
