Author(s) Moritz Ingendahl (Ruhr-Universität Bochum) - moritz.ingendahl@rub.de Franziska Schäfer (University of Mannheim) - franziska.schaefer@uni-mannheim.de
Pre-registered on 03/09/2023 12:55 PM (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? We investigate the role of metamemory in evaluative conditioning (EC).
We expect that pairings with positive/neutral/negative USs lead to corresponding evaluations of CSs, such that positive > neutral > negative.
We expect that US valence also impacts JOLs, such that positive and negative USs lead to higher JOLs than neutral USs.
We expect that EC effects are stronger for pairings where participants can identify the correct US.
We expect that higher JOLs are associated with stronger EC effects.
In this study, we investigate whether the effects of JOLs are due to and incremental to the subjective CS-US fit. We expect that stronger CS-US fit is positively associated with JOLs. We also expect that CS-US fit is associated with a stronger EC effect and accounts for the stronger EC effect for higher JOLs.
3) Describe the key dependent variable(s) specifying how they will be measured. We assess JOLs with the question: "How likely is it that you will remember this picture if your are presented with this brand name?", and a scale from 0 -100% for each of the 24 CS.
We assess CS-US fit with the question: "How well would you say do picture and brand name fit together?", and a scale from 0 to 100 representing a scale from "not at all" to "very much" for each of the 24 CS.
We assess CS Evaluations and CS-US memory with the same instructions and tasks as Ingendahl and Vogel (2023).
4) How many and which conditions will participants be assigned to? US valence (positive/neutral/negative, within-subjects). There are 8 CS-US pairs per valence level.
We counterbalance the order of the JOL and the fit phase between participants.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. We will analyze each dependent variable with a multilevel regression in lme4, using the highest converging random effect structure. For CS-US memory, we will use a binomial multilevel regression. In each model, we will use two dummy variables (positive + negative valence, baseline = neutral) as predictors. For all models, Order will be added as a further main effect (1 vs. -1) and will be allowed to interact with each variable. If order does not have an effect, we will repeat the respective model without order and use that model as the primary model for our main analysis.
For CS evaluations, we expect a positive effect of positive valence and a negative effect of negative valence.
For JOLs, we expect two positive effects.
For CS-US fit, we do not expect any effects.
For CS-US memory, we do not expect any effects.
Next, we will compute within-subjects gamma correlations between JOLs and CS-US memory. We will also compute a correlation between JOLs and FIt both on a person- and on a within-person level.
Next, we will do one multilevel model where we add the z-standardized (within-person-centered) JOLs as a moderator to the model predicting CS evaluations. The model will have a main effect of within-person JOL, the two dummies, and two interaction terms. We expect two significant interaction terms (positive for positive, negative for negative interaction term).
Next, we will do one multilevel model where we add the z-standardized (within-person-centered) FIT as a moderator to the model predicting CS evaluations. The model will have a main effect of within-person FIT, the two dummies, and two interaction terms. We expect two significant interaction terms (positive for positive, negative for negative interaction term).
Finally, we will do a model with the predictors of the previous two models combined. We leave open whether the JOL*positive and JOL*negative interactions are still significant when the FIT*positive and FIT*negative interactions are included.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. We do not plan any exclusions.
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 collect 70 finished interviews.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) --
