Author(s) Moritz Ingendahl (Ruhr-Universität Bochum) - moritz.ingendahl@rub.de Franziska Schäfer (University of Mannheim) - franziska.schaefer@uni-mannheim.de
Pre-registered on 04/23/2023 06:16 AM (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.
In this study, we investigate to what extent assessing JOLs strengthens the EC effect, the memory for the stimulus pairings, or the US valence. Also, we investigate to what extent assesing JOLs changes the moderating impact of memory and individual US extremity on the EC effect.
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 Evaluations, US 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) x Condition (Control vs. JOL; between-subjects). There are 8 CS-US pairs per valence level.
Participants in the control condition will have the same procedure as in the JOL condition, but without the assessment of JOLs and instead an additional presentation for each CS-US pair.
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 together with the effect-coded condition (1 = JOL, -1 = control) and the two interaction terms.
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 memory, we do not expect any effects.
For US evaluations, we expect a positive effect of positive valence and a negative effect of negative valence.
Next, we will compute within-subjects gamma correlations between JOLs and CS-US memory [within the JOL condition]. We will also compute a correlation between JOLs and US evaluations both on a person- and on a within-person level.
Last, we will examine to what extent assessing JOLS changes the relation between memory and EC, or between individual US extremity and EC.
We will compute an extremity index for the US evaluation (0 = neutral, 3 = very extreme based on the scale midpoint). We will do one multilevel model where we add the z-standardized US extremity as a moderator to the model predicting CS evaluations. The model will have a main effect of US extremity, the two dummies, and two interaction terms, and all interactions with condition. We expect two significant interaction terms (positive for positive, negative for negative interaction term) and leave open whether there is also a three-way interaction of condition*extremity*positive(or negative).
We will do the same model but with z-standardized memory instead of US extremity. We expect that memory strengthens the effect of positive and negative US valence and leave open whether there are also three-way interactions.
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?) Nothing else to pre-register.
