'Study 1b: Forgotten Inference'
(AsPredicted #25219)
Created: 06/26/2019 06:35 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? We predict that there will be a positive correlation between the inferred value of a forgotten attribute and the overall attitude to a product.
3) Describe the key dependent variable(s) specifying how they will be measured. Inferences for a forgotten attribute made on a 1 to 100 numerical scale. We will also measure overall evaluations of the bicycle on a 9-point scale anchored by -4 (very unfavorable) and 4 (very favorable), following the method of Sanbonmatsu et al. (1991).
4) How many and which conditions will participants be assigned to? The study is correlational, so there will only be one condition.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. We will examine an OLS regression with product attitude as the independent variable and inferred attribute value as the dependent variable.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. none
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 aim to collect data on 300 participants.
8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) As exploratory measures, we will also vary the break between when a participants learns about a product attribute and when they make inferences. The delay will either be 1 day or approximately 1 week.
We will also add in exploratory measures of confusion, recall completeness, and other attribute values to address alternative explanations as recommended by the review team.
