As Predicted:Study 5: Forgotten Inference (#9221)
Created: 03/20/2018 12:54 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 will conduct a field study where we sell hand warmers in Paris during the winter. In this study we will ask participants to choose between either a high-heat hand warmer with a short heating life or a low-heat hand warmer with a long heating life. Participants will be placed in either a ‘forgotten’ condition where they were told that they had been shown the heating life of one of the hand warmer brands (the missing attribute warmer), or an ‘unknown’ condition where they are told they had never been shown the heating life of the missing attribute warmer. For each participant the missing attribute warmer will be randomly counterbalanced to be either the high-heat/short life or low-heat/long life brand. In both conditions participants are told the heating life of the missing attribute warmer, but in a format that is difficult to remember. We expect participants to construe the heating life as forgotten in the forgotten condition and unknown in the unknown condition.
Participants will then choose between receiving either the missing attribute warmer or a second hand warmer where the heating life is given (the fully described warmer). Participants also will make inferences about the heating life of the missing attribute warmer.
We predict that when the hand warmer life is believed to be forgotten, participants will search their memories and make the gist-based inference that a missing attribute warmer with a high (low) heat also had a long (short) heating life, consistent with its other performance characteristics. In contrast, we expect that when the missing attribute warmer life was believed to be unknown, participants will make the rule-based inference that a high (low) heat brand had a short (long) heating life driven either by the probabilistic consistency inference that higher heating will burn faster (Bradlow, Hu, and Ho 2004), or the compensatory inference that the high heat brand will have a heating life than the low heat brand, since both warmers are the same price (Chernev and Carpenter 2001). Following these inference, we predict that when the missing attribute warmer is the high-heat/short life warmer, participants in the forgotten condition compared to the unknown condition will be more likely to choose the missing attribute warmer over the fully described warmer. In contrast, when the missing attribute warmer is the low-heat/long life warmer, participants in the forgotten condition compared to the unknown condition will be more likely to choose the fully described warmer over the missing attribute warmer. We also predict that the difference in choices between the forgotten and unknown conditions would be mediated by the inferences participants made about heating life.3) Describe the key dependent variable(s) specifying how they will be measured.
Hand warmer life (hours ranging from 0 to 20)
Hand warmer choice (actual choice)
4) How many and which conditions will participants be assigned to?
Condition 1: Forgotten vs. Unknown condition
Condition 2: counterbalancing whether the missing information heater is high heat/short life or low heat/long life
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Linear regression of interaction between condition 1 and condition 2 to predict Hand warmer life
Logistic regression of interaction between condition 1 and condition 2 to predict choice
Logistic mediation to see if the relationship between condition 1x2 and choice is mediated by hand warmer life.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
none7) 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.
150-200, based on the number of hand-warmers pre-purchased8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?)