This project entails multi-lab collaborative replications of studies on Construal Level Theory (CLT):
Liberman, N., & Trope, Y. (1998). The role of feasibility and desirability considerations in near and distant future decisions: A test of temporal construal theory. Journal of Personality and Social Psychology, 75(1), 5-18. Study 1.
Fujita, K., Henderson, M., Eng, J., Trope, Y., & Liberman, N. (2006). Spatial distance and mental construal of social events. Psychological Science, 14, 278-282. Study 1.
In addition to close replications of these two studies, this project also includes two paradigmatic replications relevant to social and likelihood distance.
The CLIMR project compendium comprises two main parts, one hosted on the Open Science Framework (OSF; https://osf.io/ra3dp/) and one hosted on GitHub (https://github.com/RabbitSnore/CLIMR). The OSF repository for CLIMR contains the materials, methods, and data (when data are collected). The OSF repository also contains the registration documentation and Stage 1 manuscript for the registered report for the primary results of the project. The GitHub repository contains the code necessary to execute and reproduce the statistical analyses for the project.
This repository is structured as follows:
- The source file for compiling the project is located in the root directory.
- The source files to render analysis reports (i.e.,
.Rmdfiles) in the root directory. - The source files for data wrangling, visualization, simulation,
effect calculation, and analysis are located in the
/R/directory. - Rendered figures are located in the
/figures/directory. - Some data are located in the
/data/directory, and data required for analyses will be downloaded automatically from the Open Science Framework as required. - Rendered reports are located in the
/reports/directory.
If you want to reproduce the analyses and output for the CLIMR project, the most straightforward way to do this is to clone this repository into an RStudio project. This webpage has information about how to clone repositories in R Studio. Once you have cloned the repository, open the project in R Studio, and run the following code:
source("CLIMR_build-project.R")
Running this script will install all necessary packages and build the project, including all effect size calculations, meta-analytic models, data visualizations, and reports.
Additionally, CLIMR_build-project.R includes parameters that control its
operations (e.g., whether to run a simulation or load data files). These
parameters must be changed manually, and they should only be changed if you know
what you are doing.
Additional supplemental materials are available on the Open Science Framework: https://osf.io/ra3dp/
Reports of the preliminary studies (as well as placeholder reports using
simulated data for the main studies) are available in the /reports/ directory.
These reports are rendered in a format that is readable on GitHub.
When data collection is complete, the primary results of the replications will be available in the reports linked below.
- Main Analyses
- Comprehension Check Analyses
- Manipulation Check Analyses
- Power Analyses
- BIF Response Option Valence Robustness Checks
In part to assist with the selection of studies that would be theoretically informative to replicate, we have conducted a series of studies assessing measures of mental abstraction/concreteness. These validations studies are reported in a preprint available here: https://osf.io/preprints/psyarxiv/v6xt4
- Validation Study 1: BIF, Categorization, Segmentation
- Validation Study 2: Interval Estimation
- Validation Study 3: Linguistic Measures
To address reviewer concerns and to validate the procedures used in the replication studies, we have conducted a series of pretests and assessments of potential sources of error. These analyses are reported in the documents linked below.
- Differntial Effects on BIF Items
- Relevance of BIF Items to Target Event
- Valence of BIF Response Options
- Pretest of Social Distance Manipulation
Currently, the project is configured so that it will simulate data by default, rather than load real data. Data collection is ongoing. When data collection for the project is complete, the code will be updated to import the publicly available data set by default.
As data are collected, the code in this repository will be periodically updated as we add code to address any issues reported by the contributing labs (e.g., removal of data from researchers testing the surveys), and the code will be updated to correct any errors we detect and/or to address technical issues (e.g., code breakage from package updates).
The CLIMR project analysis code was built using R 4.3.2. The packages required
for the project with information about the version with which the code has been
tested is available in the file /data/meta/climr_version-info.csv. A brief
overview of the most central required packages is provided below.
If you are attempting to reproduce the analyses and encountering errors, some
issues may be resolved by updating R and/or the required packages. For
convenience, you can set the force_update parameter in CLIMR_build-project.R
to TRUE if you want to update and (re)install all the required packages.
Version
cowplot 1.1.3
dplyr 1.1.4
ggbeeswarm 0.7.2
ggplot2 3.5.0
ggstance 0.3.6
leaflet 2.2.1
lme4 1.1-35.1
lubridate 1.9.3
mapview 2.11.2
metafor 4.4-0
osfr 0.2.9
purrr 1.0.2
readr 2.1.5
rmarkdown 2.25
simr 1.0.7
stringr 1.5.1
tidyr 1.3.0
viridis 0.6.4
Some of the supplemental analyses (e.g., validation study analyses) require additional packages not noted here. However, these packages are automatically installed by the scripts for those analyses.
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