This folder contains raw data of the whole sample and spreadsheets of our statistical analysis. We will also add a general discussion about our replication study. We replicated the descriptive analysis of the authors for race, age, income. Also, we added nationality to the descriptive analysis because this variable was added to our study. We added the variable 'nationality' to recruit the number of participants we needed. Since we wanted to conduct this replication in english, we search for people that spoke English. Thus, our sample include people from the UK and the US, contrary to the original study that only include people from the US. We replicated the multiple linear regressions of the authors. As they did, we looked at the link between CRA and SES (controled by the score in life stress) and we also looked if the covariates (age, income, race and HCRU) had an influence on our correlation (CRA and SES). We did our analysis using Jamovi after stopping the data collection. For the income analysis of both the United Kingdom and the United States of America we z-transformed the income variable within country before data analysis. There was 101 participants in this study. In the original study, there was 301 participants. This difference is not worrying because we make sure that this number was sufficient to observe the effect (See the Power Analysis in the Materials' wiki). For the analysis for the age of the participants, we had to excluded 3 participants because they did not answered this question. **Results :** To test the effect of CRA and SES while controlling the life stress on depressive symptoms, we computed different linear regression with a model where the interaction between CRA and SES was tested. In view of our results, there were no significant effects of SES and CRA but there were significant effects of PSS (stress). It means that PSS was the variable that explain the most of the model in our linear regressions. To make sure that results were not linked by demographic confounds or some habitual cognitive uses, we controlled for age, gender, race (reported as Caucasians and other) and habitual reappraisal use individually and entered these predictors as covariates to the model described above. Also, when not controlling for life stress, interaction between SES and CRA was also non-significant β = 0.0905, t (97) = 1,865, p = 0,065. In each model, the interaction between SES and CRA remained non-significant, only the stress variable was significant. Please see the Results files for more details.