References
- Aczel, B., Szaszi, B., Nilsonne, G., Albers, C. J., van Assen, M. A., Bastiaansen, J. A., Benjamin, D., Boehm, U., Botvinik-Nezer, R., Bringmann, L. F., Busch, N. A., Caruyer, E., Cataldo, A. M., Cowan, N., Delios, A., van Dongen, N. N., Donkin, C., van Doorn, J. B., Dreber, A., …Wagenmakers, E. J. (2021). Consensus-based guidance for conducting and reporting multi-analyst studies. eLife, 10, Article e72185. https://doi.org/10.7554/eLife.72185
- Atkinson, Q. D., Claessens, S., Fischer, K., Forsyth, G. L., Kyritsis, T., Wiebels, K., & Moreau, D. (2022). Being specific about generalisability. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070251
- Balkaya-Ince, M., & Schnitker, S. (2022). Advantages of using multilevel modeling approaches for the many analysts religion project. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070264
- Bulbulia, J. A. (2022). A workflow for causal inference in cross-cultural psychology. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070245
- Edelsbrunner, P. A., Sebben, S., Frisch, L. K., Schüttengruber, V., Protzko, J., & Thurn, C. M. (2022). How to understand a research question – A challenging first step in setting up a statistical model. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070258
- Hanel, P. H. P., & Zarzeczna, N. (2022). From multiverse analysis to multiverse operationalisations: 262, 143 ways of measuring well-being. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070259
- Himawan, K. K., Martoyo, I., Himawan, E. M., Aditya, Y., & Suwartono, C. (2022). Religion and well-being in Indonesia: Exploring the role of religion in a society where being atheist is not an option. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070266
- Hoogeveen, S., Sarafoglou, A., Aczel, B., Aditya, Y., Alayan, A. J., Allen, P. J., Altay, S., Alzahawi, S., Amir, Y., Anthony, F.-V., Appiah, O. K., Atkinson, Q. D., Baimel, A., Balkaya-Ince, M., Balsamo, M., Banker, S., Bartoš, F., Becerra, M., Beffara, B., Beitner, J., Bendixen, T., … Wagenmakers, E.-J. (2022). A many-analysts approach to the relation between religiosity and well-being. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070255
- Islam, C. G., & Lorenz, J. (2022). Commentary to MARP: How to increase the robustness of survey studies. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070257
- Krypotos, A. M., Klein, R., & Jong, J. (2022). Resolving religious debates through a multiverse approach. Religion, Brain & Behavior. https://doi.org/10.1080/10.1080/2153599X.2022.2070261
- Lodder, P. (2022). Why researchers should not ignore measurement error and skewness in questionnaire item scores. Religion, Brain & Behavior. https://doi.org/10.1080/10.1080/2153599X.2022.2070250
- McNamara, A. A. (2022). The impact (or lack thereof) of analysis choice on conclusions with likert data from the Many Analysts Religion Project. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070256
- Murphy, J., & Martinez, N. (2022). Quantifying religiosity: A comparison of approaches based on categorical self-identification and multidimensional measures of religious activity. Religion, Brain & Behavior. https://doi.org/10.1080/10.1080/2153599X.2022.2070252
- Paloutzian, R. (2017). Invitation to the psychology of religion. Guilford Press.
- Pearson, H. I., Lo, R. F., & Sasaki, J. Y. (2022). How do culture and religion interact worldwide? A cultural match approach to understanding religiosity and well-being in the Many Analysts Religion Project. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070265
- Ross, R. M., Sulik, J., Buczny, J., & Schivinski, B. (2022). Many analysts and few incentives. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070248
- Sarafoglou, A., Hoogeveen, S., & Wagenmakers, E. J. (2022). Comparing analysis blinding with preregistration in the many-analysts religion project. PsyArXiv. https://doi.org/10.31234/osf.io/6dn8f
- Schreiner, M. R., Mercier, B., Frick, S., Wiwad, D., Schmitt, M. C., Kelly, J. M., & Quevedo Pütter, J. (2022). Measurement issues in the Many Analysts Religion Project. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070260
- Silberzahn, R., Uhlmann, E. L., Martin, D. P., Anselmi, P., Aust, F., Awtrey, E., Bahník, Š., Bai, F., Bannard, C., Bonnier, E., Carlsson, R., Cheung, F., Christensen, G., Clay, R., Craig, M. A., Dalla Rosa, A., Dam, L., Evans, M. H., Flores Cervantes, I., …Nosek, B. A. (2018). Many analysts, one data set: Making transparent how variations in analytic choices affect results. Advances in Methods and Practices in Psychological Science, 1(3), 337–356. https://doi.org/10.1177/2515245917747646
- Smith, E. (2022). Individual-level versus country-level moderation [Commentary in MARP special issue].
- van Assen, M. A., Stoevenbelt, A. H., & van Aert, R. C. (2022). The end justifies all means: Questionable conversion of different effect sizes to a common effect size measure. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070249
- van Lissa, C. J. (2022). Complementing preregistered confirmatory analyses with rigorous, reproducible exploration using machine learning. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070254
- van Lissa, C. J., Peikert, A., & Brandmaier, A. M. (2022). WORCS: Workflow for open reproducible code in science [Manual]. R package version 0.1.9.1. https://github.com/cjvanlissa/worcs
- Vogel, V., Prenoveau, J., Kelchtermans, S., Magyar-Russell, G., McMahon, C., Ingendahl, M., & Schaumans, C. B. C. (2022). Different facets, different results: The importance of considering the multidimensionality of constructs. Religion, Brain & Behavior. https://doi.org/10.1080/2153599X.2022.2070262
- Wagenmakers, E. J., Sarafoglou, A., Aarts, S., Albers, C., Algermissen, J., Bahník, Š., van Dongen, N., Hoekstra, R., Moreau, D., van Ravenzwaaij, D., Sluga, A., Stanke, F., Tendeiro, J., & Aczel, B. (2021). Seven steps toward more transparency in statistical practice. Nature Human Behaviour, 5(11), 1473–1480. https://doi.org/10.1038/s41562-021-01211-8