Portfolio item number 1
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In press (Collabra: Psychology)
This paper is about trend and the best practice of causal mediation in the field of social psychology.
Recommended citation: Kim, J.& Thommes, F. (2026). https://doi.org/10.17605/OSF.IO/DTK4H
Under review
This paper provides new statistical evidence of gender discrimination using instrumental inequality.
Recommended citation: Kim,J., & Kim, Y. (2026). https://www.postersessiononline.eu/173580348_eu/congresos/SCI2024/aula/-P_43_SCI2024.pdf
Published in The SNU Journal of Education Research, 2021
This paper is about developing and validating an academic resilience scale.
Recommended citation: Baek, S. G., Kim, J, & Park, H. (2021). Development and validation of the academic resilience scale for undergraduate students using scenario method. The SNU Journal of Education Research, 30(3), 29-57. https://www.dbpia.co.kr/journal/voisDetail?voisId=VOIS00700524
Under review
In this study, we aim to develop a new scale, Augmented Triangular Theory of the Expression of Love (ATTEL), and conduct an LPA analysis to check the different types of latent profiles using the scale.
Recommended citation: Soleimani, A, D., Kim, J., & Sternberg, R, J. (2026)
Under Review
This paper distinguishes data generation, detection, and handling in careless responding and uses a causal framework to define careless-response generation mechanisms.
Recommended citation: Kim, J.& Thommes, F. (2026). https://doi.org/10.17605/OSF.IO/DTK4H
Published in Multivariate Behavioral Research, 2025
In this study, we aim to clearly define the specific causal effects estimated by each method within the two-wave longitudinal mediation model.
Recommended citation: Kim, J & Thoemmes, F. (2025). Causal assumptions of the two-wave longitudinal mediation model. Multivariate Behavioral Research. 10.1080/00273171.2025.2443360 (Abstract) https://doi.org/10.1080/00273171.2025.2443360
Published in SAGE Open, 2025
This study contributes to teacher education by providing a validated tool that can help evaluate and enhance pre-service teacher preparation programs for online and hybrid learning environments.
Recommended citation: Baek, J., Kim, J., Lee, H., & Choi, Y.-J. (2025). Development and Validation of the Pre-service Teacher Competency Scale in an Online Learning Environment Using the Scenario Method. SAGE Open, 15(2).(Original work published 2025) https://doi.org/10.1177/21582440251344753
Published:
In this study, I suggested a new method to specify the existence of gender discrimination, using instrumental inequality. Causal graphical model was used to conceptualize the definition of gender discrimination.
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This talk is about the possibility of table 2 fallacy in latent class analysis when putting multiple predictors for latent class.
Published:
In this study, I suggested a new method to specify the existence of gender discrimination, using instrumental inequality. Causal graphical model was used to conceptualize the definition of gender discrimination.
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In this study, I analyzed causal assumptions required for both ANCOVA and change score method under two-wave longitudinal model.
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This study uses the scenario method to develop and validate a scale measuring pre-service teacher competency in an online learning environment. After conducting a comprehensive literature review, this study constructed seven competencies of pre-service teacher in online learning environments: design/planning competency, social competency, instructive competency, technological competency, management competency, positive teacher attitude competency, and learning competency. We developed the Pre-service Teacher Competency in Online Learning Environment scale with 11 scenarios and 34 items after revising and improving it based on a focus group interview with six pre-service teachers and five in-service teachers to review face and content validity. We conducted confirmatory factor analyses and reliability analyses with 579 pre-service teachers. As a result, the scale showed good construct validity and reliability.
Published:
In this study, I suggested a causal graphical approach using m-DAG to check the possible bias in either in intercept and slope under the list-wise deletion situation. By doing so, this paper proposes general criteria for identifying which parameters are recoverable without bias under NMAR. Also, using m-DAGs with distinct notations for conditioning and controlling, this paper clarifies mechanisms behind bias in NMAR models. This approach allows researchers to assess recoverability of means and slopes (e.g., treatment effects), even under listwise deletion.
Published:
In this study, I suggested a causal graphical approach using m-DAG to check the possible bias in either in intercept and slope under the list-wise deletion situation. By doing so, this paper proposes general criteria for identifying which parameters are recoverable without bias under NMAR. Also, using m-DAGs with distinct notations for conditioning and controlling, this paper clarifies mechanisms behind bias in NMAR models. This approach allows researchers to assess recoverability of means and slopes (e.g., treatment effects), even under listwise deletion.
Published:
This study was presented by Felix Thoemmes. In this study, I systematically review the use of causal mediation analysis in social psychology, focusing on how researchers connect statistical analyses to claims about psychological mechanisms. I examine research designs, analytic approaches, and the assumptions needed to interpret mediation effects causally. By distinguishing statistical mediation from causal identification, this review evaluates how methodological practices support causal interpretations and highlights considerations for designing, analyzing, and reporting mediation studies in social psychology.
Published:
In this study, I use a causal graphical framework to characterize careless-response generation mechanisms and distinguish them from detection and handling decisions. Similar observed response patterns can arise from different mechanisms, with different implications for whether responses should be retained, removed, or adjusted. Through simulations, I examine how imperfect detection and handling strategies that do not match the data-generating process contribute to bias. This work clarifies why removing respondents flagged as careless does not necessarily eliminate bias and provides a framework for evaluating the assumptions underlying common handling practices. This study was selected to receive the Psychometric Society Travel Award sponsored by ACS Ventures.
Middle school studet course, Samsung dream class, 2017
I taught impoverished middle school students math math for three years. Also, for their future career, I planned an individualized career development program. Link
Mentoring, Harvard University, 2024
I mentored an underprivileged hish school student to conduct a study using instrumental variable estimation. To do that, I provided lectures for causal inference, focusing on causal graphical model, and papers related to instrumental variable. Also, I guided the mentee to find and conduct her own research. Link
Mentoring, GESIS, 2024
I worked as a TA for the causal mediation workshop held by GESIS. As a TA, I helped students dealing with exercise in class using R, led the discussion and provided them relevent reading materials.
Teaching, Cornell, 2025
I gave a lecture on causal mediation analysis in a quantitative methods class, covering topics such as natural and controlled direct effects, as well as effect decomposition.