Left truncation in linked data: A practical guide to understanding left truncation and applying it using SAS and R

Time-to-event data such as time to death are broadly used in medical research and drug development to understand the efficacy of a therapeutic. For time-to-event data, right censoring (data only observed up to a certain point of time) is common and easy to recognize. Methods that use right censored data, such as the Kaplan–Meier estimator and the Cox proportional hazard model, are well established. Time-to-event data can also be left truncated, which arises when patients are excluded from the sample because their events occur before a specific milestone, potentially resulting in an immortal time bias. For example, in a study evaluating the association between biomarker status and overall survival, patients who did not live long enough to receive a genomic test were not observed in the study. Left truncation causes selection bias and often leads to an overestimate of survival time. In this tutorial, we used a nationwide electronic health record-derived de-identified database to demonstrate how to analyze left truncated and right censored data without bias using example code from SAS and R.     

Racial-ethnic socialization,racial discrimination,and internalization of the model minority myth in East Asian families

Guided by the integrative model, this study investigated the moderating effect of East Asian American youth-reported (N = 143) racial-ethnic socialization (RES) in the relationship between the youth's experiences of discrimination and internalization of the model minority myth. The results suggest that there was a significant interaction between youth's racial discrimination and youth-reported awareness of discrimination on youth's internalization of the model minority myth (b = 3.52, p < .05). No significant interaction effect emerged between racial discrimination and maintenance of heritage culture on internalization of model minority myth. The findings offer several contributions to inform research, family, and communities in understanding the ways caregivers respond to youth's racialized settings, which also contribute to youth's positive outcomes.