@article{ref1,
title="Study designs and statistical approaches to suicide and prevention research in real-world data",
journal="Suicide and life-threatening behavior",
year="2021",
author="Lavigne, Jill E. and Lagerberg, Tyra and Ambrosi, John W. and Chang, Zheng",
volume="51",
number="1",
pages="127-136",
abstract="OBJECTIVE: To provide researchers, clinicians and policy makers with a primer to study designs, statistical approaches and graphical reporting methods for suicide research in real world data (RWD). <br><br>METHODS: Study designs, statistical method and graphical reporting standards are detailed with examples from the recently published literature. <br><br>RESULTS: Data sources and codes for identifying suicidal behavior are described. Study designs are described in detail for post-market surveillance, retrospective cohort studies, case control and nested case-control studies, and self-controlled (within-individual) studies including applications of marginal structural models. Graphical reporting of designs is described using an original research study. <br><br>CONCLUSIONS: Compared to RCTs, RWE studies offer larger sample sizes, greater generalizability, and real-world validity. However, these non-experimental data risk uncontrolled confounding and potential introduction of bias unless data, design and statistical approaches are rigorously aligned.<p /> <p>Language: en</p>",
language="en",
issn="0363-0234",
doi="10.1111/sltb.12677",
url="http://dx.doi.org/10.1111/sltb.12677"
}