@article{ref1,
title="Approach to analysing correlated contextual factors: an application for studies on violence",
journal="Injury prevention",
year="2021",
author="Peek-Asa, Corinne L. and Cheng, Gang and Flores, Javier E. and Ramirez, Marizen R. and Cavanaugh, Joseph E.",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="BACKGROUND: Numerous public health studies, especially in the area of violence, examine the effects of contextual or group-level factors on health outcomes. Often,  these contextual factors exhibit strong pairwise correlations, which pose a  challenge when these factors are included as covariates in a statistical model. Such  models may be characterised by inflated standard errors and unstable parameter  estimates that may fluctuate drastically from sample to sample, where the excessive  estimation variability is reflected by inflated standard errors. <br><br>METHODS: We propose  a three-stage approach for analysing correlated contextual factors that proceeds as  follows: (1) a principal components analysis (PCA) is performed on the original set  of correlated variables, (2) the primary generated principal components are included  in a multilevel multivariable model and (3) the estimated parameters for these  components are transformed into estimates for each of the original contextual  factors. Using school violence data, we examined the associations between school  crime and correlated contextual school factors (ie, English proficiency, academic  performance, pupil to teacher ratio, average class size and children on free and  reduced meals). <br><br>RESULTS: From models ignoring correlations, school crime was not  reliably associated with any of the contextual school factors. When models were fit  with principal components, school crime was found to be positively associated with a  school's student to teacher ratio, average classroom size and academic performance  but negatively associated with the proportion of children who were on free and  reduced meals. <br><br>CONCLUSION: Our multistep approach is one way to address  multicollinearity encountered in social epidemiological studies of violence.<p /> <p>Language: en</p>",
language="en",
issn="1353-8047",
doi="10.1136/injuryprev-2020-043967",
url="http://dx.doi.org/10.1136/injuryprev-2020-043967"
}