This is the accepted version of the paper.This version of the publication may differ from the final published version. censoring to be present in the data. This type of filtering is omnipresent in biostatistical and demographical applications, where people can join a study, leave the study and perhaps join the study again. This paper provides a data application to aggregated national mortality data, where immigrations to and from the country correspond to respectively left truncation and right censoring. The estimation methodology is based on a recent class of local linear density estimators to which we develop a new stable bandwidth-selector, the do-validated estimator. Our aggregated mortality data study illustrates that our new practical density estimators provide us with an important extra element in our visual toolbox for understanding survival data.
Permanent repository link
This is the accepted version of the paper.This version of the publication may differ from the final published version.
Permanent repository link
AbstractPractical estimation procedures for local linear estimation of an unrestricted failure rate when more information is available than just time are developed. This extra information could be a covariate and this covariate could be a time series. Time dependent covariates are sometimes called markers, and failure rates are sometimes called hazards, intensities or mortalities. It is shown through simulations and a practical example that the fully local linear estimation procedure exhibits an excellent practical performance. Two different bandwidth selection procedures are developed. One is an adaptation of classical cross-validation, and the other one is indirect cross-validation. The simulation study concludes that classical cross-validation works well on continuous data while indirect cross-validation performs only marginally better. However, cross-validation breaks down in the practical data application to old-age mortality. Indirect cross-validation is thus shown to be superior when selecting a fully feasible estimation method for marker dependent hazard estimation.
Background
Despite Guatemala’s large indigenous population, indigenous health is often neglected in reported health data and interventions. Although this data is limited in scope, it shows that indigenous people have poorer health outcomes. Sexually transmitted infections (STIs) are now a growing threat in Guatemala and pose great risk to the wellbeing of its indigenous population.
Methods
This qualitative pilot study assessed the knowledge, attitudes, and beliefs of STIs through semi-structured interviews among a previously unstudied population of indigenous Maya women (n = 35, ages 18–50) in the six municipalities of Santa Cruz La Laguna, Guatemala.
Results
Four key themes were identified: 1) indigenous Maya women have limited factual knowledge about sex and STIs; 2) widespread partner infidelity minimizes women’s control over preventing STI contraction; 3) close-knit communities and the resulting heightened fear of gossip prevents communication and hinders care seeking; and 4) lack of quality medical care and inaccessibility of biomedical healthcare systems pose barriers to seeking care for potential STIs.
Conclusions
To address these findings, we suggest methods to improve sexual education, combat male infidelity, promote condom use, and improve health services to reduce the incidence of STIs in Maya Guatemala.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.