PubMed · 15715389
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
Sally Lehrman. 2005. Performance without anxiety.. https://doi.org/10.1038/scientificamerican0205-36
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
Trend tests for genetic association using a matched case-control design are studied, which allows for a variable number of controls per case. However, the tests depend on the scores based on the underlying genetic model, thus it may result in substantial loss of power when the model is misspecified. Since the mode of inheritance may be unknown for complex diseases, robust trend tests in matched case-control studies are developed. Simulation is conducted to compare the trend tests and the robust trend tests under various genetic models. The results are applied to detect candidate-gene association using an example from a case-control aetiologic study of sarcoidosis.
In population-based cancer survival studies, the cause-specific survival measures the net survival (excess mortality) due to cancer when the cause of death information is available and reliable. In contrast, when the cause of death is uncertain or unavailable, relative survival, the ratio of the survival rate due to all causes to the expected survival rate, is more appropriate. There is a large body of work on the modelling and hypothesis testing of cause-specific survival, but many of these methods are not directly applicable to relative survival. In this paper, we extend the multiple imputation (MI) methods (Stat. Methods Med. Res. 1999; 8:3-15) to the case of relative survival data. The MI methodology is combined with relative survival to estimate the net survival by changing relative survival data to cause-specific data. This facilitates the direct application to statistical methods developed for the cause-specific survival to the special situation of relative survival. The parameter estimates and the log-rank statistics are obtained by combining the results from multiple imputed cause-specific data. The likelihood-based methods for modelling relative survival data have been implemented by a Windows application called CANSURV (Comput. Meth. Prog. Biomed 2005). Although these methods produce accurate parameter estimates, the choice for models and diagnostic tools is limited. The MI method is presented as a simpler alternative. The relative survival data for the colorectal cancer patients from Surveillance, Epidemiology, and End Results (SEER) program (SEER Cancer Statistics Review, 1973-1999. National Cancer Institute: Bethesda, 2002) is used as an illustration. The results are compared with those obtained from the likelihood-based relative survival analysis methods. A sample SAS macro for the MI method is provided.
Recent research has indicated that the prevalence of mental disorders is estimated to be higher among Blacks than among Whites, most likely due to the nexus of race and socioeconomic disparity. Blacks are under-represented in in-patient populations and more likely than Whites to use the emergency rooms for mental health treatment. Numerous studies confirm that Blacks drop out of mental health services at a significantly higher rate than Whites and use fewer treatment sessions for mental health issues. Furthermore, Blacks enter mental health treatment at a later, more advanced stage than Whites, under-consume community mental health services of all kinds, are misdiagnosed more often than Whites, and are more often diagnosed with a severe mental illness than Whites. People from diverse ethnic backgrounds often are prevented from receiving adequate mental health treatment due to misdiagnoses and lack of access to the services they need. Factors contributing to this disparity include a general mistrust of medical health professionals, cultural barriers, co-occurring disorders, socioeconomic factors, and primary reliance on family and the religious community during times of distress. Unfortunately, the traditional institutions of racialized research largely ignore the disparate social and political exposures confronting people of color, such as residential and occupational segregation, racial profiling, tokenism, discrimination, racism, and the consequential physiological and psychological effects flowing from the macro and micro effects of such interactions and intersectionalities. This article explores these issues and proposes civil law legal frameworks for addressing these disparities. In particular, it is suggested that renewed consideration be made of the Thin-skull and Eggshell doctrines in the United States and comparable traditional international doctrine.