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- Assessment tools (1)
- Bi-level selection (1)
- Clinimetrics (1)
- Finnegan Neonatal Abstinence Score (1)
- Formative model (1)
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- Gene sets (1)
- Genomics (1)
- Lung cancer (1)
- Machine learning (1)
- NAS (1)
- Neonatal Abstinence Syndrome (1)
- Neonatal Abstinence Syndrome Score (1)
- P-value (1)
- Predictive accuracy (1)
- Prognostic genes (1)
- Psychiatric disorders (1)
- Psychometrics (1)
- Reflective model (1)
- Replicability (1)
- Statistical methods (1)
Articles 1 - 3 of 3
Full-Text Articles in Medicine and Health Sciences
Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies, Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri Zaykin
Bayesian Prediction Intervals For Assessing P-Value Variability In Prospective Replication Studies, Olga A. Vsevolozhskaya, Gabriel Ruiz, Dmitri Zaykin
Biostatistics Faculty Publications
Increased availability of data and accessibility of computational tools in recent years have created an unprecedented upsurge of scientific studies driven by statistical analysis. Limitations inherent to statistics impose constraints on the reliability of conclusions drawn from data, so misuse of statistical methods is a growing concern. Hypothesis and significance testing, and the accompanying P-values are being scrutinized as representing the most widely applied and abused practices. One line of critique is that P-values are inherently unfit to fulfill their ostensible role as measures of credibility for scientific hypotheses. It has also been suggested that while P-values …
Judging The Neonatal Abstinence Syndrome Assessment Tools To Guide Future Tool Development: The Use Of Clinimetrics As Opposed To Psychometrics, Philip M. Westgate, Enrique Gomez-Pomar
Judging The Neonatal Abstinence Syndrome Assessment Tools To Guide Future Tool Development: The Use Of Clinimetrics As Opposed To Psychometrics, Philip M. Westgate, Enrique Gomez-Pomar
Biostatistics Faculty Publications
In the face of the current Neonatal Abstinence Syndrome (NAS) epidemic, there is considerable variability in the assessment and management of infants with NAS. In this manuscript, we particularly focus on NAS assessment, with special attention given to the popular Finnegan Neonatal Abstinence Score (FNAS). A major instigator of the problem of variable practices is that multiple modified versions of the FNAS exist and continue to be proposed, including shortened versions. Furthermore, the validity of such assessment tools has been questioned, and as a result, the need for better tools has been suggested. The ultimate purpose of this manuscript, therefore, …
Identification Of Prognostic Genes And Gene Sets For Early-Stage Non-Small Cell Lung Cancer Using Bi-Level Selection Methods, Suyan Tian, Chi Wang, Howard H. Chang, Jianguo Sun
Identification Of Prognostic Genes And Gene Sets For Early-Stage Non-Small Cell Lung Cancer Using Bi-Level Selection Methods, Suyan Tian, Chi Wang, Howard H. Chang, Jianguo Sun
Biostatistics Faculty Publications
In contrast to feature selection and gene set analysis, bi-level selection is a process of selecting not only important gene sets but also important genes within those gene sets. Depending on the order of selections, a bi-level selection method can be classified into three categories – forward selection, which first selects relevant gene sets followed by the selection of relevant individual genes; backward selection which takes the reversed order; and simultaneous selection, which performs the two tasks simultaneously usually with the aids of a penalized regression model. To test the existence of subtype-specific prognostic genes for non-small cell lung cancer …