Covariates and Factors
Macro-economic factors in credit risk calculations: including time-varying covariates in mixture cure models
... and Crook, 2009), to our knowledge TVCs have not been implemented before in mixture cure models. In the present paper, we examine TVCs in these models, more specifically macro-economic factors, along with the ...
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Mental health in the aged: prevalence, covariates and related neuroendocrine, cardiovascular and inflammatory factors of successful aging
... For descriptive statistical analysis, associations between categorical variables will be carried out with the chi- square test. Group differences in continuous variables will be analysed by the t-test (variables with 2 ...
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Case-control geographic clustering for residential histories accounting for risk factors and covariates
... The approach described in this paper may prove to be a highly useful addition to the traditional aspatial case-con- trol design because it allows researchers to identify local groups of individuals whose risk exceeds ...
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Case control geographic clustering for residential histories accounting for risk factors and covariates
... The approach described in this paper may prove to be a highly useful addition to the traditional aspatial case-con- trol design because it allows researchers to identify local groups of individuals whose risk exceeds ...
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Accommodating Covariates in ROC Analysis
... settings, covariates should be incorporated into the ROC ...are covariates which impact the marker distribution among ...Other covariates may affect the inherent discriminatory accuracy of the marker ...
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A sparse ising model with covariates
... extraneous factors available to us in the form of explanatory variables or covariates, which result in subject-specific graphical ...additional factors may influence the regulatory relationships, and ...
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In search of induction and latency periods: Space-time interaction accounting for residential mobility, risk factors and covariates
... risk factors (smoking) and covariates using the methods described in equation ...risk factors and covariates to the induction and latency periods and (2) those local clusters that cannot be ...
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The Analysis of Censored Covariates in Observational Studies
... ment duration policy. As such, the ESPRIT infusion trial investigators were asked to identify factors that they believed would influence treatment duration. The inves- tigators confirmed that treatment would be ...
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Beyond Traditional Covariates in Medical Informatics
... by factors such as the greater accessibility of medical records enabled by the ever-improving software and hardware security mechanisms, the development of friendlier online collaborative methods, and increased ...
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Missing covariates in competing risks analysis.
... To illustrate the two MI approaches, we consider data from the third US National Health and Nutrition Examination Survey (NHANES III), which was conducted between 1988 and 1994. The overall study involved around 40 000 ...
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Including covariates in the regression discontinuity design
... without covariates fails to identify the e¤ect of the program due to confounding related to an imbal- ance of the characteristics around the ...these factors do ...
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Including Covariates in the Regression Discontinuity Design
... without covariates fails to identify the e¤ect of the program due to confounding related to an imbal- ance of the characteristics around the ...these factors do ...
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Modelling the time variant covariates for gait recognition
... a) b) c) d) Fig. 1. Average silhouette representing subject 46: a) LDB, b) SDB, walking normally, c) SDB, carrying a bag, d) SDB, wearing trench coat it represents subject-dependent covariates. The small database ...
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High-Dimensional Covariates
... high-dimensional covariates With high-dimensional covariates, it is often reasonable to assume that many of these covariates are not relevant for modeling the marginal mean of the response variable, ...
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Regression discontinuity design with covariates
... observed covariates are di¤erently distributed across the threshold, which can lead to spurious estimated e¤ects if these di¤erences are not accounted ...without covariates has recently been studied in ...
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Dummy covariates in CUB models
... dummy covariates within a unique sample while the last one refers to disjoint samples, collected in different times 9 ...relevant covariates is not substantially different with respect to a general ...
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On nonparametric classification with missing covariates
... General procedures are proposed for nonparametric classification in the presence of missing covariates. Both kernel-based imputation as well as Horvitz–Thompson-type inverse weighting approaches are em- ployed to ...
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On categorical time series with covariates
... Likelihood based inference for the models we study can be developed along the lines of previous refer- ences by appealing to the properties of multinomial distribution. The proof of consistency and asymptotic normality ...
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Regression discontinuity design with covariates
... observed covariates X in a fully nonparametric ...without covariates, requiring assumptions that may often be too strong in ...in covariates is important to reduce ...for covariates may also ...
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Semiparametric Estimation with Generated Covariates
... Lemma 1; or Chen, Linton, and Van Keilegom, 2003, Condition (2.6)). The main contribution of our paper is to provide a connection between the extensive literature on estimation and inference in semiparametric models and ...
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