This study describes a new graphical method for assessing and characterizing e$ect modi%cation by a matching covariate in matched case–control studies. This method to understand e$ect modi%cation is based on a semiparametric model using a varying coe2cient model. The method allows for nonparametric relationships between e$ect modi%cation and other covariates, or can be useful in suggesting para...

Abstract In some applications, acquiring covariates comes at a cost which is not negligible. For example in the medical domain, order to classify whether patient has diabetes or not, measuring glucose tolerance can be expensive. Assuming that of each covariate, and misclassification specified by user, our goal minimize (expected) total classification, i.e. plus acquired covariates. We formalize...

We consider a failure hazard function, conditional on a time-independent covariate Z, given by ηγ0(t)fβ0(Z). The baseline hazard function ηγ0 and the relative risk fβ0 both belong to parametric families with θ = (β, γ0)> ∈ R. The covariate Z has an unknown density and is measured with an error through an additive error model U = Z + ε where ε is a random variable, independent from Z, with known...

Conclusions In the proportional hazards model the effect of a covariate is assumed to be time-invariant. In this paper a graphical method based on a linear regression model (LRM) is used to test whether this assumption is realistic. The variation in the effect of a covariate is plotted against time. The slope of this plot indicates the nature of the influence of a covariate over time. A covaria...

the fixed regression test-day model (frm) and random regression test-day model (rrm) for genetic evaluation of milk yield trait of dairy cattle in khorasan razavi province were studied. breeding values and genetic parameters of milk yield trait from two models were compared. a total of 164391 monthly test day milk records (three times milking per day) obtained from 19217 holstein cows distribut...

In recent years, some researches have been done on simultaneous monitoring of multivariate process mean vector and covariance matrix. However, the effect of measurement error, which exists in many practical applications, on the performance of these control charts is not well studied. In this paper, the effect of measurement error with linearly increasing variance on the performance of ELR contr...

This paper studies Cox‘s proportional hazards model under covariate measurement error. Nakamura‘s (1990) methodology of corrected log-likelihood will be applied to the so called Breslow likelihood, which is, in the absence of measurement error, equivalent to partial likelihood. For a general error model with possibly heteroscedastic and non-normal additive measurement error, corrected estimator...

Discrete survival models have been extended in several ways. More flexible models are obtained by including time-varying coefficients and covariates which determine the hazard rate in an additive but not further specified form. In this paper, a general model is considered which comprises both types of covariate effects. An additional extension is the incorporation of smooth interaction between ...