Marginal Regression for a Bi-variate Response with Diabetes Mellitus Study

Binary Regression With a Misclassified Response Variable in Diabetes Data

Objectives: The categorical data analysis is very important in statistics and medical sciences. When the binary response variable is misclassified, the results of fitting the model will be biased in estimating adjusted odds ratios.  The present study aimed to use a method to detect and correct misclassification error in the response variable of Type 2 Diabetes Mellitus (T2DM), applying binary ...

prevalence of atopic dermatitis in children with type 1 diabetes mellitus in southeastern of iran (kerman province): a case-control study

چکیده ندارد.

A Note On Marginal Linear Regression With Correlated Response Data

Correlated response data often arise in longitudinal and familial studies The marginal regression model and its associated generalized estimating equation GEE method are becoming more and more popular in handling such data Pepe and Anderson pointed out that there is an important yet implicit assumption behind the marginal model and GEE If the assumption is violated and a non diagonal working co...

Use of Two Smoothing Parameters in Penalized Spline Estimator for Bi-variate Predictor Non-parametric Regression Model

Penalized spline criteria involve the function of goodness of fit and penalty, which in the penalty function contains smoothing parameters. It serves to control the smoothness of the curve that works simultaneously with point knots and spline degree. The regression function with two predictors in the non-parametric model will have two different non-parametric regression functions. Therefore, we...

Inflation, Growth And Their Uncertainties: A Bi-variate GARCH Evidence for Iran