regression models

Variables with a significant univariate relationship were loaded into a series of binary logistic regression models.

Second-order fractional polynomials and random effects meta-regression models were used for modeling the dose-risk relation.

In the multivariate regression models, multicollinearity between the multivariate are very common.

We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) by means of multivariable Cox proportional hazards regression models.

XY data can be modelled using a toolbox of linear regression models, nonlinear regression models, interpolation, or splines.

Regression models were developed for the total sample, by gender and by race.

Finally, Linear regression models between modal properties of the two bridges and temperature are respectively built.

Negative binomial regression models were used to assess trends and associations.

Secondly, we established some regression models for retrieving chlorophyll concentration using spectral data and routine water quality data.

Linear and logistic regression models were constructed examining the relationship between urbanicity and chronic disease risk.

Logistic regression models were used to compute adjusted odds ratios.

Spatial lag model is better than the traditional multiple linear regression models.

Through setting up liner regression models, the paper develops empirical research on institutional investors from two levels.

The randomly weighted least square estimator (RWLSE) for the parametric component in semi-parametric regression models was mainly discussed.

higher blood urea nitrogen and lower serum creatinine were also associated with mortality in logistic regression models.

Regression models showed that Caesarean delivery and delivery at a higher-level facility were associated with higher expenditure in 2007.

conditional logistic regression models.

We used Cox regression models to estimate the risk of cancer and adjust for potential confounding factors.

then, multiple regression models to simulate the demand of potassium fertilizer.

In effect, regression models all fit the same general pattern.

The regression models use the natural log of CEO PAY.

Maximum weighted likelihood estimation of parametric regression models and its asymptotic properties

Asymptotic Properties of Two Steps Estimation for Semiparametric Regression Models

The Existence of the Maximum Likelihood Estimate of the Parameters in Censored Linear Regression Models

Estimations of Density Function of Contaminating Variable in Regression Models for Longitudinal Contaminated Data

EM Algorithm for the Maximum Likelihood Estimate of the Parameters in Censored Linear Regression Models

Statistical Analysis of Heteroscedasticity in Nonlinear Regression Models with Random Weight Function

Parameter Estimations of Semi-Parametric Linear Regression Models Using Simulated Annealing Algorithm

Universal Penalized Least Squares Estimation for Semiparametric Regression Models

The Comparison of the Multivariant Regression Models of Shanghai's and Tianjin's GDP Increases and the Study of Their Development Foreground

Varying-coefficient Regression Models with Different Smoothing Variables

Assessing Proportional Hazards Assumption in Cox Regression Models Using Cubic Spline Functions

Score Tests of Heteroscedasticity in Nonlinear Regression Models with Random Coefficients

Predicting final cost for competitively bid construction projects using regression models

A unified statistical test for correlation structures of the error terms in regression models

Biomass Structure and Its Regression Models of Bambusa wenchouensis Population

An Alternative Estimation for the Scale Parameter in Robust Linear Regression Models

Diagnosis for multiple outliers and robust estimations in linear regression models in medicine

Quantitative Methods for Evaluating the Performance of Regression Models

Robust designs for approximate regression models with correlated errors

Research on improvement of ridge estimation of coefficients in linear regression models

On Parameter Estimation for Varying-coefficient Regression Models

The Regression Models of Principle Component Analysis on In-output Variables in Agriculture

a - optimal design for duality quadratic polynomial regression models in circle region

Recursive Kernel Regression Models and their Application

In their logistic regression models to establish odds ratios (OR), the authors adjusted for demographics;

The Optimization of Nonlinear Regression models in Economic Analysis

Varying-Coefficient Regression Models With Censored Data

A Restricted Least Squares Estimation for Fuzzy Linear Regression Models

The Tree Approach of Linear Regression Models with Categorical Independent Variables

Variable Selection for Censored Regression Models

Application of Methods of Regression Models in Equipment Valuation

geometric properties of ar nonlinear regression models

Rectangular Method in Building Regression Models

Colorimetric Characterization for Scanner Based on Polynomial Regression Models

Research on Fuzzy Switching Regression Models with Outliers

Fields of nonlinear regression models for inversion of satellite data

LAD-based Tests for Linear Hypothesis in Censored Regression Models

Relative efficiency of LSE of over-fitted linear regression models

A Panel Data Method of Correcting the Omitted Variable Bias in Regression Models

Two New Interval-valued Linear Regression Models

Exact Confidence field of Unknown Parameter in linear regression models with t- error

A Study on the Supply of Enterprises Based on Regression Models