Peduzzi P.N., et. al (1995). “The importance of events per independent variable in multivariable analysis, II: accuracy and precision of regression estimates.”Journal of Clinical Epidemiology48:1503–10. Peduzzi P.N., et. al (1996). “A simulation study of the number of events per vari...
Analysis of U.S. Fresh Produce Users 2006. "Does Price or Income Affect Organic Choice? Analysis of U.S. Fresh Produce Users". Journal of Agricultural and Applied Economics 41 (3): 731-... TA Smith,CL Huang,BH Lin - 《Journal of Agricultural & Applied Economics》 被引量: 107发表: ...
A linear regression analysis was performed to study the association between GDP per capita of a journal's country of publication and IF. When excluding 2 outliers, there was a small but statistically significant positive correlation between GDP per capita and journal IF (β = 0.021, P = 0.03,...
Regression analysis is an important statistical method that is commonly used to determine the relationship between several factors and disease outcomes or to identify relevant prognostic factors for diseases [1]. This editorial will acquaint readers with the basic principles of and an approach to ...
The path analytic method is an extension of multiple regression analysis and estimates the magnitude and strength of effects within a hypothesized causal system. From: Encyclopedia of Social Measurement, 2005 About this pageSet alert Also in subject area: MathematicsDiscover other topics On this page...
Wheat From Chaff: Meta-Analysis As Quantitative Literature Review. :This article discusses the potential of meta-analysis to summarize, evaluate and analyze empirical economic research. Meta-analysis is a body of statistic... Stanley,D T. - 《Journal of Economic Perspectives》 被引量: 1092发表:...
Measures of cepstral peak prominence, using the smoothing algorithm and linear regression analysis software developed by Hillenbrand, have been shown to be... YD Heman-Ackah - 《Journal of Voice》 被引量: 22发表: 2004年 Statistical model for the random cyclic strain--life relations of 1Cr18Ni9Ti...
When it comes to using and interpreting the constant in a regression model, you should almost always include the constant in your regression model even though it is almost never worth interpreting. The key benefit of regression analysis is determining how changes in the independent variables are as...
Abstract Linear regression analysis is one of the most important statistical methods. It examines the linear relationship between a metric-scaled dependent variable (also called endogenous, explained, response, or predicted variable) and one or more metric-scaled independent variables (also called exogeno...
View article Related terms: Least Squares Method Principal Components Dependent Variable Covariance Matrix Logistic Regression Regression Equation Regularization Explanatory Variable Selection Operator maximum-likelihood View all Topics Recommended publications Computational Statistics & Data Analysis Journal Computers...