Criticality of predictors in multiple regression
نویسندگان
چکیده
منابع مشابه
Criticality of predictors in multiple regression.
A new method is proposed for comparing all predictors in a multiple regression model. This method generates a measure of predictor criticality, which is distinct from and has several advantages over traditional indices of predictor importance. Using the bootstrapping (resampling with replacement) procedure, a large number of samples are obtained from a given data set which contains one response...
متن کاملNonparametric Kernel Regression with Multiple Predictors and Multiple Shape Constraints
Nonparametric smoothing under shape constraints has recently received much well-deserved attention. Powerful methods have been proposed for imposing a single shape constraint such as monotonicity and concavity on univariate functions. In this paper, we extend the monotone kernel regression method in Hall and Huang (2001) to the multivariate and multi-constraint setting. We impose equality and/o...
متن کاملMultiple regression analysis of diagnostic predictors in optic nerve disease.
Demyelination is assumed to be the cause of the majority of cases of isolated optic neuritis. Because of the importance of establishing the presence of optic nerve dysfunction in patients suspected of having multiple sclerosis several new indices of optic nerve conduction have been reported including the visual evoked potential, the edge-light pupil cycle time, and the Pulfrich test. These meas...
متن کاملSome Modifications to Calculate Regression Coefficients in Multiple Linear Regression
In a multiple linear regression model, there are instances where one has to update the regression parameters. In such models as new data become available, by adding one row to the design matrix, the least-squares estimates for the parameters must be updated to reflect the impact of the new data. We will modify two existing methods of calculating regression coefficients in multiple linear regres...
متن کاملDichotomizing continuous predictors in multiple regression: a bad idea.
In medical research, continuous variables are often converted into categorical variables by grouping values into two or more categories. We consider in detail issues pertaining to creating just two groups, a common approach in clinical research. We argue that the simplicity achieved is gained at a cost; dichotomization may create rather than avoid problems, notably a considerable loss of power ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: British Journal of Mathematical and Statistical Psychology
سال: 2001
ISSN: 0007-1102
DOI: 10.1348/000711001159483