# partial regression coefficient

## partial regression coefficient

[′pär·shəl ri′gresh·ən ‚kō·ə‚fish·ənt]
(statistics)
Statistics in the population multiple linear regression equation that indicate the effect of each independent variable on the dependent variable with the influence of all the remaining variables held constant; each coefficient is the slope between the dependent variable and each of the independent variables.
References in periodicals archive ?
Condition indexes contribute to the reliability of the diagnosis, indicating equally the proportion of variance for each partial regression coefficient that is explained by each dimension or factor.
05 Dependent variable is the maize out put (in 50 kg bags) B: Partial regression coefficient Table 4: The relationship between adoption and different independent variables Variable Age Duration Training Household size Coefficient -- -0.
The inter-individual variation in behaviour, scored as behavioural similarity between each pair of individuals, is non-independent, so Whitehead addresses the significance of the partial regression coefficient by bootstrapping a distribution of partial regression coefficients, where the similarity scores of the independent variables are randomized across individuals.
When an independent variable has very high correlations with other independent variables, the estimate of the partial regression coefficient may become unreliable.
The value in parenthesis underneath each variable is the F-test of the null hypothesis that the variable's partial regression coefficient is zero against the two-sided alternative that it is not zero.
In the case of two correlated independent variables, for instance, the bias caused by leaving out one variable will be equal to the product of the partial regression coefficient of the omitted variable had it been in the equation and the simple regression coefficient of the omitted variable on the remaining independent variable.
This specification means that the estimated partial regression coefficient on the income variable is an estimate of the income elasticity of the demand for lottery products.
In OLS regression the partial slope partial regression coefficient indicates the change in the expected value of the dependent variable for a one-unit change in a given predictor, while the rest of the predictor variables are held constant.
The best example is multiple regression analysis in which the weight for each of these independent variables known as a partial regression coefficient is computed.
When variable Z was regressed on X and Y they found that the partial regression coefficient of Z on X, controlling for Y, was not statistically significant at the .
Partial regression coefficient for an independent variable denotes the amount of response to a dependent variable while the rest of the independent variables were held constant.
Path analysis is a standardized partial regression coefficient measuring the direct influence of one variable upon the other and permits separation of correlation coefficients into components of direct and indirect effects (Saleem et al.
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