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| = How do I compute the standard error of ''beta'' in a linear regression in SPSS?= | = How do I compute the standard error (s.e.) of ''beta'' in a linear regression in SPSS? = |
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| Two estimates of regression coefficients are given in SPSS. These are called B and beta and correspond to using raw score (response and predictor variables) and z-scored response and predictor variables respectively. | Two estimates of covariate regression coefficients are given in SPSS. These are called B and beta and correspond to using raw score (response and predictor variables) and z-scored response and predictor variables respectively. |
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| Alternatively (see for example Cohen and Cohen, 1983), | Alternatively (see for example Cohen and Cohen, 1983, p.100), you can compute standard errors using the standard deviations (s.ds) of the response and covariates. |
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| $$ \mbox{s.e.(beta) = s.e.(B)} \frac{\mbox{s.d.(covariate)}}{\mbox{s.d.(response)}}$$ | $$ \mbox{s.e.(beta) of a covariate = s.e.(B) of covariate} \frac{\mbox{s.d.(covariate)}}{\mbox{s.d.(response)}}$$ |
How do I compute the standard error (s.e.) of ''beta'' in a linear regression in SPSS?
Two estimates of covariate regression coefficients are given in SPSS. These are called B and beta and correspond to using raw score (response and predictor variables) and z-scored response and predictor variables respectively.
The Descriptives procedure [:FAQ/zscore: may be used] to obtain z-scores.
Alternatively (see for example Cohen and Cohen, 1983, p.100), you can compute standard errors using the standard deviations (s.ds) of the response and covariates.
$$ \mbox{s.e.(beta) of a covariate = s.e.(B) of covariate} \frac{\mbox{s.d.(covariate)}}{\mbox{s.d.(response)}}$$
Reference
Cohen J. and Cohen P. (1983) Applied multiple regression/correlation analysis for the behavioral sciences Second Edition. lawrence Erlbaum: Hillsdale, NJ.