1. comparing strength of effects between models (different dependent var, same independent var)

Dear newsgroup members,

We have a problem comparing the strength of regression coefficients of the

same independent variable in models with different dependent variables.

Below I will show two (related) examples:

Example 1.

Cross-sectional design. Dependent variables: two speed tasks (number of

seconds needed is recorded; the lower, the better, the faster) and tasks

differ in complexity/difficulty. Independent variable: age (0: young and 1:

old). Question: do older people particularly differ from younger people in

the difficult task (more so than in the easy task)?

Example 2.

Cross-sectional design. Dependent variables: one speed task (number of

seconds needed is recorded; the lower, the better, the faster) and a memory

task (number of words reproduced after presentation; the higher, the better

(the memory)). Independent variable: age (0: young and 1: old). Question: do

older people particularly differ from younger people in the speed task (more

so than in the easy task)?

How can these effects of age be compared? In the first example both

dependent variables are in seconds, in the second the scales differ

completely. It seems to me that standardisation of at least the dependent

variable is needed? But how to test for a significant difference in the

effect of age.

Some have suggested MANOVA or GLM repeated measures designs. Is this the way

to go? And, foremost, should at least the dependent variable be standardised

then?

Thank you for any information.

Best regards,

Hans Bosma

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