I missed the earlier discussion. However, the main point for some students
is that even if the main effects are non-significant, they should be
included in the analysis whenever interactions are included. (More generally
- if n-way interactions are included, then the (n-1)-way interactions should
also be included.) JOHN BIBBY
2009/3/25 Jamie Fagg <[log in to unmask]>
> Dear list,
>
> Thanks to everyone who responded to my query, it was really helpful.
>
> A summary of responses:
>
> Everyone who responded said that it was very much valid to statistically
> test for interactions if one of the main effects was non-significant (this
> was the basis of my initial query - just the naive idea that it might not
> be
> ok for some reason)
>
> Several cited the case (which is also the case in my data), where the main
> effect of var1 is significant in the presence of sex only. This is because
> the effect of var1 is positive for girls and negative for boys and so when
> the sex-adjusted main effect is tested with no interaction these
> correlations cancel each other out.
>
> A second suggestion which also came up referred to the possibility that an
> adjusted main effect could be nonsignificant, but the interaction would
> highlight that the association was significant for one group but not the
> other.
>
> However, perhaps the most important responses for me highlighted that
> implicit in my question was that I was basing a decision of what to test in
> my analysis based on the statistical significance or not of a coefficient.
> All three respondents who raised this pointed out the dangers of this and
> emphasised the importance of making analytical decisions based on logical
> and / or theoretical concerns.
>
> So thanks to everyone for your thoughts, I hope I've done justice to your
> responses.
>
> Jamie
>
> --
> Dept. of Geography, Queen Mary, University of London
> Mile End Rd
> E1 4NS
>
> Tel: 020 7882 5400
>
>
>
>
>
> --
> Dept. of Geography, Queen Mary, University of London
> Mile End Rd
> E1 4NS
>
> Tel: 020 7882 5400
>
--
Cheers JOHN BIBBY
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