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Re: st: My ANOVA and regression results don't agree
From
David Hoaglin <[email protected]>
To
[email protected]
Subject
Re: st: My ANOVA and regression results don't agree
Date
Wed, 8 Jan 2014 13:44:32 -0500
Jess,
Your description of the boxplots is encouraging, but you have not
given much information about your outcome variable (e.g., range of
possible values, such as 0 to 100). You didn't comment on skewness,
so it may be reasonable to use ANOVA or regression.
If you used random assignment separately for the women and the men,
you should at least have balance (or near-balance) within sex. That
structure, however, is not the usual 2-way ANOVA, which has the same
number of observations in each cell. Thus, in the ANOVA you would
want to look at the mean square for adcontent after you have accounted
for variation associated with sex. The corresponding regression
"automatically" adjusts for the contribution of sex.
I don't recall from earlier messages whether the interaction of
adcontent and sex is significant. The analysis is simpler if you can
omit the interaction from your model. Then you can compare the
effects of the levels of adcontent after adjusting for the
contribution of sex (e.g., look at differences among the coefficients
for adcontent). If the interaction is significant, you are limited to
comparing the effects of adcontent within each sex separately.
David Hoaglin
On Wed, Jan 8, 2014 at 11:46 AM, Pepper, Jessica <[email protected]> wrote:
> The boxplots show similar distributions (median, size of quartile, and max value) for 4 of the 6 combinations. The other 2 are similar to one another.
> Also, my data are not balanced; although there was random assignment to ad type, more women took the survey than men. In other aspects of my analysis (survey results), I am weighting my results to reflect this, but I was not planning to do this in the experiment.
> Do these 2 aspects (distribution of DV and lack of balance) change the ANOVA/regression situation?
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