[R] Question About lm()

[David Winsemius]

The models are NOT equivalent. Why would you’ll think they were?

— 
David

Sent from my iPhone

> On Feb 9, 2022, at 11:10 PM, Bromaghin, Jeffrey F via R-help <r-help using r-project.org> wrote:
> 
> Hello,
> 
> I was constructing a simple linear model with one categorical (3-levels) and one quantitative predictor variable for a colleague. I estimated model parameters with and without an intercept, sometimes called reference cell coding and cell means coding.
> 
> Model 1: yResp ~ -1 + xCat + xCont
> Model 2: yResp ~ xCat + xCont
> 
> These models are equivalent and the estimated coefficients come out fine, but the R-squared and F statistics returned by summary() differ markedly. I spent some time looking at the code for both lm() and summary.lm() but did not find the source of the difference. aov() and anova() results also differ, so I suspect the issue involves how the sums of squares are being computed. I've also spent some time trying to search online for information on this, without success. I haven't used lm() for quite a while, but my memory is that these differences didn't occur in the distant past when I was teaching.
> 
> Thanks in advance for any insights you might have,
> Jeff
> 
> Jeffrey F. Bromaghin
> Research Statistician
> USGS Alaska Science Center
> 907-786-7086
> Jeffrey Bromaghin, Ph.D. | U.S. Geological Survey (usgs.gov)<https://www.usgs.gov/staff-profiles/jeffrey-bromaghin>
> Ecosystems Analytics | U.S. Geological Survey (usgs.gov)<https://www.usgs.gov/centers/alaska-science-center/science/ecosystems-analytics>
> 
> 
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> 
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