Dear Stathis,

I recommend that you try to get some advice from a local statistician or read 
an introductory book on statistics. This kind of question is beyond the scope 
of a mailing list.

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and 
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
thierry.onkel...@inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more than 
asking him to perform a post-mortem examination: he may be able to say what the 
experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure 
that a reasonable answer can be extracted from a given body of data.
~ John Tukey


-----Oorspronkelijk bericht-----
Van: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens 
Stathis Kamperis
Verzonden: donderdag 8 augustus 2013 12:43
Aan: r-help@r-project.org
Onderwerp: [R] Varying statistical significance in estimates of linear model

Hi everyone,

I have a response variable 'y' and several predictor variables 'x_i'.
I start with a linear model:

m1 <- lm(y ~ x1); summary(m1)

and I get a statistically significant estimate for 'x1'. Then, I modify my 
model as:

m2 <- lm(y ~ x1 + x2); summary(m2)

At this moment, the estimate for x1 might become non-significant while the 
estimate of x2 significant.

As I add more predictor variables (or interaction terms), the estimates for 
which I get a statistically significant result vary. So sometimes x1, x2, x6 
are significant, while others, x2, x4, x5 are.

It seems to me that I could tweak my model in such a way (by adding/removing 
predictor variables or "suitable" interaction terms) that I could "prove" 
whatever I'd like to prove.

What is the proper methodology involved here ? What do you people do in such 
cases ? I can provide the data if anyone cares and would like to have a look at 
them.

Best regards,
Stathis Kamperis

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