[R] How to represent the effect of one covariate on regression results?

[Abby Spurdle]

I'm wondering if you want one of these:
(1) Plots of "Main Effects".
(2) "Partial Residual Plots".

Search for them, and you should be able to tell if they're what you want.

But a word of warning:

Many people (including many senior statisticians) misinterpret this
kind of information.
Because, it's always the effect of xj on Y, while holding the other
variables *constant*.
That's not as simple as it sounds, and people have a tendency of
disregarding the importance of the second half of that sentence, in
their final interpretations.


P.S.
John Fox, announced a package with support for Regression Diagnostics,
about 11 days ago:
https://stat.ethz.ch/pipermail/r-help/2020-September/468609.html

I'm not sure how relevant it is to your question, but I just glanced
at the vignette, and it's pretty slick...




On Tue, Sep 15, 2020 at 1:30 AM Ana Marija <sokovic.anamarija using gmail.com> wrote:
>
> Hello,
>
> I was running association analysis using --glm genotypic from:
> https://www.cog-genomics.org/plink/2.0/assoc with these covariates:
> sex,age,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,TD,array,HBA1C. The
> result looks like this:
>
>     #CHROM    POS    ID    REF    ALT    A1    TEST    OBS_CT    BETA
>   SE    Z_OR_F_STAT    P    ERRCODE
>     10    135434303    rs11101905    G    A    A    ADD    11863
> -0.110733    0.0986981    -1.12193    0.261891    .
>     10    135434303    rs11101905    G    A    A    DOMDEV    11863
> 0.079797    0.111004    0.718868    0.472222    .
>     10    135434303    rs11101905    G    A    A    sex=Female
> 11863    -0.120404    0.0536069    -2.24605    0.0247006    .
>     10    135434303    rs11101905    G    A    A    age    11863
> 0.00524501    0.00391528    1.33963    0.180367    .
>     10    135434303    rs11101905    G    A    A    PC1    11863
> -0.0191779    0.0166868    -1.14928    0.25044    .
>     10    135434303    rs11101905    G    A    A    PC2    11863
> -0.0269939    0.0173086    -1.55957    0.118863    .
>     10    135434303    rs11101905    G    A    A    PC3    11863
> 0.0115207    0.0168076    0.685448    0.493061    .
>     10    135434303    rs11101905    G    A    A    PC4    11863
> 9.57832e-05    0.0124607    0.0076868    0.993867    .
>     10    135434303    rs11101905    G    A    A    PC5    11863
> -0.00191047    0.00543937    -0.35123    0.725416    .
>     10    135434303    rs11101905    G    A    A    PC6    11863
> -0.0103309    0.0159879    -0.646172    0.518168    .
>     10    135434303    rs11101905    G    A    A    PC7    11863
> 0.00790997    0.0144025    0.549207    0.582863    .
>     10    135434303    rs11101905    G    A    A    PC8    11863
> -0.00205639    0.0142709    -0.144096    0.885424    .
>     10    135434303    rs11101905    G    A    A    PC9    11863
> -0.00873771    0.0057239    -1.52653    0.126878    .
>     10    135434303    rs11101905    G    A    A    PC10    11863
> 0.0116197    0.0123826    0.938388    0.348045    .
>     10    135434303    rs11101905    G    A    A    TD    11863
> -0.670026    0.0962216    -6.96337    3.32228e-12    .
>     10    135434303    rs11101905    G    A    A    array=Biobank
> 11863    0.160666    0.073631    2.18205    0.0291062    .
>     10    135434303    rs11101905    G    A    A    HBA1C    11863
> 0.0265933    0.00168758    15.7583    6.0236e-56    .
>     10    135434303    rs11101905    G    A    A    GENO_2DF    11863
>   NA    NA    0.726514    0.483613    .
>
> This results is shown just for one ID (rs11101905) there is about 2
> million of those in the resulting file.
>
> My question is how do I present/plot the effect of covariate "TD" in
> the example it has "P" equal to 3.32228e-12 for all IDs in the
> resulting file so that I show how much effect covariate "TD" has on
> the analysis. Should I run another regression without covariate "TD"
> and than do scatter plot of P values with and without "TD" covariate
> or there is a better way to do this from the data I already have?
>
> Thanks
> Ana
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.