Plot linear model, what is "adjusted whole model"

I have given some data of children: Age, weight, height.

I want to fit the following model

lm = fitlm(data,'Weight~Age+Height+Height^2+Height^3+Height^4');

By looking at the coefficients table

Estimate         SE         tStat       pValue  
                   __________    __________    _______    __________

    (Intercept)        50.645        48.143      1.052       0.29388
    Age               0.42242      0.040691     10.381    4.7207e-21
    Height            -6.6635        5.3439    -1.2469       0.21365
    Height^2          0.37769       0.21575     1.7506      0.081312
    Height^3       -0.0084367     0.0037419    -2.2547      0.025068
    Height^4       6.5841e-05    2.3519e-05     2.7996     0.0055389

I see, that I might drop the variable "Height".

So far no problem, but I would like to visualize in some way, that dropping Height ist not bad or maybe is even beneficial.

Indeed matlab gives me easy acces to a visualisation, via

    plot(lm)

Since the data is 6 dimensional I wonder, how matlab does project this in 2-dim.

Especially I do not know what is meant by "Adjusted whole model".

On my search for an answer I was directed to

https://stats.stackexchange.com/questions/125561/what-does-an-added-variable-plot-partial-regression-plot-explain-in-a-multiple

where it was explained, that matlab uses the "Frisch–Waugh–Lovell theorem" in some way.

But in this thread my question was not adressed, as far as I realize.

Every help would greatly be appreciated,

thank you in advance :)

Answer 1

[Benjamin]

Dear Tobias,

Thanks for asking this question, which is mine too. But it's interesting you didn't get any response. Since I see you posted this question a few months ago, I wondered if you finally figured out the meaning of "Adjusted Whole Model"? If so, I appreciate it if you share that with me.

Regards,

Benjamin

([e-mail])