[R-sig-ME] fixed-effect model matrix is rank deficient so dropping 1 column / coefficient

[Thierry Onkelinx]

Note that you should only use the new interaction variable to avoid the
rank deficiency (no x3).

lmer(outcome ~ YLD0 + YLD1 + YLD2 + YLD3 + YLD4 + SEV1 + SEV2 + SEV3 + SEV4
+ SEV5 + SEV6 + x0*x1 + x2 + x3_1 + x3_2 + year + (1|id), data = data2Sh)

ir. Thierry Onkelinx
Statisticus / Statistician

Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx using inbo.be
Havenlaan 88 bus 73, 1000 Brussel
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
///////////////////////////////////////////////////////////////////////////////////////////

<https://www.inbo.be>


Op wo 3 mrt. 2021 om 14:45 schreef Thierry Onkelinx <
thierry.onkelinx using inbo.be>:

> Dear Iago,
>
> The reference category of x0 (x0 == "0") contains only zeros for x3. This
> is why you get the rank deficiency. The solution is to create the
> meaningful interactions as new variables.
>
> data2Sh$x3_1 <- ifelse(data2Sh$x0 == "1", data2Sh$x3, 0)
> data2Sh$x3_2 <- ifelse(data2Sh$x0 == "2", data2Sh$x3, 0)
> lmer(outcome ~ YLD0 + YLD1 + YLD2 + YLD3 + YLD4 + SEV1 + SEV2 + SEV3 +
> SEV4 + SEV5 + SEV6 + x0*x1 + x2 + x3 + x3_1 + x3_2 + year + (1|id), data =
> data2Sh)
>
> Best regards,
>
> ir. Thierry Onkelinx
> Statisticus / Statistician
>
> Vlaamse Overheid / Government of Flanders
> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND
> FOREST
> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
> thierry.onkelinx using inbo.be
> Havenlaan 88 bus 73, 1000 Brussel
> 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
>
> ///////////////////////////////////////////////////////////////////////////////////////////
>
> <https://www.inbo.be>
>
>
> Op wo 3 mrt. 2021 om 14:23 schreef IAGO GINÉ VÁZQUEZ <i.gine using pssjd.org>:
>
>> Dear Thierry,
>>
>> Thank you for the ask. I send you the data attached. The model I am using
>> is
>>
>> lmer(outcome ~ YLD0 + YLD1 + YLD2 + YLD3 + YLD4 + SEV1 + SEV2 + SEV3 +
>> SEV4 + SEV5 + SEV6 + x0*x1 + x2 + x0*x3 + year + (1|id), data=data2Sh).
>>
>> The factor variable is x0. The dropped coefficient is x0==2 : x3
>>
>> Let me know any other information I can give.
>>
>> Thank you!
>>
>>
>> *Iago *
>> ------------------------------
>> *De:* Thierry Onkelinx <thierry.onkelinx using inbo.be>
>> *Enviat el:* dimecres, 3 de març de 2021 13:30
>> *Per a:* IAGO GINÉ VÁZQUEZ <i.gine using pssjd.org>
>> *A/c:* r-sig-mixed-models using r-project.org <r-sig-mixed-models using r-project.org
>> >
>> *Tema:* Re: [R-sig-ME] fixed-effect model matrix is rank deficient so
>> dropping 1 column / coefficient
>>
>> Dear Iago,
>>
>> We only have your description of the data. It would be easier for us to
>> help you if you provide a small dataset that illustrates the structure in
>> your data and how you use the data in your model.
>>
>> Best regards,
>>
>> Thierry
>>
>> ir. Thierry Onkelinx
>> Statisticus / Statistician
>>
>> Vlaamse Overheid / Government of Flanders
>> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
>> AND FOREST
>> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
>> thierry.onkelinx using inbo.be
>> Havenlaan 88 bus 73, 1000 Brussel
>> 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
>>
>> ///////////////////////////////////////////////////////////////////////////////////////////
>>
>> <https://www.inbo.be>
>>
>>
>> Op wo 3 mrt. 2021 om 13:11 schreef IAGO GINÉ VÁZQUEZ <i.gine using pssjd.org>:
>>
>> Dear all,
>>
>> I have 3 related questions, probably already answered, but which I cannot
>> find:
>>
>> When computing a model with lmer I get the message
>>
>> fixed-effect model matrix is rank deficient so dropping 1 column /
>> coefficient
>>
>> Then, my questions are, first, how can I see/compute/get the rank
>> deficient fixed-effect model matrix, second how is that matrix computed,
>> and third (these actually are 2 questions), if my model is yet valid (is
>> it?) how can the dropped fixed effect explained in the results of a paper.
>>
>> In the example in ?fixef
>> fm2 <- lmer(Reaction ~ Days + Days2 + (1|Subject),
>>             data=transform(sleepstudy,Days2=Days))
>> fixef(fm2,add.dropped=TRUE)
>>
>> the problem happens because 2 independent variables are equal, but in my
>> model the numeric independent variables are not so highly correlated. In
>> fact the problem happens with the interaction between a factor and a
>> numeric variable, since it is one of the categories of the factor
>> interacting with the numeric, which is dropped.
>>
>> Thank you and stay safe!
>>
>>
>> Iago
>>
>>
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>>
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