$ Weight : num 63 64 36 46 67 40 25 30 36 33 ...
$ BMI : num NA NA NA NA NA NA NA NA NA NA ...
$ YoYo : int 80 80 160 160 160 160 160 160 160 160 ...
John Kane
Kingston ON Canada
-Original Message-
From: joshuamichaeldi...@gmail.com
Sent: Mon, 27 Apr 2015 23:35:13 +0100
NA NA NA ...
>> $ Weight : num 63 64 36 46 67 40 25 30 36 33 ...
>> $ BMI : num NA NA NA NA NA NA NA NA NA NA ...
>> $ YoYo: int 80 80 160 160 160 160 160 160 160 160 ...
>>
>> John Kane
>> Kingston ON Canada
>>
>> -Original Message--
200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L,
>
> 200L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L,
>
> 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L,
>
> 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L, 240L,
>
> 240L, 2
um NA NA NA NA NA NA NA NA NA NA ...
$ YoYo: int 80 80 160 160 160 160 160 160 160 160 ...
John Kane
Kingston ON Canada
-Original Message-
From: joshuamichaeldi...@gmail.com
Sent: Mon, 27 Apr 2015 23:35:13 +0100
To: jrkrid...@inbox.com
Subject: Re: [R] Help Interpreting Linear Mixed
>
> Just a sample is usually fine. As long as it cover a representative
> (must be time for dinner---I was going to type reprehensibe) sample of the
> data then something like dput(head(mydata, 100) ) works well.
>
> Kingston ON Canada
>
> -Original Message-
&
...@gmail.com
Sent: Mon, 27 Apr 2015 21:30:39 +0100
To: li...@dewey.myzen.co.uk
Subject: Re: [R] Help Interpreting Linear Mixed Model
Apologies for my ignorance!
Thierry - thank you for the reading. I'll look into those ASAP!
John - The data set I have is quite large, when using the dput() comman
gt; variable) do better
>
>
> On 27/04/2015 12:42, John Kane wrote:
>
>>
>>
>> John Kane
>> Kingston ON Canada
>>
>>
>> -Original Message-
>>> From: joshuamichaeldi...@gmail.com
>>> Sent: Mon, 27 Apr 2015 08:54:51 +0100
>
: thierry.onkel...@inbo.be
Subject: Re: [R] Help Interpreting Linear Mixed Model
Hello Thierry,
No, this isn't homework. Not that young unfortunately.
A few years ago a friend of mine and her daughter were neck-in-neck on who got their Ph.D
first. What's this "not that young" busi
John Kane
Kingston ON Canada
> -Original Message-
> From: joshuamichaeldi...@gmail.com
> Sent: Mon, 27 Apr 2015 08:54:51 +0100
> To: thierry.onkel...@inbo.be
> Subject: Re: [R] Help Interpreting Linear Mixed Model
>
> Hello Thierry,
>
> No, this isn
Hello Josh,
One is never too old to study ;-)
Your question seems quite broad. You might be better off to read some books
on mixed models (e.g. Pinheiro & Bates (2000) or Zuur et al (2009)) or try
to find a local statistician. Email is not a suitable medium to teach
statistics.
Note that r-sig-m
Hello Thierry,
No, this isn't homework. Not that young unfortunately.
Josh
> On 27 Apr 2015, at 08:06, Thierry Onkelinx wrote:
>
> Dear Josh,
>
> Is this homework? Because the list has a no homework policy.
>
> Best regards,
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek
Dear Josh,
Is this homework? Because the list has a no homework policy.
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
Belg
Hello!
Very new to R (10 days), and I've run the linear mixed model, below.
Attempting to interpret what it means... What do I need to look for?
Residuals, correlations of fixed effects?!
How would I look at very specific interactions, such as PREMIER_LEAGUE
(Level) 18 (AgeGr) GK (Position) mean
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