[R] missing data

[wilquin Minaya]

 
  hi
 
  I would like to know how I can complete those missing data from these 
programs:
 
program number one
  
DATOS2 <- sin(seq(1,20,0.1))
> DATOS2[103] <- NA
> DATOS2[65] <- NA
> DATOS2[134] <- NA
 
 
  this is the other one
 
> data(pressure)
> DATOS3 <- pressure
> DATOS3[4,1] <- NA
> DATOS3[14,1:2] <- c(NA,NA)
> DATOS3[17,2] <- NA
 
 

 
_


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[R] Missing data

[David Kaplan]

Hi all,

I'm looking for a contributed package that can provide a detailed 
account of missing data patterns and perhaps also provide imputation 
procedures, such as mean imputation or hot deck imputation and the like. 
  Is there anything out there?

Thanks in advance,

David


-- 
===
David Kaplan, Ph.D.
Professor
Department of Educational Psychology
University of Wisconsin - Madison
Educational Sciences, Room, 1061
1025 W. Johnson Street
Madison, WI 53706

email: [EMAIL PROTECTED]
homepage: http://www.education.wisc.edu/edpsych/facstaff/kaplan/kaplan.htm
Phone: 608-262-0836

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[R] missing data

[genomenet]

Hi There,

Will somebody know if there is a function in R which can compute the
proximity from an incomplete data matrix?

Or any other software which can do this?

Thank you.

Van

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Re: [R] Missing data

[Bert Gunter]

Please use R's existing search tools before posting:

RsiteSearch("imputation")
RsiteSearch("missing data imputation") 

 etc.

Bert Gunter
Genentech Nonclinical Statistics


-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of David Kaplan
Sent: Tuesday, September 11, 2007 2:36 PM
To: [EMAIL PROTECTED]
Subject: [R] Missing data

Hi all,

I'm looking for a contributed package that can provide a detailed 
account of missing data patterns and perhaps also provide imputation 
procedures, such as mean imputation or hot deck imputation and the like. 
  Is there anything out there?

Thanks in advance,

David


-- 
===
David Kaplan, Ph.D.
Professor
Department of Educational Psychology
University of Wisconsin - Madison
Educational Sciences, Room, 1061
1025 W. Johnson Street
Madison, WI 53706

email: [EMAIL PROTECTED]
homepage: http://www.education.wisc.edu/edpsych/facstaff/kaplan/kaplan.htm
Phone: 608-262-0836

__
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Re: [R] Missing data

[David Kaplan]

I did. If you don't want to answer, then your unhelpful suggestions to 
yourself.


===
David Kaplan, Ph.D.
Professor
Department of Educational Psychology
University of Wisconsin - Madison
Educational Sciences, Room 1061
1025 W. Johnson Street
Madison, WI 53706

email: [EMAIL PROTECTED]
Web:   http://www.education.wisc.edu/edpsych/facstaff/kaplan/kaplan.htm
Phone: 608-262-0836
Fax:   608-262-0843
===


Bert Gunter wrote:
> Please use R's existing search tools before posting:
> 
> RsiteSearch("imputation")
> RsiteSearch("missing data imputation") 
> 
>  etc.
> 
> Bert Gunter
> Genentech Nonclinical Statistics
> 
> 
> -Original Message-
> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
> Behalf Of David Kaplan
> Sent: Tuesday, September 11, 2007 2:36 PM
> To: [EMAIL PROTECTED]
> Subject: [R] Missing data
> 
> Hi all,
> 
> I'm looking for a contributed package that can provide a detailed 
> account of missing data patterns and perhaps also provide imputation 
> procedures, such as mean imputation or hot deck imputation and the like. 
>   Is there anything out there?
> 
> Thanks in advance,
> 
> David
> 
>

__
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Re: [R] Missing data

[Rolf Turner]

On 12/09/2007, at 11:33 AM, David Kaplan wrote:

> I did. If you don't want to answer, then your unhelpful suggestions to
> yourself.


This is uncalled for.  Bert Gunter's response was perfectly reasonable.
Read the posting guide.

cheers,

Rolf Turner


> == 
> =
> David Kaplan, Ph.D.
> Professor
> Department of Educational Psychology
> University of Wisconsin - Madison
> Educational Sciences, Room 1061
> 1025 W. Johnson Street
> Madison, WI 53706
>
> email: [EMAIL PROTECTED]
> Web:   http://www.education.wisc.edu/edpsych/facstaff/kaplan/ 
> kaplan.htm
> Phone: 608-262-0836
> Fax:   608-262-0843
> == 
> =
>
>
> Bert Gunter wrote:
>> Please use R's existing search tools before posting:
>>
>> RsiteSearch("imputation")
>> RsiteSearch("missing data imputation")
>>
>>  etc.
>>
>> Bert Gunter
>> Genentech Nonclinical Statistics
>>
>>
>> -Original Message-
>> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] 
>> project.org] On
>> Behalf Of David Kaplan
>> Sent: Tuesday, September 11, 2007 2:36 PM
>> To: [EMAIL PROTECTED]
>> Subject: [R] Missing data
>>
>> Hi all,
>>
>> I'm looking for a contributed package that can provide a detailed
>> account of missing data patterns and perhaps also provide imputation
>> procedures, such as mean imputation or hot deck imputation and the  
>> like.
>>   Is there anything out there?
>>
>> Thanks in advance,
>>
>> David
>>
>>
>
> __
> R-help@r-project.org mailing list
> 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.


##
Attention:\ This e-mail message is privileged and confidenti...{{dropped}}

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Re: [R] Missing data

[Bill Pikounis]

David,
Frank Harrell's pair of packages Hmisc and Design has some functions
for tabulating, visualizing, and accounting for missing data.  I
recommend them as one avenue to investigate. Frank's companion book
"Regression Modeling Strategies" covers their use in-depth.

Hope that helps,
Bill

___
Bill Pikounis
 Statistician

On 9/11/07, David Kaplan <[EMAIL PROTECTED]> wrote:
> Hi all,
>
> I'm looking for a contributed package that can provide a detailed
> account of missing data patterns and perhaps also provide imputation
> procedures, such as mean imputation or hot deck imputation and the like.
>   Is there anything out there?
>
> Thanks in advance,
>
> David
>
>
> --
> ===
> David Kaplan, Ph.D.
> Professor
> Department of Educational Psychology
> University of Wisconsin - Madison
> Educational Sciences, Room, 1061
> 1025 W. Johnson Street
> Madison, WI 53706
>
> email: [EMAIL PROTECTED]
> homepage: http://www.education.wisc.edu/edpsych/facstaff/kaplan/kaplan.htm
> Phone: 608-262-0836
>
> __
> R-help@r-project.org mailing list
> 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.
>


-- 
Bill Pikounis
Statistician

__
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Re: [R] Missing data

[James Reilly]

The mice package might also be useful, especially the md.pattern function:
http://finzi.psych.upenn.edu/R/library/mice/html/md.pattern.html

James
-- 
James Reilly
Department of Statistics, University of Auckland
Private Bag 92019, Auckland, New Zealand

On 12/9/07 1:33 PM, Bill Pikounis wrote:
> David,
> Frank Harrell's pair of packages Hmisc and Design has some functions
> for tabulating, visualizing, and accounting for missing data.  I
> recommend them as one avenue to investigate. Frank's companion book
> "Regression Modeling Strategies" covers their use in-depth.
> 
> Hope that helps,
> Bill
> 
> ___
> Bill Pikounis
>  Statistician
> 
> On 9/11/07, David Kaplan <[EMAIL PROTECTED]> wrote:
>> Hi all,
>>
>> I'm looking for a contributed package that can provide a detailed
>> account of missing data patterns and perhaps also provide imputation
>> procedures, such as mean imputation or hot deck imputation and the like.
>>   Is there anything out there?
>>
>> Thanks in advance,
>>
>> David
>>

__
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Re: [R] Missing data

[David Kaplan]

Excellent.  Thanks!


===
David Kaplan, Ph.D.
Professor
Department of Educational Psychology
University of Wisconsin - Madison
Educational Sciences, Room 1061
1025 W. Johnson Street
Madison, WI 53706

email: [EMAIL PROTECTED]
Web:   http://www.education.wisc.edu/edpsych/facstaff/kaplan/kaplan.htm
Phone: 608-262-0836
Fax:   608-262-0843
===


James Reilly wrote:
> The mice package might also be useful, especially the md.pattern function:
> http://finzi.psych.upenn.edu/R/library/mice/html/md.pattern.html
> 
> James

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[R] missing data imputation - simulation

[Birgitle]

My dataset contains missing data and I would like to do something like an EM
algorithm or a Markov Chain Monte Carlo approach to get rid of the missing
data.

Is there a function for imputation or simulation of missing data apart from
those in the randomForest library?

Thanks in advance

Birgit

-
The art of living is more like wrestling than dancing.
(Marcus Aurelius)
-- 
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[R] Missing Data and applying

[Michael Pearmain]

Hi All,

Newbie question that i'm sure is easy, but i can't seem to apply properly

I read in a datafram from a CSV file and i want to tell R that from coloum
"n_0" to "n_32" the value "-1" is missing data
i was looking at the
is.na(xx) <- c(..,...,) idea but i can't seem to apply it properly, can
anyone offer advice?

On a side issue while i'm asking i have a an XML that i intend to use to add
value labels and variable labels to the dataframe (using a python script)
but i can't seem to find the syntax for adding value labels? i.e  1=Male
2=Female

the labels command doesn't look like the one i want to use, and i've
searched the archives but to no avail (maybe it's a too simple, but i have
looked)

Any help willing accepted

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Re: [R] missing data imputation - simulation

[Chuck Cleland]

On 6/4/2008 5:32 AM, Birgitle wrote:

My dataset contains missing data and I would like to do something like an EM
algorithm or a Markov Chain Monte Carlo approach to get rid of the missing
data.

Is there a function for imputation or simulation of missing data apart from
those in the randomForest library?

Thanks in advance

Birgit


RSiteSearch("imputation", restrict="functions")

RSiteSearch("{multiple imputation}", restrict="functions")

  return many relevant hits.


-
The art of living is more like wrestling than dancing.
(Marcus Aurelius)


--
Chuck Cleland, Ph.D.
NDRI, Inc. (www.ndri.org)
71 West 23rd Street, 8th floor
New York, NY 10010
tel: (212) 845-4495 (Tu, Th)
tel: (732) 512-0171 (M, W, F)
fax: (917) 438-0894

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Re: [R] missing data imputation - simulation

[Ulrike Grömping]

Birgit,

not knowing your data, I would recommend R-package "mice" or function
aregImpute from R-package Hmisc as good multi-purpose tools.

Regards, Ulrike

-- 
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Re: [R] missing data imputation - simulation

[Birgitle]

Many thenks to both of you:
Will have a look.

Birgit


Chuck Cleland wrote:
> 
> On 6/4/2008 5:32 AM, Birgitle wrote:
>> My dataset contains missing data and I would like to do something like an
>> EM
>> algorithm or a Markov Chain Monte Carlo approach to get rid of the
>> missing
>> data.
>> 
>> Is there a function for imputation or simulation of missing data apart
>> from
>> those in the randomForest library?
>> 
>> Thanks in advance
>> 
>> Birgit
> 
> RSiteSearch("imputation", restrict="functions")
> 
> RSiteSearch("{multiple imputation}", restrict="functions")
> 
>return many relevant hits.
> 
>> -
>> The art of living is more like wrestling than dancing.
>> (Marcus Aurelius)
> 
> -- 
> Chuck Cleland, Ph.D.
> NDRI, Inc. (www.ndri.org)
> 71 West 23rd Street, 8th floor
> New York, NY 10010
> tel: (212) 845-4495 (Tu, Th)
> tel: (732) 512-0171 (M, W, F)
> fax: (917) 438-0894
> 
> __
> R-help@r-project.org mailing list
> 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.
> 
> 


-
The art of living is more like wrestling than dancing.
(Marcus Aurelius)
-- 
View this message in context: 
http://www.nabble.com/missing-data-imputation---simulation-tp17642736p17644180.html
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Re: [R] Missing Data and applying

[jim holtman]

This might help the first question:

> da <- (-1):1
> x <- data.frame(a1=sample(da,10,TRUE), a2=sample(da,10,TRUE),
a3=sample(da,10,TRUE))
> x
   a1 a2 a3
1   0  1  0
2   0  0  1
3   0  1  0
4  -1  0 -1
5   1  0 -1
6   1  1 -1
7   1 -1 -1
8  -1  0  0
9   1  1  0
10  0  1  0
> is.na(x[1:3]) <- x[1:3] == -1
> x
   a1 a2 a3
1   0  1  0
2   0  0  1
3   0  1  0
4  NA  0 NA
5   1  0 NA
6   1  1 NA
7   1 NA NA
8  NA  0  0
9   1  1  0
10  0  1  0
>



On Mon, Jun 9, 2008 at 11:18 AM, Michael Pearmain <[EMAIL PROTECTED]>
wrote:

> Hi All,
>
> Newbie question that i'm sure is easy, but i can't seem to apply properly
>
> I read in a datafram from a CSV file and i want to tell R that from coloum
> "n_0" to "n_32" the value "-1" is missing data
> i was looking at the
> is.na(xx) <- c(..,...,) idea but i can't seem to apply it properly, can
> anyone offer advice?
>
> On a side issue while i'm asking i have a an XML that i intend to use to
> add
> value labels and variable labels to the dataframe (using a python script)
> but i can't seem to find the syntax for adding value labels? i.e  1=Male
> 2=Female
>
> the labels command doesn't look like the one i want to use, and i've
> searched the archives but to no avail (maybe it's a too simple, but i have
> looked)
>
> Any help willing accepted
>
>[[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list
> 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.
>



-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem you are trying to solve?

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