You are posting in HTML and the R-help list is a plain text one. Would you reset
to plain in your e-mail editor before posting, please?
For security reasons R-help strips the HTML version and, we on the list,
receive the resulting plain text. This, often, mangles code to the point that
it is almost indecipherable.
Re your question, if I understood it. Something like this should do it
fm <- subset(dat1, Level =="PREMIER_LEAGUE" & (Position ==
"F" | Position == "m"))
This now gives you a data.frame with only those rows that match your criteria.
Untested since all 100 rows are CHAMPIONSHIP. No fPREMIER_LEAGUE in your first
100 rows of data. I should have warned you about this but it was late and I
didn't think through your statement about "The data set I have is quite
large".
Here is an example of how to do some random sampling of your data.frame, which I
should have mentioned yesterday
http://stackoverflow.com/questions/8273313/random-rows-in-dataframe-in-r
But in any case the idea is just to subset the data and go from there. Just
type ?subset for help.
## "Where "F" position are in the same AgeGr as well."
You should be able to add a AgeGr = 99 in the subset statement.
fm <- subset(dat1, Level =="PREMIER_LEAGUE" & AgeGr = 10
& (Position == "F" | Position == "m"))
should work. Untested and again it's almost dinner time so no guarantees.
I think that there are faster and better ways to do this but this is fairly
basic and "relatively' self-documenting.
After that, it depends on what you want to do with the data.
I hope this helps
John Kane
Kingston ON Canada
-----Original Message-----
From: joshuamichaeldixon at gmail.com
Sent: Tue, 28 Apr 2015 21:26:31 +0100
To: jrkrideau at inbox.com
Subject: Re: [R] Help Interpreting Linear Mixed Model
*Edit*?
Where "F" position are in the same AgeGr as well.
Thanks,
Josh
On Tue, Apr 28, 2015 at 9:25 PM, Joshua Dixon <joshuamichaeldixon at
gmail.com> wrote:
John - ?Lot's of missing data for height unfortunately.? Which is needed for
BMI calculation. ?
How would I look compare very specific parts of the data, i.e. comparing YoYo
outcomes between "F" and "M" position that are both in the
PREMIER_LEAGUE Level?
Still can't figure it out!
Josh
On Tue, Apr 28, 2015 at 2:39 AM, John Kane <jrkrideau at inbox.com> wrote:
Looks great.? How come so many NA's in Height and BMI? Just no data
available?
?str(dat1)
'data.frame':? ?100 obs. of? 8 variables:
?$ Id? ? ? : int? 7451 148 10393 10200 1961 10428 10541 10012 9895 10626 ...
?$ Level? ?: Factor w/ 5 levels "CHAMPIONSHIP",..: 1 1 1 1 1 1 1 1 1
1 ...
?$ AgeGr? ?: int? 14 16 10 10 13 10 10 10 10 10 ...
?$ Position: Factor w/ 4 levels
"D","F","GK","M": 4 1 1 2 3 3 2 3 1 1
...
?$ Height? : int? NA NA NA NA NA NA NA 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-----
From: joshuamichaeldixon at gmail.com
Sent: Mon, 27 Apr 2015 23:35:13 +0100
To: jrkrideau at inbox.com
Subject: Re: [R] Help Interpreting Linear Mixed Model
Thanks John!
This ok?
> dput(head(data, 100))
structure(list(Id = c(7451L, 148L, 10393L, 10200L, 1961L, 10428L,?
10541L, 10012L, 9895L, 10626L, 1151L, 8775L, 10083L, 6217L, 90L,?
10168L, 10291L, 8549L, 3451L, 10003L, 5907L, 10136L, 6182L, 6315L,?
10015L, 9956L, 2040L, 4710L, 10747L, 6787L, 1222L, 10757L, 2892L,?
117L, 10328L, 10503L, 768L, 2979L, 1961L, 10520L, 10498L, 3018L,?
10335L, 2448L, 9027L, 362L, 8499L, 10603L, 9489L, 2124L, 707L,?
8501L, 4908L, 9905L, 3000L, 2819L, 9973L, 10550L, 9921L, 10639L,?
8771L, 10121L, 32L, 9935L, 9299L, 3246L, 682L, 10325L, 6741L,?
3295L, 5270L, 727L, 8500L, 50L, 4705L, 3018L, 787L, 2953L, 1391L,?
3682L, 7974L, 5023L, 652L, 727L, 679L, 10212L, 9488L, 9987L,?
10039L, 5025L, 250L, 2539L, 787L, 3000L, 1151L, 8946L, 6177L,?
3296L, 250L, 498L), Level = structure(c(1L, 1L, 1L, 1L, 1L, 1L,?
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,?
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,?
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,?
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,?
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,?
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label =
c("CHAMPIONSHIP",?
"CONFERENCE", "LEAGUE_ONE", "LEAGUE_TWO",
"PREMIER_LEAGUE"), class = "factor"),?
? ? AgeGr = c(14L, 16L, 10L, 10L, 13L, 10L, 10L, 10L, 10L, 10L,?
? ? 14L, 10L, 10L, 10L, 12L, 10L, 10L, 12L, 10L, 10L, 10L, 10L,?
? ? 12L, 10L, 10L, 10L, 10L, 10L, 10L, 15L, 10L, 10L, 10L, 12L,?
? ? 10L, 10L, 13L, 10L, 13L, 11L, 11L, 13L, 12L, 11L, 12L, 14L,?
? ? 13L, 13L, 13L, 13L, 12L, 11L, 15L, 11L, 14L, 13L, 11L, 11L,?
? ? 11L, 12L, 14L, 12L, 13L, 11L, 13L, 15L, 11L, 13L, 13L, 13L,?
? ? 14L, 13L, 13L, 12L, 13L, 13L, 13L, 14L, 12L, 14L, 13L, 13L,?
? ? 13L, 13L, 13L, 12L, 13L, 14L, 13L, 14L, 13L, 14L, 13L, 14L,?
? ? 14L, 13L, 14L, 13L, 13L, 13L), Position = structure(c(4L,?
? ? 1L, 1L, 2L, 3L, 3L, 2L, 3L, 1L, 1L, 1L, 2L, 4L, 3L, 2L, 3L,?
? ? 4L, 3L, 4L, 2L, 4L, 2L, 3L, 1L, 1L, 2L, 4L, 4L, 2L, 4L, 4L,?
? ? 2L, 1L, 4L, 1L, 1L, 2L, 4L, 3L, 1L, 4L, 1L, 2L, 3L, 3L, 1L,?
? ? 1L, 3L, 1L, 3L, 4L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 3L, 1L,?
? ? 2L, 2L, 2L, 4L, 4L, 2L, 4L, 2L, 3L, 3L, 4L, 4L, 1L, 1L, 1L,?
? ? 2L, 2L, 4L, 1L, 1L, 1L, 2L, 4L, 1L, 3L, 4L, 4L, 4L, 4L, 2L,?
? ? 2L, 2L, 1L, 1L, 4L, 1L, 4L, 2L, 2L), .Label = c("D",
"F",?
? ? "GK", "M"), class = "factor"), Height = c(NA,
NA, NA, NA,?
? ? NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,?
? ? NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,?
? ? NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 151L, NA,?
? ? 154L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 156L, NA,?
? ? 147L, NA, NA, NA, NA, NA, 138L, 172L, NA, NA, 150L, NA, NA,?
? ? NA, NA, NA, NA, NA, 140L, 153L, NA, NA, NA, NA, NA, NA, NA,?
? ? 158L, NA, NA, NA, NA, NA, NA, NA, NA, NA, 156L), Weight = c(63,?
? ? 64, 36, 46, 67, 40, 25, 30, 36, 33, 61, 31, 29, 34, 47, 38,?
? ? 32, 44, 32, 32, 30, 34, 51, 34, 28, 27, 33, 31, 28, 44, 37,?
? ? 46, 26, 42, 32, 32, 43, 31, 72, 27, 30, 55, 53, 50, 51, 55,?
? ? 48.6, 49, 48, 64, 35, 32, 55, 32, 50, 61, 42, 33, 37, 45,?
? ? 45, 50, 36, 33, 49, 59, 42, 43, 35.1, 66.9, 52, 47, 40, 38,?
? ? 45, 53, 44, 54, 39, 62, 33, 53.8, 42, 46, 39, 48, 39, 54,?
? ? 40, 42.4, 50, 48, 46, 52, 58, 40, 46, 51, 54, 42), BMI = c(NA,?
? ? NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,?
? ? NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,?
? ? NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,?
? ? 21.2, NA, 20.24, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,?
? ? NA, 18.49, NA, 16.66, NA, NA, NA, NA, NA, 18.57, 22.61, NA,?
? ? NA, 17.77, NA, NA, NA, NA, NA, NA, NA, 16.84, 22.86, NA,?
? ? NA, NA, NA, NA, NA, NA, 16.9, NA, NA, NA, NA, NA, NA, NA,?
? ? NA, NA, 17.26), YoYo = c(80L, 80L, 160L, 160L, 160L, 160L,?
? ? 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L,?
? ? 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L,?
? ? 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L, 160L,?
? ? 160L, 160L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L,?
? ? 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L, 200L,?
? ? 200L, 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, 240L, 240L, 240L)), .Names = c("Id", "Level",
"AgeGr",?
"Position", "Height", "Weight", "BMI",
"YoYo"), row.names = c(NA,?
100L), class = "data.frame")
On Mon, Apr 27, 2015 at 10:43 PM, John Kane <jrkrideau at inbox.com>
wrote:
?Hi Josh,
?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-----
?From: joshuamichaeldixon at gmail.com
Sent: Mon, 27 Apr 2015 21:30:39 +0100
?To: lists at 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() command
I'm unsure if it actually fits the whole output into the console.? I
can't scroll up far enough to see the actual command.? I can paste what is
there if that may help?? The bottom line:?
?Names = c("Id", "Level", "AgeGr",
"Position", "Height", "Weight", "BMI",
"YoYo"), class = "data.frame", row.names = c(NA, -9689L))
?Michael - Essentially, I'm looking for differences between
"YoYo" outcome for "Positions", "Levels" and
accounting for repeated measures using "Id" as a random factor.? So I
was able to figure out points 2 and 3.
?I've searched for definitions of "Scaled
residuals",?"Random effects",?"Fixed
effects",?"Correlation of Fixed Effects".? However, I'm
confused at the different interpretations I've found.? Or quite possibly,
I'm just confused...? What should I be?looking?out for in these variables?
?I've tried to take my analysis smaller, and just look at specifics, to
make it simpler.? Such as, comparing YoYo (outcome score) for a Premier_League
(Level), 22 (AgeGr) F (Position) with a?Premier_League (Level), 22 (AgeGr) M
(Position).? How do I convert these into a factors for analysis?
?Simple question maybe, but it's not when you can't find the answer!
?Thank you,
?Josh
?On Mon, Apr 27, 2015 at 4:10 PM, Michael Dewey <lists at
dewey.myzen.co.uk> wrote:
?? ? ? ? Dear Joshua
??It would also help if you told us what your scientific question was. At the
moment we know what R commands you used and have seen the head of your dataset
but not why you are doing it.
??I would summarise what you have given us as
??1 - most ID only occur once
??2 - goal keepers do worse than outfield players
??3 - older people (presumably in fact age is in years as a continuous
variable) do better
??On 27/04/2015 12:42, John Kane wrote:
??John Kane
??Kingston ON Canada
?? ? ? ? ?-----Original Message-----
??From: joshuamichaeldixon at gmail.com
??Sent: Mon, 27 Apr 2015 08:54:51 +0100
??To: thierry.onkelinx at 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" business?
??BTW, a better way to supply sample data is to use the dput() command.
??Do a dput(mydata), copy the results into the email and you have supplied us
with an exact copy of your data.
??It is possible for many reasons that I will not read in your data, as you
supplied it, in the format you have it in.? This can lead to real confusion.
?? ? ? ? ?Josh
?? ? ? ? ?On 27 Apr 2015, at 08:06, Thierry Onkelinx <thierry.onkelinx at
inbo.be>
??wrote:
??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
??Belgium
??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
??2015-04-27 2:26 GMT+02:00 Joshua Dixon <joshuamichaeldixon at
gmail.com>:
?? ? ? ? ?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 difference to CHAMPIONSHIP 18
??GK?
??For reference my data set looks like this:
??Id Level AgeGr? ?Position Height Weight BMI YoYo
??7451 CHAMPIONSHIP 14 M NA 63 NA 80
??148 PREMIER_LEAGUE 16 D NA 64 NA 80
??10393 CONFERENCE 10 D NA 36 NA 160
??10200 CHAMPIONSHIP 10 F NA 46 NA 160
??1961 LEAGUE_TWO 13 GK NA 67 NA 160
??10428 CHAMPIONSHIP 10 GK NA 40 NA 160
??10541 LEAGUE_ONE 10 F NA 25 NA 160
??10012 CHAMPIONSHIP 10 GK NA 30 NA 160
??9895 CHAMPIONSHIP 10 D NA 36 NA 160
??Many thanks in advance for time and help.? Really appreciate it.
??Josh
?? ? ? ? ?summary(lmer(YoYo~AgeGr+Position+(1|Id)))
??Linear mixed model fit by REML ['lmerMod']
??Formula: YoYo ~ AgeGr + Position + (1 | Id)
??REML criterion at convergence: 125712.2
??Scaled residuals:
??? ? ?Min? ? ? 1Q? Median? ? ? 3Q? ? ?Max
??-3.4407 -0.5288 -0.0874? 0.4531? 4.8242
??Random effects:
??? Groups? ?Name? ? ? ? Variance Std.Dev.
??? Id? ? ? ?(Intercept) 15300? ? 123.7
??? Residual? ? ? ? ? ? ?16530? ? 128.6
??Number of obs: 9609, groups:? Id, 6071
??Fixed effects:
??? ? ? ? ? ? ? Estimate Std. Error t value
??(Intercept) -521.6985? ? 16.8392? -30.98
??AgeGr? ? ? ? ?62.6786? ? ?0.9783? ?64.07
??PositionD? ? 139.4682? ? ?7.8568? ?17.75
??PositionM? ? 141.2227? ? ?7.7072? ?18.32
??PositionF? ? 135.1241? ? ?8.1911? ?16.50
??Correlation of Fixed Effects:
??? ? ? ? ? ?(Intr) AgeGr? PostnD PostnM
??AgeGr? ? ?-0.910
??PositionD -0.359 -0.009
??PositionM -0.375? 0.001? 0.810
??PositionF -0.349 -0.003? 0.756? 0.782
?? ? ? ? ?model=lmer(YoYo~AgeGr+Position+(1|Id))
??summary(glht(model,linfct=mcp(Position="Tukey")))
??? Simultaneous Tests for General Linear Hypotheses
??Multiple Comparisons of Means: Tukey Contrasts
??Fit: lmer(formula = YoYo ~ AgeGr + Position + (1 | Id))
??Linear Hypotheses:
??? ? ? ? ? ? ?Estimate Std. Error z value Pr(>|z|)
??D - GK == 0? 139.468? ? ? 7.857? 17.751? ?<1e-04 ***
??M - GK == 0? 141.223? ? ? 7.707? 18.323? ?<1e-04 ***
??F - GK == 0? 135.124? ? ? 8.191? 16.496? ?<1e-04 ***
??M - D == 0? ? ?1.754? ? ? 4.799? ?0.366? ? 0.983
??F - D == 0? ? -4.344? ? ? 5.616? -0.774? ? 0.862
??F - M == 0? ? -6.099? ? ? 5.267? -1.158? ? 0.645
??---
??Signif. codes:? 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
??(Adjusted p values reported -- single-step method)
??? ? ? ? ?[[alternative HTML version deleted]]
??______________________________________________
??R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
?https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]]]
??PLEASE do read the posting guide
??http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]]]
??and provide commented, minimal, self-contained, reproducible code.
??? ? ? ? [[alternative HTML version deleted]]
??______________________________________________
??R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
??https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]]]
??PLEASE do read the posting guide
??http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]]]
??and provide commented, minimal, self-contained, reproducible code.
??____________________________________________________________
??FREE ONLINE PHOTOSHARING - Share your photos online with your friends and
family!
??Visit http://www.inbox.com/photosharing [http://www.inbox.com/photosharing]
[http://www.inbox.com/photosharing [http://www.inbox.com/photosharing]]
[http://www.inbox.com/photosharing [http://www.inbox.com/photosharing]
[http://www.inbox.com/photosharing [http://www.inbox.com/photosharing]]] to find
out more!
??______________________________________________
??R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
??https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]
[https://stat.ethz.ch/mailman/listinfo/r-help
[https://stat.ethz.ch/mailman/listinfo/r-help]]]
??PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]
[http://www.R-project.org/posting-guide.html
[http://www.R-project.org/posting-guide.html]]]
??and provide commented, minimal, self-contained, reproducible code.
??--
??Michael
??http://www.dewey.myzen.co.uk/home.html
[http://www.dewey.myzen.co.uk/home.html] [http://www.dewey.myzen.co.uk/home.html
[http://www.dewey.myzen.co.uk/home.html]]
[http://www.dewey.myzen.co.uk/home.html [http://www.dewey.myzen.co.uk/home.html]
[http://www.dewey.myzen.co.uk/home.html
[http://www.dewey.myzen.co.uk/home.html]]]
?____________________________________________________________
?Can't remember your password? Do you need a strong and secure password?
?Use Password manager! It stores your passwords & protects your account.
?Check it out at http://mysecurelogon.com/manager
[http://mysecurelogon.com/manager] [http://mysecurelogon.com/manager
[http://mysecurelogon.com/manager]]
____________________________________________________________
FREE 3D EARTH SCREENSAVER - Watch the Earth right on your desktop!
Check it out at http://www.inbox.com/earth [http://www.inbox.com/earth]
____________________________________________________________
FREE 3D EARTH SCREENSAVER - Watch the Earth right on your desktop!