Don't know how you searched, but perhaps this might help: https://stat.ethz.ch/pipermail/r-help/2007-March/128064.html
> -----Original Message----- > From: r-help-boun...@r-project.org > [mailto:r-help-boun...@r-project.org] On Behalf Of Jenn Barrett > Sent: Tuesday, April 03, 2012 1:23 AM > To: r-help@r-project.org > Subject: [R] Imputing missing values using "LSmeans" (i.e., > population marginal means) - advice in R? > > Hi folks, > > I have a dataset that consists of counts over a ~30 year > period at multiple (>200) sites. Only one count is conducted > at each site in each year; however, not all sites are > surveyed in all years. I need to impute the missing values > because I need an estimate of the total population size > (i.e., sum of counts across all sites) in each year as input > to another model. > > > head(newdat,40) > SITE YEAR COUNT > 1 1 1975 12620 > 2 1 1976 13499 > 3 1 1977 45575 > 4 1 1978 21919 > 5 1 1979 33423 > ... > 37 2 1975 40000 > 38 2 1978 40322 > 39 2 1979 70000 > 40 2 1980 16244 > > > It was suggested to me by a statistician to use LSmeans to do > this; however, I do not have SAS, nor do I know anything much > about SAS. I have spent DAYS reading about these "LSmeans" > and while (I think) I understand what they are, I have > absolutely no idea how to a) calculate them in R and b) how > to use them to impute my missing values in R. Again, I've > searched the mail lists, internet and literature and have not > found any documentation to advise on how to do this - I'm lost. > > I've looked at popMeans, but have no clue how to use this > with predict() - if this is even the route to go. Any advice > would be much appreciated. Note that YEAR will be treated as > a factor and not a linear variable (i.e., the relationship > between COUNT and YEAR is not linear - rather there are highs > and lows about every 10 or so years). > > One thought I did have was to just set up a loop to calculate > the least-squares estimates as: > > Yij = (IYi + JYj - Y)/[(I-1)(J-1)] > where I = number of treatments and J = number of blocks (so > I = sites and J = years). I found this formula in some stats > lecture handouts by UC Davis on unbalanced data and > LSMeans...but does it yield the same thing as using the > LSmeans estimates? Does it make any sense? Thoughts? > > Many thanks in advance. > > Jenn > > ______________________________________________ > 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. > Notice: This e-mail message, together with any attachme...{{dropped:11}} ______________________________________________ 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.
