While I'm trying to catch up on the statistical basis of my task, could
someone point me to how I should fix my R error?
Thanks
########################################################################
####
> library(survey)
> SurveyData <- read.spss("C:/Data/R/orange_delivery.sav",
use.value.labels=TRUE, max.value.labels=Inf, to.data.frame=TRUE)
>
#=======================================================================
========
> temp <- sub(' +$', '', SurveyData$direction_)
> SurveyData$direction_ <- temp
>
#=======================================================================
========
>
SurveyData$NumStn=abs(as.numeric(SurveyData$lineon)-as.numeric(SurveyDat
a$lineoff))
> EBSurvey <- subset(SurveyData, direction_ == "EASTBOUND" )
> XTTable <- xtabs(~direction_ , EBSurvey)
> XTTable
direction_
EASTBOUND
345
> WBSurvey <- subset(SurveyData, direction_ == "WESTBOUND" )
> XTTable <- xtabs(~direction_ , WBSurvey)
> XTTable
direction_
WESTBOUND
307
> #
> EBDesign <- svydesign(id=~sampn, weights=~expwgt, data=EBSurvey)
> # svytable(~lineon+lineoff, EBDesign)
> OnLabels <- c( "Warner Center", "De Soto", "Pierce College",
"Tampa", "Reseda", "Balboa", "Woodley", "Sepulveda", "Van Nuys",
"Woodman", "Valley College", "Laurel Canyon", "North Hollywood")
> EBOnNewTots <- c( 1000, 600, 1200,
500, 1000, 500, 200, 250, 1000, 300,
100, 50, 73.65 )
> EBNumStn <- c(673.65, 800, 1000, 1000, 800, 700, 600, 500, 400,
200, 50, 50 )
> ByEBOn <- data.frame(OnLabels,EBOnNewTots)
> ByEBNum <- data.frame(c(1:12),EBNumStn)
> RakedEBSurvey <- rake(EBDesign, list(~ByEBOn, ~ByEBNum),
list(EBOnNewTots, EBNumStn ) )
Error in model.frame.default(margin, data = design$variables) :
invalid type (list) for variable 'ByEBOn'
>
###################################################################
sessionInfo()
R version 2.7.1 (2008-06-23)
i386-pc-mingw32
locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252
attached base packages:
[1] graphics grDevices utils datasets stats methods base
other attached packages:
[1] survey_3.8 fortunes_1.3-5 moonsun_0.1 prettyR_1.3-2
foreign_0.8-28
>
####################################################################
Robert Farley
Metro
www.Metro.net
-----Original Message-----
From: Farley, Robert
Sent: Monday, August 18, 2008 16:18
To: 'r-help@r-project.org'
Subject: RE: [R] Survey Design / Rake questions
Thank you for the list of references. Do you know of any "free"
references available online? I'll have to find my library card :-)
My motivation is to try to correct for a "time on board" bias we see in
our surveys. Not surprisingly, riders who are only on board a short
time don't attempt/finish our survey forms. We're able to weight our
survey to the "bus stop-on by bus run" level. I want to keep that, and
rake on new (imposed?) marginals, like an estimate of how many minutes
they were on-board derived from their origin-destination. In practice,
we'll have thousands of observations on hundreds of runs. As I see it,
my work-plan involves:
Running rake successfully on test data
Preparing "bus stop-on by run" marginals automatically
Plus any other "pre-existing" marginals to be kept.
Appending "time on bus" estimates
Determining the "time on bus" distribution (second survey?)
Implementing the raking adjustment for a production (large)
dataset
As of yet, I cannot get the first step to work :-(
I hope there are no "fatal flaws" in this concept....
Robert Farley
Metro
www.Metro.net
-----Original Message-----
From: Stas Kolenikov [mailto:[EMAIL PROTECTED]
Sent: Monday, August 18, 2008 10:32
To: Farley, Robert
Cc: r-help@r-project.org
Subject: Re: [R] Survey Design / Rake questions
Your reading, in increasing order of difficulty/mathematical details,
might be Lohr's "Sampling"
(http://www.citeulike.org/user/ctacmo/article/1068825), Korn &
Graubard's "Health Surveys"
(http://www.citeulike.org/user/ctacmo/article/553280), and Sarndal et.
al. Survey Math Bible
(http://www.citeulike.org/user/ctacmo/article/716032). You certainly
should try to get a hold of the primary concepts before collecting
your data (or rather before designing your survey... so it might
already be too late!). Post-stratification is not that huge topic, for
some reason; a review of mathematical details is given by Valliant
(1993) (http://www.citeulike.org/user/ctacmo/article/1036976). On
raking, the paper on top of Google Scholar search by Deville, Sarndal
and Sautory (1993)
(http://www.citeulike.org/user/ctacmo/article/3134001) is certainly
coming from the best people in the field.
I am not aware of general treatment of transportation survey sampling,
although I suspect such references do exist in transportation
research. There might be particular twists as the same subject/bus
usage episode might be sampled at different locations.
As far as rake() procedure is concerned, you need to have your data
set up as sampled observations with two classifications across which
you will be raking, probably the directions "E"/"W" and the stations.
Those are not different data.frames, as you are trying to set them up,
but a single data.frame with several columns. In other words, your
sampled data will have labels "E"/"W" in one of the columns, and
station names in another column, and (the names of) those columns will
be the imputs of rake().
On 8/18/08, Farley, Robert <[EMAIL PROTECTED]> wrote:
> I'm trying to learn how to calibrate/postStratify/rake survey data in
> preparation for a large survey effort we're about to embark upon. As
a
> working example, I have results from a small survey of ~650
respondents,
> ~90 response fields each. I'm trying to learn how to (properly?)
apply
> the aforementioned functions.
>
> My data are from a bus on board survey. The expansion in the dataset
is
> derived from three elements:
>
> Response rates by bus stop for a sampled run
>
> Total runs/samples runs
>
> Normalized to (separately derived) daily line boarding
>
> In order to get to the point of raking the data, I need to learn more
> about the survey package and nomenclature. For instance, given how
I've
> described the survey/weighting, is my call to svydesign correct? I'm
> not sure I understand just what a "survey design" is. Where can I
read
> up on this? What's a good reference for such things as "PSUs",
"cluster
> sampling", and so on.
--
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.
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