I'm about to add weights to a bus on-board survey dataset with ~150 variables
and ~28,000 records. My intention is to weight (for each bus "run") by
boarding stop and alighting stop. I've seen the Rake function of the Survey
package, but it seems that converting to a "svydesign" might be excessive for
my purpose.
My dataset has a huge number of unique "Run-Boarding" and "Run-Alighting"
groups each with a small number of records to expand. Would it be easier to
manually implement Iterative-Proportional-Fitting/Raking/Fratar/Furness on the
data? Or are there benefits to converting the data to a svydesign that would
make it valuable? This "traditional" weighting expands what we call unlinked
(based on each boarding)trips. I'm thinking of also using IPF/Raking to
estimate linked (based on each individual) trips. Would this change the
consideration of using the svydesign process?
I initially looked into this process about 3 years ago, but haven't touched R
since then....
Thanks in advance,
Robert Farley
LACMTA
1 Gateway Plaza
Los Angeles, CA 90012-2952
(213)922-2532
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