On 04/02/2015 10:16 AM, [email protected] wrote:
I'm preparing some reports for substate regions from BRFSS survey data. I
can get estimates easily enough, but am having problems putting the results
in convenient form. Here's some code using the New Hampshire portion of the
public BRFSS "SMART" data:
library(foreign)
library(survey)
# download and extract http://www.cdc.gov/brfss/smart/2012/CNTY12XPT.zip
nh.smart <- svydesign(ids = ~0, strata = ~X_STSTR, weights = ~X_CNTYWT,
data = subset(read.xport("CNTY12.xpt"), X_STATE ==
33))
# using asthma status as example
nh.smart <- update(nh.smart,
X_ASTHMS1 = factor(X_ASTHMS1, levels = 1:3,
labels = c("Current","Former","Never")),
X_CNTY = factor(X_CNTY, labels = c("Belknap","Carroll","Cheshire","Coos",
"Grafton","Hillsborough","Merrimack",
"Rockingham","Strafford")))
a <- svyby(~X_ASTHMS1, ~X_CNTY, nh.smart, svymean, na.rm = TRUE,
vartype = "ci")
Is there a convenient way to get a flat table similar to the following? I'm
not having much success with "ftable."
Thanks in advance,
Michael L.
# Percent LCI UCI
# Belknap Current 10.4 5.6 15.3
# Former 1.5 0.4 2.7
# Never 88.1 83.1 93.0
# Carroll Current 7.5 4.9 10.1
# Former 2.9 1.3 4.5
# Never 89.6 86.5 92.7
# ...
What do you mean by a "flat table"? You can get a table that's suitable
for conversion to LaTeX or HTML (or maybe some other format) from the
tables package. I haven't tried this, but I would think the syntax
would be something like
tabular(Factor(X_CNTY, "County")*Factor(X_ASTHMS1, "Asthma")
~ Percent(denom=Equal(X_CNTY)) +
Percent(denom=Equal(X_CNTY), fn=LCI) +
Percent(denom=Equal(X_CNTY), fn=UCI), data=nh.smart)
You'll need to write the LCI and UCI functions to compute the confidence
limits. I don't know how to extract those from the objects you've got;
you may need to add an "analysis variable" to the tabular() call to get
the required inputs.
Duncan Murdoch
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