Displaying 5 results from an estimated 5 matches for "mydesign".
2012 Jun 21
4
crosstable and regression for survey data (weighted)
I have survey data that I am working on. I need to make some multi-way tables
and regression analyses on the data. After attaching the data, this is the
code I use for tables for four variables (sweight is the weight variable):
> a <- xtabs(sweight~research.area + gender + a2n2 + age)
> tmp <- ftable(a)
Is this correct? I don't think I need to use the strata and cluster
2013 Feb 11
1
Simple frequencies using svy design
Hello,
excuse me if this is trivial. I have some survey data with the following
design
MyDesign<-(id=ident, weights=~fwgt, fcp=~nval1+nval2, data=hh_data1)
I would like to run simple frequency tables such as those provided by the
freq() function of rgrs to check the impact of the sampling design on my
Ns. Anyway I can do this? thanks, V
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2012 Oct 12
0
goodness of fit for logistic regression with survey package
...exploratory analyses on a complex survey data by using survey
package. Could you help me how to see the goodness of fit for the model
below? Should I use AIC, BIC, ROC, or what? What code would let me run a
goodness of fit test for the model? Here are my codes:
#incorporating design effects#
> mydesign <- svydesign(id=~clust, strata=~strat, weights=~sweight,
> data=mydata)
#logistic regression model#
> model1 <- svyglm(y ~ x1 + x2+ x3 + x4 + x5, design = mydesign,
> data=(mydata),family=quasibinomial())
#I tried loglik function, but didn't work#
> logLik(model1)
[1] 8753.057...
2012 Jun 12
2
GEE with Inverse Probability Weights
Greetings,
I have a very, very, simple research question. I want to predict one
dichotomous variable using another dichotomous variable. Straightforward,
right? The issue is that the dataset has two issues causing some
complications for me.
1) The subjects are not independent -- they are sibling pairs. Every person
in the dataset has a sibling in the dataset. This needs to be treated a
2010 Aug 25
1
Surprising behaviour survey-package with missing values
...ssing values.
Some example code demonstrating the behaviour is included below.
I have a stratified sampling design where I want to estimate the total
income. In some strata some of the incomes are missing. I want to
ignore these missing incomes. I would have expected that
svytotal(~income, design=mydesign, na.rm=TRUE) would do the trick.
However, when calculating the estimates 'by hand' the estimates were
different from those obtained from svytotal. The estimated mean
incomes do agree with each other. It seems that using the na.rm option
with svytotal is the same as replacing the missing val...