Compute separate nonresponse adjustments in a set of classes.
1  NRadjClass(ID, NRclass, resp, preds=NULL, wts=NULL, type)

ID 
identification value for a unit 
NRclass 
vector of classes to use for nonresponse adjustment. Length is number of respondents plus nonrespondents 
resp 
indicator for whether unit is anonrespondent (must be coded 0) or respondent (must be coded 1) 
preds 
response probabilities, typically estimated from a binary regression model as in 
wts 
vector of survey weights, typically base weights or base weights adjusted for unknown eligibility 
type 
type of adjustment computed within each value of 
The input vectors should include both respondents and nonrespondents in a sample. A single value between 0 and 1 is computed in each nonresponse adjustment class to be used as a nonresponse adjustment. Five alternatives are available for computing the adjustment based on the value of type
. The value of the adjustment is merged with individual unit data and stored in the RR
field of the output data frame.
A data frame of respondents only with four columns:
NRcl.no 
number of the nonresponse adjustment class for each unit 
ID 
identification value for a unit 
resp 
value of the 
RR 
nonresponse adjustment for each unit 
Richard Valliant, Jill A. Dever, Frauke Kreuter
Valliant, R., Dever, J., Kreuter, F. (2013, chap. 13). Practical Tools for Designing and Weighting Survey Samples. New York: Springer.
pclass
1 2 3 4 5 6 7  require(PracTools)
data(nhis)
out < pclass(formula = resp ~ age + as.factor(sex) + as.factor(hisp) + as.factor(race),
data = nhis, type = "unwtd", link="logit", numcl=5)
# unweighted average of response propensities within each class
zz < NRadjClass(ID=nhis[,"ID"], NRclass = as.numeric(out$p.class), resp=nhis[,"resp"],
preds=out$propensities, wts=NULL, type=1)

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