| NRadjClass | R Documentation |
Compute separate nonresponse adjustments in a set of classes.
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 a nonrespondent (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. (2018, chap. 13). Practical Tools for Designing and Weighting Survey Samples, 2nd edition. New York: Springer.
pclass
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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