Goodness-of-fit statistics for binary Randomized Response data

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Description

Compute goodness-of-fit statistics for binary Randomized Response data. Pearson, Deviance and Hosmer-Lemeshow statistics are available. Reference: Fox, J-P, Klotzke, K. and Veen, D. (2016). Generalized Linear Mixed Models for Randomized Responses. Manuscript submitted for publication.

Usage

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RRglmGOF(RRglmOutput, doPearson = TRUE, doDeviance = TRUE,
  doHlemeshow = TRUE, hlemeshowGroups = 10, rm.na = TRUE, print = TRUE)

Arguments

RRglmOutput

a model fitted with the RRglm function.

doPearson

compute Pearson statistic.

doDeviance

compute Deviance statistic.

doHlemeshow

compute Hosmer-Lemeshow statistic.

hlemeshowGroups

number of groups to split the data into for the Hosmer-Lemeshow statistic (default: 10).

rm.na

remove cases with missing data.

print

print summary of goodness-of-fit statistics.

Value

an option of class RRglmGOF.

Examples

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out <- RRglm(response ~ Gender + RR + pp + age, link="RRlink.logit", RRmodel=RRmodel,
         p1=RRp1, p2=RRp2, data=Plagiarism, etastart=rep(0.01, nrow(Plagiarism)))
RRglmGOF(RRglmOutput = out, doPearson = TRUE, doDeviance = TRUE, doHlemeshow = TRUE, print = TRUE)

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