RRglmGOF: Goodness-of-fit statistics for binary Randomized Response...

Description Usage Arguments Value Examples

View source: R/RRglmGOF.R

Description

Compute goodness-of-fit statistics for binary Randomized Response data. Pearson, Deviance and Hosmer-Lemeshow statistics are available.

Usage

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

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)

GLMMRR documentation built on Jan. 16, 2021, 5:28 p.m.

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