R: Pseudo-Rsquareds

psrsq {survey} | R Documentation

## Pseudo-Rsquareds

### Description

Compute the Nagelkerke and Cox–Snell pseudo-rsquared statistics, primarily for logistic regression. A generic function with methods for `glm` and `svyglm`. The method for `svyglm` objects uses the design-based estimators described by Lumley (2017)

### Usage

    psrsq(object, method = c("Cox-Snell", "Nagelkerke"), ...)

### Arguments

`object` | A regression model (`glm` or `svyglm`)
`method` | Which statistic to compute
`...` | For future expansion

### Value

Numeric value

### References

Lumley T (2017) "Pseudo-R2 statistics under complex sampling" Australian and New Zealand Journal of Statistics DOI: 10.1111/anzs.12187 (preprint: https://arxiv.org/abs/1701.07745)

### See Also

`AIC.svyglm`

### Examples

    data(api)
    dclus2<-svydesign(id=~dnum+snum, weights=~pw, data=apiclus2)

    model1<-svyglm(I(sch.wide=="Yes")~ell+meals+mobility+as.numeric(stype),
         design=dclus2, family=quasibinomial())

    psrsq(model1, type="Nagelkerke")

[Package survey version 3.32-1 Index]