tidy.svyolr: Tidy a(n) svyolr object

View source: R/survey-tidiers.R

tidy.svyolrR Documentation

Tidy a(n) svyolr object


Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.


## S3 method for class 'svyolr'
tidy(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...)



A svyolr object returned from survey::svyolr().


Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to FALSE.


The confidence level to use for the confidence interval if conf.int = TRUE. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.


Logical indicating whether or not to exponentiate the the coefficient estimates. This is typical for logistic and multinomial regressions, but a bad idea if there is no log or logit link. Defaults to FALSE.


Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Two exceptions here are:

  • tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

  • augment() methods will warn when supplied a newdata argument if it will be ignored.


The tidy.svyolr() tidier is a light wrapper around tidy.polr(). However, the implementation for p-value calculation in tidy.polr() is both computationally intensive and specific to that model, so the p.values argument to tidy.svyolr() is currently ignored, and will raise a warning when passed.


A tibble::tibble() with columns:


Upper bound on the confidence interval for the estimate.


Lower bound on the confidence interval for the estimate.


The estimated value of the regression term.


The two-sided p-value associated with the observed statistic.


The value of a T-statistic to use in a hypothesis that the regression term is non-zero.


The standard error of the regression term.


The name of the regression term.

See Also

tidy, survey::svyolr()

Other ordinal tidiers: augment.clm(), augment.polr(), glance.clmm(), glance.clm(), glance.polr(), glance.svyolr(), tidy.clmm(), tidy.clm(), tidy.polr()



dclus1 <- svydesign(id = ~dnum, weights = ~pw, data = apiclus1, fpc = ~fpc)
dclus1 <- update(dclus1, mealcat = cut(meals, c(0, 25, 50, 75, 100)))

m <- svyolr(mealcat ~ avg.ed + mobility + stype, design = dclus1)


tidy(m, conf.int = TRUE)

broom documentation built on Aug. 30, 2022, 1:07 a.m.