cramersV {ufs} | R Documentation |
These functions compute the point estimate and confidence interval for Cramer's V.
cramersV(x, y = NULL, digits = 2) ## S3 method for class 'CramersV' print(x, digits = x$input$digits, ...) confIntV( x, y = NULL, conf.level = 0.95, samples = 500, digits = 2, method = c("bootstrap", "fisher"), storeBootstrappingData = FALSE ) ## S3 method for class 'confIntV' print(x, digits = x$input$digits, ...)
x |
Either a crosstable to analyse, or one of two vectors to use to generate that crosstable. The vector should be a factor, i.e. a categorical variable identified as such by the 'factor' class). |
y |
If x is a crosstable, y can (and should) be empty. If x is a vector, y must also be a vector. |
digits |
Minimum number of digits after the decimal point to show in the result. |
... |
Any additional arguments are passed on to the |
conf.level |
Level of confidence for the confidence interval. |
samples |
Number of samples to generate when bootstrapping. |
method |
Whether to use Fisher's Z or bootstrapping to compute the confidence interval. |
storeBootstrappingData |
Whether to store (or discard) the data generating during the bootstrapping procedure. |
A point estimate or a confidence interval for Cramer's V, an effect size to describe the association between two categorical variables.
### Get confidence interval for Cramer's V ### Note that by using 'table', and so removing the raw data, inhibits ### bootstrapping, which could otherwise take a while. confIntV(table(infert$education, infert$induced));