corregplicate: Repeated Correspondence Regression
In corregp: Functions and Methods for Correspondence Regression

Description Usage Arguments Value See Also

A function for repeated correspondence regressions with bootstrapping in order to handle large data sets. This is essentially a wrapper replicate(n = r, expr = corregp(...), simplify = FALSE), so it may dissappear in the future.

1
2
3

corregplicate(formula, data, part = NULL, b = 100, r = 10, xep = TRUE,
  std = FALSE, rel = TRUE, phi = FALSE, chr = ".",
  b_scheme = "multinomial")

`formula`	A `formula` specification of which factors to cross with each other. The left-hand (`y`) side must be a single factor. The right-hand side (`x`) can involve all the usual specifications of interactions and/or nested analyses.
`data`	The data frame containing the variables specified in the `formula`.
`part`	Character vector specifying the names of conditional factors (e.g. a factor partioning the levels of the left-hand side `y` into groups). This argument is relevant for analyses in which one wants to remove between-item variation.
`b`	Number of the bootstrap replications (simulations).
`r`	Number of repeated calls to `corregp`.
`xep`	Logical specifying whether to output the separate terms in the right-hand side (`x`) as components in a list. If `FALSE`, then all `x` output is collected in a matrix.
`std`	Logical specifying whether to output the standardized coordinates. Defaults to `FALSE`.
`rel`	Logical specifying whether to divide the coordinates by the `sqrt` of their totals, so that one obtains coordinates for the relative frequencies (as is customary in correspondence analysis). Defaults to `TRUE`.
`phi`	Logical specifying whether to compute the output on the scale of the Chi-squared value of the contingency table or of the Phi-squared value (which is Chi-squared divided by N). Reminiscent of `corresp` in package MASS, defaults to `FALSE`.
`chr`	Character specifying the separator string for constructing the interaction terms.
`b_scheme`	Character specifying the sampling scheme for bootstrapping. Must match either `"multinomial"` (the default) or `"product-multinomial"`.