View source: R/summary.btfit.R
summary.btfit | R Documentation |
summary
method for class "btfit"
## S3 method for class 'btfit' summary(object, subset = NULL, ref = NULL, SE = FALSE, ...)
object |
An object of class "btfit", typically the result |
subset |
A condition for selecting one or more subsets of the components. This can either be a character vector of names of the components (i.e. a subset of |
ref |
A reference item. Either a string with the item name, or the number 1, or NULL. If NULL, then the coefficients are constrained such that their mean is zero. If an item name is given, the coefficient estimates are shifted so that the coefficient for the ref item is zero. If there is more than one component, the components that do not include the ref item will be treated as if ref = NULL. If ref = 1, then the first item of each component is made the reference item. |
SE |
Logical. Whether to include the standard error of the estimate in the |
... |
other arguments |
Note that the values given in the estimate
column of the item_summary
element are NOT the same as the values in object$pi
. Rather, they are the λ_i, where λ_i = \log{π_i} (i.e. the coefficients as found by They are the coefficients, as found by coef.btfit
.). By default, these are normalised so that mean(λ_i) = 0. However, if ref
is not equal to NULL
, then the λ_i in the component in which ref
appears are shifted to λ_i - λ_{ref}, for i = 1, …, K_c, where K_c is the number of items in the component in which ref
appears, and λ_{ref} is the estimate for the reference item.
An S3 object of class "summary.btfit"
. It is a list containing the following components:
item_summary |
A |
component_summary |
A |
Ella Kaye
btfit
, coef.btfit
, vcov.btfit
citations_btdata <- btdata(BradleyTerryScalable::citations) fit1 <- btfit(citations_btdata, 1) summary(fit1) toy_df_4col <- codes_to_counts(BradleyTerryScalable::toy_data, c("W1", "W2", "D")) toy_btdata <- btdata(toy_df_4col) fit2a <- btfit(toy_btdata, 1) summary(fit2a) fit2b <- btfit(toy_btdata, 1.1) summary(fit2b, SE = TRUE) fit2c <- btfit(toy_btdata, 1) summary(fit2c, subset = function(x) "Amy" %in% names(x)) summary(fit2c, subset = function(x) length(x) > 3, ref = "Amy")
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