Returns weighting variable of a model.
Usage
get_weights(x, ...)
# S3 method for default
get_weights(x, na_rm = FALSE, null_as_ones = FALSE, ...)Arguments
- x
A fitted model.
- ...
Currently not used.
- na_rm
Logical, if
TRUE, removes possible missing values.- null_as_ones
Logical, if
TRUE, will return a vector of1if no weights were specified in the model (as if the weights were all set to 1).
Value
The weighting variable, or NULL if no weights were specified.
If the weighting variable should also be returned (instead of NULL)
when all weights are set to 1 (i.e. no weighting),
set null_as_ones = TRUE.
Examples
data(mtcars)
set.seed(123)
mtcars$weight <- rnorm(nrow(mtcars), 1, .3)
# LMs
m <- lm(mpg ~ wt + cyl + vs, data = mtcars, weights = weight)
get_weights(m)
#> [1] 0.8318573 0.9309468 1.4676125 1.0211525 1.0387863 1.5145195 1.1382749
#> [8] 0.6204816 0.7939441 0.8663014 1.3672245 1.1079441 1.1202314 1.0332048
#> [15] 0.8332477 1.5360739 1.1493551 0.4100149 1.2104068 0.8581626 0.6796529
#> [22] 0.9346075 0.6921987 0.7813326 0.8124882 0.4939920 1.2513361 1.0460119
#> [29] 0.6585589 1.3761445 1.1279393 0.9114786
get_weights(lm(mpg ~ wt, data = mtcars), null_as_ones = TRUE)
#> [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
# GLMs
m <- glm(vs ~ disp + mpg, data = mtcars, weights = weight, family = quasibinomial)
get_weights(m)
#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
#> 0.8318573 0.9309468 1.4676125 1.0211525
#> Hornet Sportabout Valiant Duster 360 Merc 240D
#> 1.0387863 1.5145195 1.1382749 0.6204816
#> Merc 230 Merc 280 Merc 280C Merc 450SE
#> 0.7939441 0.8663014 1.3672245 1.1079441
#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
#> 1.1202314 1.0332048 0.8332477 1.5360739
#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
#> 1.1493551 0.4100149 1.2104068 0.8581626
#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
#> 0.6796529 0.9346075 0.6921987 0.7813326
#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
#> 0.8124882 0.4939920 1.2513361 1.0460119
#> Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
#> 0.6585589 1.3761445 1.1279393 0.9114786
m <- glm(cbind(cyl, gear) ~ mpg, data = mtcars, weights = weight, family = binomial)
get_weights(m)
#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
#> 8.318573 9.309468 11.740900 9.190373
#> Hornet Sportabout Valiant Duster 360 Merc 240D
#> 11.426650 13.630675 12.521023 4.963853
#> Merc 230 Merc 280 Merc 280C Merc 450SE
#> 6.351553 8.663014 13.672245 12.187386
#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
#> 12.322546 11.365253 9.165724 16.896813
#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
#> 12.642907 3.280119 9.683254 6.865301
#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
#> 4.757570 10.280683 7.614185 8.594659
#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
#> 8.937370 3.951936 11.262025 9.414107
#> Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
#> 8.561266 15.137589 14.663210 7.291828