vcov.Rd
Returns the variance-covariance matrix for the predicted values from object
.
# S3 method for ggeffects vcov(object, vcov.fun = NULL, vcov.type = NULL, vcov.args = NULL, ...)
object | An object of class |
---|---|
vcov.fun | String, indicating the name of the |
vcov.type | Character vector, specifying the estimation type for the
robust covariance matrix estimation (see |
vcov.args | List of named vectors, used as additional arguments that
are passed down to |
... | Currently not used. |
The variance-covariance matrix for the predicted values from object
.
The returned matrix has as many rows (and columns) as possible combinations
of predicted values from the ggpredict()
call. For example, if there
are two variables in the terms
-argument of ggpredict()
with 3 and 4
levels each, there will be 3*4 combinations of predicted values, so the returned
matrix has a 12x12 dimension. In short, nrow(object)
is always equal to
nrow(vcov(object))
. See also 'Examples'.
data(efc) model <- lm(barthtot ~ c12hour + neg_c_7 + c161sex + c172code, data = efc) result <- ggpredict(model, c("c12hour [meansd]", "c161sex")) vcov(result)#> 1 2 3 4 5 6 #> 1 3.62642428 0.71518593 2.922676591 0.011438238 2.21892890 -0.69230945 #> 2 0.71518593 1.74243837 -0.073477976 0.953774462 -0.86214188 0.16511056 #> 3 2.92267659 -0.07347798 2.987294098 -0.008860469 3.05191160 0.05575704 #> 4 0.01143824 0.95377446 -0.008860469 0.933475755 -0.02915918 0.91317705 #> 5 2.21892890 -0.86214188 3.051911604 -0.029159177 3.88489431 0.80382353 #> 6 -0.69230945 0.16511056 0.055757037 0.913177047 0.80382353 1.66124354#> 1 2 3 4 5 6 #> 1.9043173 1.3200145 1.7283790 0.9661655 1.9710135 1.2888924as.data.frame(result)#> x predicted std.error conf.low conf.high group #> 1 -8.3 76.75375 1.9043173 73.02136 80.48615 Male #> 2 -8.3 77.79518 1.3200145 75.20800 80.38236 Female #> 3 42.2 63.96204 1.7283790 60.57448 67.34960 Male #> 4 42.2 65.00347 0.9661655 63.10982 66.89712 Female #> 5 92.7 51.17033 1.9710135 47.30721 55.03344 Male #> 6 92.7 52.21175 1.2888924 49.68557 54.73794 Female# only two predicted values, no further terms # vcov() returns a 2x2 matrix result <- ggpredict(model, "c161sex") vcov(result)#> 1 2 #> 1 2.987290958 -0.008861546 #> 2 -0.008861546 0.933476742# 2 levels for c161sex multiplied by 3 levels for c172code # result in 6 combinations of predicted values # thus vcov() returns a 6x6 matrix result <- ggpredict(model, c("c161sex", "c172code")) vcov(result)#> 1 2 3 4 5 6 #> 1 4.87803294 3.024738355 1.17144377 1.76091479 -0.092379792 -1.94567437 #> 2 3.02473835 2.983277938 2.94181752 0.03225611 -0.009204306 -0.05066472 #> 3 1.17144377 2.941817522 4.71219127 -1.69640257 0.073971180 1.84434493 #> 4 1.76091479 0.032256111 -1.69640257 2.58228744 0.853628756 -0.87502993 #> 5 -0.09237979 -0.009204306 0.07397118 0.85362876 0.936804241 1.01997973 #> 6 -1.94567437 -0.050664722 1.84434493 -0.87502993 1.019979727 2.91498938