Fix coefficients and update model
Refits a model with a specified set of coefficients.
fix.coef(model, beta = NULL)
model |
An R model, e.g., produced by |
beta |
A numeric vector with |
The function calculates the linear predictor using the new coefficients,
and reformulates the model using the offset
argument. The linear predictor is called
offset, and its coefficient will be 1 by definition.
The new model only fits the intercept, which should be 0
if we set beta = coef(model).
An updated R model object
Stef van Buuren, 2018
model0 <- lm(Volume ~ Girth + Height, data = trees) formula(model0) coef(model0) deviance(model0) # refit same model model1 <- fix.coef(model0) formula(model1) coef(model1) deviance(model1) # change the beta's model2 <- fix.coef(model0, beta = c(-50, 5, 1)) coef(model2) deviance(model2) # compare predictions plot(predict(model0), predict(model1)) abline(0, 1) plot(predict(model0), predict(model2)) abline(0, 1) # compare proportion explained variance cor(predict(model0), predict(model0) + residuals(model0))^2 cor(predict(model1), predict(model1) + residuals(model1))^2 cor(predict(model2), predict(model2) + residuals(model2))^2 # extract offset from constrained model summary(model2$offset) # it also works with factors and missing data model0 <- lm(bmi ~ age + hyp + chl, data = nhanes2) model1 <- fix.coef(model0) model2 <- fix.coef(model0, beta = c(15, -8, -8, 2, 0.2))
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