blr_step_p_both {blorr} | R Documentation |
Build regression model from a set of candidate predictor variables by entering and removing predictors based on p values, in a stepwise manner until there is no variable left to enter or remove any more.
blr_step_p_both(model, ...) ## Default S3 method: blr_step_p_both(model, pent = 0.1, prem = 0.3, details = FALSE, ...) ## S3 method for class 'blr_step_p_both' plot(x, model = NA, print_plot = TRUE, ...)
model |
An object of class |
... |
Other arguments. |
pent |
p value; variables with p value less than |
prem |
p value; variables with p more than |
details |
Logical; if |
x |
An object of class |
print_plot |
logical; if |
blr_step_p_both
returns an object of class "blr_step_p_both"
.
An object of class "blr_step_p_both"
is a list containing the
following components:
model |
final model; an object of class |
orders |
candidate predictor variables according to the order by which they were added or removed from the model |
method |
addition/deletion |
steps |
total number of steps |
predictors |
variables retained in the model (after addition) |
aic |
akaike information criteria |
bic |
bayesian information criteria |
dev |
deviance |
indvar |
predictors |
Chatterjee, Samprit and Hadi, Ali. Regression Analysis by Example. 5th ed. N.p.: John Wiley & Sons, 2012. Print.
## Not run: # stepwise regression model <- glm(y ~ ., data = stepwise) blr_step_p_both(model) # stepwise regression plot model <- glm(y ~ ., data = stepwise) k <- blr_step_p_both(model) plot(k) # final model k$model ## End(Not run)