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.

ols_step_both_p(model, ...)
# S3 method for default
ols_step_both_p(model, pent = 0.1, prem = 0.3,
details = FALSE, ...)
# S3 method for ols_step_both_p
plot(x, model = NA, ...)

## Arguments

model |
An object of class `lm` ; the model should include all
candidate predictor variables. |

... |
Other arguments. |

pent |
p value; variables with p value less than `pent` will enter
into the model. |

prem |
p value; variables with p more than `prem` will be removed
from the model. |

details |
Logical; if `TRUE` , will print the regression result at
each step. |

x |
An object of class `ols_step_both_p` . |

## Value

`ols_step_both_p`

returns an object of class `"ols_step_both_p"`

.
An object of class `"ols_step_both_p"`

is a list containing the
following components:

modelfinal model; an object of class `lm`

orderscandidate predictor variables according to the order by which they were added or removed from the model

methodaddition/deletion

stepstotal number of steps

predictorsvariables retained in the model (after addition)

rsquarecoefficient of determination

aicakaike information criteria

sbcbayesian information criteria

sbicsawa's bayesian information criteria

adjradjusted r-square

rmseroot mean square error

mallows_cpmallow's Cp

indvarpredictors

## Deprecated Function

`ols_stepwise()`

has been deprecated. Instead use `ols_step_both_p()`

.

## References

Chatterjee, Samprit and Hadi, Ali. Regression Analysis by Example. 5th ed. N.p.: John Wiley & Sons, 2012. Print.

## Examples

#> Stepwise Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. bcs
#> 2. pindex
#> 3. enzyme_test
#> 4. liver_test
#> 5. age
#> 6. gender
#> 7. alc_mod
#> 8. alc_heavy
#>
#> We are selecting variables based on p value...
#>
#> Variables Entered/Removed:
#>

#> Error in subtract(., b): could not find function "subtract"

#> Stepwise Selection Method
#> ---------------------------
#>
#> Candidate Terms:
#>
#> 1. bcs
#> 2. pindex
#> 3. enzyme_test
#> 4. liver_test
#> 5. age
#> 6. gender
#> 7. alc_mod
#> 8. alc_heavy
#>
#> We are selecting variables based on p value...
#>
#> Variables Entered/Removed:
#>

#> Error in subtract(., b): could not find function "subtract"

#> Error in plot(k): object 'k' not found

# final model
k$model

#> Error in eval(expr, envir, enclos): object 'k' not found