tests/testthat/test-stepwise-output.R
In cmlopera/olsrr: Tools for Building OLS Regression Models
context("stepwise regression output")
model <- lm(y ~ ., data = surgical)
test_that("output from stepwise regression is as expected", {
x <- cat("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
------------------------------------------------------------------------------------------
Stepwise Selection Summary
------------------------------------------------------------------------------------------
Added/ Adj.
Step Variable Removed R-Square R-Square C(p) AIC RMSE
------------------------------------------------------------------------------------------
1 liver_test addition 0.455 0.444 62.5120 771.8753 296.2992
2 alc_heavy addition 0.567 0.550 41.3680 761.4394 266.6484
3 enzyme_test addition 0.659 0.639 24.3380 750.5089 238.9145
4 pindex addition 0.750 0.730 7.5370 735.7146 206.5835
5 bcs addition 0.781 0.758 3.1920 730.6204 195.4544
------------------------------------------------------------------------------------------")
expect_output(print(ols_step_both_p(model)), x)
})
test_that("output from stepwise regression is as expected when details == TRUE", {
x <- cat("Variable Selection Procedure
Dependent Variable: y
Stepwise Selection: Step 1
Variable liver_test Entered
Model Summary
-----------------------------------------------------------------
R 0.674 RMSE 296.299
R-Squared 0.455 Coef. Var 42.202
Adj. R-Squared 0.444 MSE 87793.232
Pred R-Squared 0.386 MAE 212.857
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 3804272.477 1 3804272.477 43.332 0.0000
Residual 4565248.060 52 87793.232
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
-------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
-------------------------------------------------------------------------------------------
(Intercept) 15.191 111.869 0.136 0.893 -209.290 239.671
liver_test 250.305 38.025 0.674 6.583 0.000 174.003 326.607
-------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 2
Variable alc_heavy Entered
Model Summary
-----------------------------------------------------------------
R 0.753 RMSE 266.648
R-Squared 0.567 Coef. Var 37.979
Adj. R-Squared 0.550 MSE 71101.387
Pred R-Squared 0.487 MAE 187.393
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 4743349.776 2 2371674.888 33.356 0.0000
Residual 3626170.761 51 71101.387
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
--------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
--------------------------------------------------------------------------------------------
(Intercept) -5.069 100.828 -0.050 0.960 -207.490 197.352
liver_test 234.597 34.491 0.632 6.802 0.000 165.353 303.841
alc_heavy 342.183 94.156 0.338 3.634 0.001 153.157 531.208
--------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 3
Variable enzyme_test Entered
Model Summary
-----------------------------------------------------------------
R 0.812 RMSE 238.914
R-Squared 0.659 Coef. Var 34.029
Adj. R-Squared 0.639 MSE 57080.128
Pred R-Squared 0.567 MAE 170.603
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 5515514.136 3 1838504.712 32.209 0.0000
Residual 2854006.401 50 57080.128
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
---------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
---------------------------------------------------------------------------------------------
(Intercept) -344.559 129.156 -2.668 0.010 -603.976 -85.141
liver_test 183.844 33.845 0.495 5.432 0.000 115.865 251.823
alc_heavy 319.662 84.585 0.315 3.779 0.000 149.769 489.555
enzyme_test 6.263 1.703 0.335 3.678 0.001 2.843 9.683
---------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 4
Variable pindex Entered
Model Summary
-----------------------------------------------------------------
R 0.866 RMSE 206.584
R-Squared 0.750 Coef. Var 29.424
Adj. R-Squared 0.730 MSE 42676.744
Pred R-Squared 0.669 MAE 146.473
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 6278360.060 4 1569590.015 36.779 0.0000
Residual 2091160.477 49 42676.744
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
-----------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
-----------------------------------------------------------------------------------------------
(Intercept) -789.012 153.372 -5.144 0.000 -1097.226 -480.799
liver_test 125.474 32.358 0.338 3.878 0.000 60.448 190.499
alc_heavy 359.875 73.754 0.355 4.879 0.000 211.660 508.089
enzyme_test 7.548 1.503 0.404 5.020 0.000 4.527 10.569
pindex 7.876 1.863 0.335 4.228 0.000 4.133 11.620
-----------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 5
Variable bcs Entered
Model Summary
-----------------------------------------------------------------
R 0.884 RMSE 195.454
R-Squared 0.781 Coef. Var 27.839
Adj. R-Squared 0.758 MSE 38202.426
Pred R-Squared 0.700 MAE 137.656
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 6535804.090 5 1307160.818 34.217 0.0000
Residual 1833716.447 48 38202.426
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
------------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
------------------------------------------------------------------------------------------------
(Intercept) -1178.330 208.682 -5.647 0.000 -1597.914 -758.746
liver_test 58.064 40.144 0.156 1.446 0.155 -22.652 138.779
alc_heavy 317.848 71.634 0.314 4.437 0.000 173.818 461.878
enzyme_test 9.748 1.656 0.521 5.887 0.000 6.419 13.077
pindex 8.924 1.808 0.380 4.935 0.000 5.288 12.559
bcs 59.864 23.060 0.241 2.596 0.012 13.498 106.230
------------------------------------------------------------------------------------------------
No more variables to be added or removed.
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
------------------------------------------------------------------------------------------
Stepwise Selection Summary
------------------------------------------------------------------------------------------
Added/ Adj.
Step Variable Removed R-Square R-Square C(p) AIC RMSE
------------------------------------------------------------------------------------------
1 liver_test addition 0.455 0.444 62.5120 771.8753 296.2992
2 alc_heavy addition 0.567 0.550 41.3680 761.4394 266.6484
3 enzyme_test addition 0.659 0.639 24.3380 750.5089 238.9145
4 pindex addition 0.750 0.730 7.5370 735.7146 206.5835
5 bcs addition 0.781 0.758 3.1920 730.6204 195.4544
------------------------------------------------------------------------------------------")
expect_output(print(ols_step_both_p(model, details = TRUE)), x)
})
cmlopera/olsrr documentation built on May 26, 2019, 10:34 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
context("stepwise regression output")
model <- lm(y ~ ., data = surgical)
test_that("output from stepwise regression is as expected", {
x <- cat("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
------------------------------------------------------------------------------------------
Stepwise Selection Summary
------------------------------------------------------------------------------------------
Added/ Adj.
Step Variable Removed R-Square R-Square C(p) AIC RMSE
------------------------------------------------------------------------------------------
1 liver_test addition 0.455 0.444 62.5120 771.8753 296.2992
2 alc_heavy addition 0.567 0.550 41.3680 761.4394 266.6484
3 enzyme_test addition 0.659 0.639 24.3380 750.5089 238.9145
4 pindex addition 0.750 0.730 7.5370 735.7146 206.5835
5 bcs addition 0.781 0.758 3.1920 730.6204 195.4544
------------------------------------------------------------------------------------------")
expect_output(print(ols_step_both_p(model)), x)
})
test_that("output from stepwise regression is as expected when details == TRUE", {
x <- cat("Variable Selection Procedure
Dependent Variable: y
Stepwise Selection: Step 1
Variable liver_test Entered
Model Summary
-----------------------------------------------------------------
R 0.674 RMSE 296.299
R-Squared 0.455 Coef. Var 42.202
Adj. R-Squared 0.444 MSE 87793.232
Pred R-Squared 0.386 MAE 212.857
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 3804272.477 1 3804272.477 43.332 0.0000
Residual 4565248.060 52 87793.232
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
-------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
-------------------------------------------------------------------------------------------
(Intercept) 15.191 111.869 0.136 0.893 -209.290 239.671
liver_test 250.305 38.025 0.674 6.583 0.000 174.003 326.607
-------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 2
Variable alc_heavy Entered
Model Summary
-----------------------------------------------------------------
R 0.753 RMSE 266.648
R-Squared 0.567 Coef. Var 37.979
Adj. R-Squared 0.550 MSE 71101.387
Pred R-Squared 0.487 MAE 187.393
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 4743349.776 2 2371674.888 33.356 0.0000
Residual 3626170.761 51 71101.387
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
--------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
--------------------------------------------------------------------------------------------
(Intercept) -5.069 100.828 -0.050 0.960 -207.490 197.352
liver_test 234.597 34.491 0.632 6.802 0.000 165.353 303.841
alc_heavy 342.183 94.156 0.338 3.634 0.001 153.157 531.208
--------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 3
Variable enzyme_test Entered
Model Summary
-----------------------------------------------------------------
R 0.812 RMSE 238.914
R-Squared 0.659 Coef. Var 34.029
Adj. R-Squared 0.639 MSE 57080.128
Pred R-Squared 0.567 MAE 170.603
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 5515514.136 3 1838504.712 32.209 0.0000
Residual 2854006.401 50 57080.128
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
---------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
---------------------------------------------------------------------------------------------
(Intercept) -344.559 129.156 -2.668 0.010 -603.976 -85.141
liver_test 183.844 33.845 0.495 5.432 0.000 115.865 251.823
alc_heavy 319.662 84.585 0.315 3.779 0.000 149.769 489.555
enzyme_test 6.263 1.703 0.335 3.678 0.001 2.843 9.683
---------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 4
Variable pindex Entered
Model Summary
-----------------------------------------------------------------
R 0.866 RMSE 206.584
R-Squared 0.750 Coef. Var 29.424
Adj. R-Squared 0.730 MSE 42676.744
Pred R-Squared 0.669 MAE 146.473
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 6278360.060 4 1569590.015 36.779 0.0000
Residual 2091160.477 49 42676.744
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
-----------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
-----------------------------------------------------------------------------------------------
(Intercept) -789.012 153.372 -5.144 0.000 -1097.226 -480.799
liver_test 125.474 32.358 0.338 3.878 0.000 60.448 190.499
alc_heavy 359.875 73.754 0.355 4.879 0.000 211.660 508.089
enzyme_test 7.548 1.503 0.404 5.020 0.000 4.527 10.569
pindex 7.876 1.863 0.335 4.228 0.000 4.133 11.620
-----------------------------------------------------------------------------------------------
1 variable(s) added...
Stepwise Selection: Step 5
Variable bcs Entered
Model Summary
-----------------------------------------------------------------
R 0.884 RMSE 195.454
R-Squared 0.781 Coef. Var 27.839
Adj. R-Squared 0.758 MSE 38202.426
Pred R-Squared 0.700 MAE 137.656
-----------------------------------------------------------------
RMSE: Root Mean Square Error
MSE: Mean Square Error
MAE: Mean Absolute Error
ANOVA
-----------------------------------------------------------------------
Sum of
Squares DF Mean Square F Sig.
-----------------------------------------------------------------------
Regression 6535804.090 5 1307160.818 34.217 0.0000
Residual 1833716.447 48 38202.426
Total 8369520.537 53
-----------------------------------------------------------------------
Parameter Estimates
------------------------------------------------------------------------------------------------
model Beta Std. Error Std. Beta t Sig lower upper
------------------------------------------------------------------------------------------------
(Intercept) -1178.330 208.682 -5.647 0.000 -1597.914 -758.746
liver_test 58.064 40.144 0.156 1.446 0.155 -22.652 138.779
alc_heavy 317.848 71.634 0.314 4.437 0.000 173.818 461.878
enzyme_test 9.748 1.656 0.521 5.887 0.000 6.419 13.077
pindex 8.924 1.808 0.380 4.935 0.000 5.288 12.559
bcs 59.864 23.060 0.241 2.596 0.012 13.498 106.230
------------------------------------------------------------------------------------------------
No more variables to be added or removed.
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
------------------------------------------------------------------------------------------
Stepwise Selection Summary
------------------------------------------------------------------------------------------
Added/ Adj.
Step Variable Removed R-Square R-Square C(p) AIC RMSE
------------------------------------------------------------------------------------------
1 liver_test addition 0.455 0.444 62.5120 771.8753 296.2992
2 alc_heavy addition 0.567 0.550 41.3680 761.4394 266.6484
3 enzyme_test addition 0.659 0.639 24.3380 750.5089 238.9145
4 pindex addition 0.750 0.730 7.5370 735.7146 206.5835
5 bcs addition 0.781 0.758 3.1920 730.6204 195.4544
------------------------------------------------------------------------------------------")
expect_output(print(ols_step_both_p(model, details = TRUE)), x)
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.