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tests/testthat/_snaps/snapshot.md
In rmsMD: Output Results from 'rms' Models for Medical Journals
Snapshot: Feed non-rms modelfit
variable coef_95CI Pvalue
1 (Intercept) 15.369 (14.175 to 16.563) <0.001
2 age 0.306 (0.294 to 0.319) <0.001
3 bmi 0.094 (0.055 to 0.134) <0.001
Snapshot: Warning output for non-rms model without setting exp_coef
The model fit does not belong to the 'rms' class.
You must specify the exp_coef argument to determine table output.
Snapshot: OLS tests - simple model
variable coef_95CI Pvalue
1 age 0.306 (0.293 to 0.319) <0.001
2 bmi 0.095 (0.056 to 0.135) <0.001
3 sex=Female Ref -
4 sex=Male 0.271 (-0.040 to 0.582) 0.087
5 smoking=Never Ref -
6 smoking=Former 0.131 (-0.248 to 0.510) 0.499
7 smoking=Current 0.431 (0.050 to 0.812) 0.027
Snapshot: OLS tests - model with interactions
variable coef_95CI Pvalue
1 age 0.342 (0.260 to 0.425) <0.001
2 bmi 0.167 (-0.001 to 0.336) 0.051
3 age * bmi -0.001 (-0.005 to 0.002) 0.383
Snapshot: OLS tests - model with splines
$simple
variable coef_95CI Pvalue
1 bmi 0.095 (0.056 to 0.134) <0.001
2 RCSoverallP: age F test <0.001
$full
variable coef_95CI Pvalue
1 age 0.293 (0.248 to 0.339) <0.001
2 age' 0.008 (-0.121 to 0.137) 0.904
3 age'' 0.047 (-0.470 to 0.563) 0.859
4 bmi 0.095 (0.056 to 0.134) <0.001
Snapshot: OLS tests - model with splines and interactions
$summary
variable coef_95CI
1 bmi 0.058 (-0.359 to 0.474)
2 sex=Female Ref
3 sex=Male 0.279 (-0.032 to 0.590)
4 RCSoverallP: age (Factor+Higher Order Factors) F test
5 RCSoverallP: age * bmi (Factor+Higher Order Factors) F test
Pvalue
1 0.787
2 -
3 0.079
4 <0.001
5 0.474
$full
variable coef_95CI Pvalue
1 age 0.264 (-0.024 to 0.551) 0.072
2 age' -0.001 (-0.812 to 0.810) 0.997
3 age'' 0.576 (-2.656 to 3.809) 0.727
4 bmi 0.058 (-0.359 to 0.474) 0.787
5 sex=Female Ref -
6 sex=Male 0.279 (-0.032 to 0.590) 0.079
7 age * bmi 0.001 (-0.010 to 0.013) 0.841
8 age' * bmi 0.000 (-0.032 to 0.033) 0.977
9 age'' * bmi -0.022 (-0.150 to 0.106) 0.739
Snapshot: Complete case OLS with splines and covariates
variable coef_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.272 (-0.039 to 0.582) 0.087
3 smoking=Never Ref -
4 smoking=Former 0.124 (-0.255 to 0.504) 0.521
5 smoking=Current 0.426 (0.045 to 0.808) 0.029
6 RCSoverallP: age F test <0.001
7 RCSoverallP: bmi F test <0.001
Snapshot: Complete case LRM without x and y
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.078 (0.927 to 1.255) 0.329
3 smoking=Never Ref -
4 smoking=Former 0.986 (0.806 to 1.207) 0.895
5 smoking=Current 2.079 (1.731 to 2.496) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test 0.014
Snapshot: Complete case LRM with x and y (LR test)
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.078 (0.927 to 1.255) 0.329
3 smoking=Never Ref -
4 smoking=Former 0.986 (0.806 to 1.207) 0.895
5 smoking=Current 2.079 (1.731 to 2.496) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test 0.015
Snapshot: Complete case CPH without x and y
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.943 (0.889 to 1.000) 0.049
3 smoking=Never Ref -
4 smoking=Former 0.982 (0.913 to 1.057) 0.633
5 smoking=Current 2.118 (1.969 to 2.277) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test <0.001
Snapshot: Complete case CPH with x and y (LR test)
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.943 (0.889 to 1.000) 0.049
3 smoking=Never Ref -
4 smoking=Former 0.982 (0.913 to 1.057) 0.633
5 smoking=Current 2.118 (1.969 to 2.277) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test <0.001
Snapshot: LRM tests - simple model
variable OR_95CI Pvalue
1 age 1.096 (1.089 to 1.103) <0.001
2 bmi 1.031 (1.015 to 1.047) <0.001
3 sex=Female Ref -
4 sex=Male 1.023 (0.904 to 1.159) 0.716
5 smoking=Never Ref -
6 smoking=Former 1.067 (0.917 to 1.241) 0.403
7 smoking=Current 1.186 (1.018 to 1.382) 0.028
Snapshot: LRM tests - model with interactions
variable OR_95CI Pvalue
1 age 1.108 (1.063 to 1.154) <0.001
2 bmi 1.053 (0.969 to 1.143) 0.222
3 age * bmi 1.000 (0.998 to 1.001) 0.603
Snapshot: LRM tests - model with splines
variable OR_95CI Pvalue
1 bmi 1.030 (1.014 to 1.047) <0.001
2 RCSoverallP: age Wald test <0.001
Snapshot: CPH tests - simple model
variable HR_95CI Pvalue
1 age 1.020 (1.018 to 1.023) <0.001
2 sex=Female Ref -
3 sex=Male 0.965 (0.910 to 1.023) 0.235
Snapshot: CPH tests - model with interactions
variable HR_95CI Pvalue
1 age 1.021 (1.018 to 1.025) <0.001
2 sex=Female Ref -
3 sex=Male 1.093 (0.846 to 1.411) 0.496
4 age * sex=Male 0.998 (0.993 to 1.002) 0.327
Snapshot: CPH tests - model with splines
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.965 (0.910 to 1.023) 0.233
3 RCSoverallP: age LR test <0.001
Snapshot: CPH tests - model with splines and interactions
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.821 (0.419 to 1.607) 0.565
3 RCSoverallP: age LR test <0.001
4 RCSoverallP: age * sex LR test 0.593
Snapshot: MI OLS with splines and covariates
variable coef_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.271 (-0.061 to 0.604) 0.110
3 smoking=Never Ref -
4 smoking=Former 0.222 (-0.181 to 0.625) 0.280
5 smoking=Current 0.379 (-0.166 to 0.925) 0.173
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test <0.001
Snapshot: MI LRM with wald test
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.094 (0.934 to 1.281) 0.266
3 smoking=Never Ref -
4 smoking=Former 0.996 (0.751 to 1.320) 0.978
5 smoking=Current 1.917 (1.322 to 2.780) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test 0.101
Snapshot: MI CPH with wald test
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.968 (0.910 to 1.030) 0.308
3 smoking=Never Ref -
4 smoking=Former 0.960 (0.891 to 1.035) 0.290
5 smoking=Current 1.866 (1.724 to 2.021) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test <0.001
Snapshot: MI LRM with LR test
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.094 (0.934 to 1.281) 0.265
3 smoking=Never Ref -
4 smoking=Former 0.994 (0.750 to 1.317) 0.965
5 smoking=Current 1.913 (1.319 to 2.774) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test 0.103
Snapshot: MI CPH with LR test
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.969 (0.911 to 1.030) 0.311
3 smoking=Never Ref -
4 smoking=Former 0.960 (0.891 to 1.035) 0.290
5 smoking=Current 1.866 (1.723 to 2.020) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test <0.001
Snapshot: Variables with labels and special names
$summary
variable coef_95CI
1 bmi 0.058 (-0.358 to 0.475)
2 sex=Female Ref
3 sex=Male 0.279 (-0.032 to 0.590)
4 random1 0.067 (-0.089 to 0.223)
5 "random2" 0.011 (-0.144 to 0.166)
6 RCSoverallP: age (Factor+Higher Order Factors) F test
7 RCSoverallP: age * bmi (Factor+Higher Order Factors) F test
Pvalue
1 0.783
2 -
3 0.079
4 0.401
5 0.892
6 <0.001
7 0.464
$hidden
variable coef_95CI
1 bmi 0.058 (-0.358 to 0.475)
2 sex=Female Ref
3 sex=Male 0.279 (-0.032 to 0.590)
4 random1 0.067 (-0.089 to 0.223)
5 "random2" 0.011 (-0.144 to 0.166)
6 RCSoverallP: age (Factor+Higher Order Factors) F test
7 RCSoverallP: age * bmi (Factor+Higher Order Factors) F test
Pvalue
1 0.783
2 -
3 0.079
4 0.401
5 0.892
6 <0.001
7 0.464
Snapshot: Variables with reserved/special names
$structure
[1] "'data.frame':\t5000 obs. of 13 variables:"
[2] " $ age : num 33.4 50.5 40.8 52.5 67.1 58.9 58.4 47.2 52.4 64.5 ..."
[3] " $ bmi : num 26.1 21.5 22.4 25 31.4 27.5 21.5 25.7 29.6 23.3 ..."
[4] " $ sex : Factor w/ 2 levels \"Female\",\"Male\": 2 2 1 1 1 1 1 2 2 1 ..."
[5] " $ smoking : Factor w/ 3 levels \"Never\",\"Former\",..: 2 2 2 1 2 2 3 2 1 2 ..."
[6] " $ majorcomplication: int 0 0 0 0 0 0 0 0 1 0 ..."
[7] " $ lengthstay : num 17.9 29.2 39 25.7 30.1 ..."
[8] " $ time : num 102.1 223.5 27.3 226.3 19.3 ..."
[9] " $ event : int 1 1 1 1 1 1 1 0 1 0 ..."
[10] " $ if : num 2.371 -0.167 0.927 -0.568 0.225 ..."
[11] " ..- attr(*, \"label\")= chr \"Random variable with name 'if'\""
[12] " $ for : num -1.354 -0.579 -0.861 0.973 0.619 ..."
[13] " ..- attr(*, \"label\")= chr \"Random variable with name 'for'\""
[14] " $ while : num -0.836 -0.221 -2.104 -1.668 -1.098 ..."
[15] " ..- attr(*, \"label\")= chr \"Random variable with name 'while'\""
[16] " $ TRUE : num -0.795 -1.135 0.58 0.518 0.208 ..."
[17] " ..- attr(*, \"label\")= chr \"Random variable with name 'TRUE'\""
[18] " $ NULL : num -0.194 0.258 -0.538 -1.179 0.901 ..."
[19] " ..- attr(*, \"label\")= chr \"Random variable with name 'NULL'\""
$summary
variable
1 bmi
2 sex=Female
3 sex=Male
4 if
5 for
6 while
7 TRUE
8 NULL
9 RCSoverallP: age (Factor+Higher Order Factors)
10 RCSoverallP: age * bmi (Factor+Higher Order Factors)
coef_95CI Pvalue
1 0.058 (-0.359 to 0.475) 0.784
2 Ref -
3 0.277 (-0.034 to 0.588) 0.081
4 -0.041 (-0.197 to 0.114) 0.603
5 0.011 (-0.145 to 0.166) 0.894
6 0.016 (-0.138 to 0.171) 0.834
7 -0.090 (-0.247 to 0.067) 0.259
8 0.035 (-0.121 to 0.191) 0.660
9 F test <0.001
10 F test 0.484
$hidden
variable
1 bmi
2 sex=Female
3 sex=Male
4 if
5 for
6 while
7 TRUE
8 NULL
9 RCSoverallP: age (Factor+Higher Order Factors)
10 RCSoverallP: age * bmi (Factor+Higher Order Factors)
coef_95CI Pvalue
1 0.058 (-0.359 to 0.475) 0.784
2 Ref -
3 0.277 (-0.034 to 0.588) 0.081
4 -0.041 (-0.197 to 0.114) 0.603
5 0.011 (-0.145 to 0.166) 0.894
6 0.016 (-0.138 to 0.171) 0.834
7 -0.090 (-0.247 to 0.067) 0.259
8 0.035 (-0.121 to 0.191) 0.660
9 F test <0.001
10 F test 0.484
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Snapshot: Feed non-rms modelfit
variable coef_95CI Pvalue
1 (Intercept) 15.369 (14.175 to 16.563) <0.001
2 age 0.306 (0.294 to 0.319) <0.001
3 bmi 0.094 (0.055 to 0.134) <0.001
Snapshot: Warning output for non-rms model without setting exp_coef
The model fit does not belong to the 'rms' class.
You must specify the exp_coef argument to determine table output.
Snapshot: OLS tests - simple model
variable coef_95CI Pvalue
1 age 0.306 (0.293 to 0.319) <0.001
2 bmi 0.095 (0.056 to 0.135) <0.001
3 sex=Female Ref -
4 sex=Male 0.271 (-0.040 to 0.582) 0.087
5 smoking=Never Ref -
6 smoking=Former 0.131 (-0.248 to 0.510) 0.499
7 smoking=Current 0.431 (0.050 to 0.812) 0.027
Snapshot: OLS tests - model with interactions
variable coef_95CI Pvalue
1 age 0.342 (0.260 to 0.425) <0.001
2 bmi 0.167 (-0.001 to 0.336) 0.051
3 age * bmi -0.001 (-0.005 to 0.002) 0.383
Snapshot: OLS tests - model with splines
$simple
variable coef_95CI Pvalue
1 bmi 0.095 (0.056 to 0.134) <0.001
2 RCSoverallP: age F test <0.001
$full
variable coef_95CI Pvalue
1 age 0.293 (0.248 to 0.339) <0.001
2 age' 0.008 (-0.121 to 0.137) 0.904
3 age'' 0.047 (-0.470 to 0.563) 0.859
4 bmi 0.095 (0.056 to 0.134) <0.001
Snapshot: OLS tests - model with splines and interactions
$summary
variable coef_95CI
1 bmi 0.058 (-0.359 to 0.474)
2 sex=Female Ref
3 sex=Male 0.279 (-0.032 to 0.590)
4 RCSoverallP: age (Factor+Higher Order Factors) F test
5 RCSoverallP: age * bmi (Factor+Higher Order Factors) F test
Pvalue
1 0.787
2 -
3 0.079
4 <0.001
5 0.474
$full
variable coef_95CI Pvalue
1 age 0.264 (-0.024 to 0.551) 0.072
2 age' -0.001 (-0.812 to 0.810) 0.997
3 age'' 0.576 (-2.656 to 3.809) 0.727
4 bmi 0.058 (-0.359 to 0.474) 0.787
5 sex=Female Ref -
6 sex=Male 0.279 (-0.032 to 0.590) 0.079
7 age * bmi 0.001 (-0.010 to 0.013) 0.841
8 age' * bmi 0.000 (-0.032 to 0.033) 0.977
9 age'' * bmi -0.022 (-0.150 to 0.106) 0.739
Snapshot: Complete case OLS with splines and covariates
variable coef_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.272 (-0.039 to 0.582) 0.087
3 smoking=Never Ref -
4 smoking=Former 0.124 (-0.255 to 0.504) 0.521
5 smoking=Current 0.426 (0.045 to 0.808) 0.029
6 RCSoverallP: age F test <0.001
7 RCSoverallP: bmi F test <0.001
Snapshot: Complete case LRM without x and y
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.078 (0.927 to 1.255) 0.329
3 smoking=Never Ref -
4 smoking=Former 0.986 (0.806 to 1.207) 0.895
5 smoking=Current 2.079 (1.731 to 2.496) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test 0.014
Snapshot: Complete case LRM with x and y (LR test)
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.078 (0.927 to 1.255) 0.329
3 smoking=Never Ref -
4 smoking=Former 0.986 (0.806 to 1.207) 0.895
5 smoking=Current 2.079 (1.731 to 2.496) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test 0.015
Snapshot: Complete case CPH without x and y
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.943 (0.889 to 1.000) 0.049
3 smoking=Never Ref -
4 smoking=Former 0.982 (0.913 to 1.057) 0.633
5 smoking=Current 2.118 (1.969 to 2.277) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test <0.001
Snapshot: Complete case CPH with x and y (LR test)
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.943 (0.889 to 1.000) 0.049
3 smoking=Never Ref -
4 smoking=Former 0.982 (0.913 to 1.057) 0.633
5 smoking=Current 2.118 (1.969 to 2.277) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test <0.001
Snapshot: LRM tests - simple model
variable OR_95CI Pvalue
1 age 1.096 (1.089 to 1.103) <0.001
2 bmi 1.031 (1.015 to 1.047) <0.001
3 sex=Female Ref -
4 sex=Male 1.023 (0.904 to 1.159) 0.716
5 smoking=Never Ref -
6 smoking=Former 1.067 (0.917 to 1.241) 0.403
7 smoking=Current 1.186 (1.018 to 1.382) 0.028
Snapshot: LRM tests - model with interactions
variable OR_95CI Pvalue
1 age 1.108 (1.063 to 1.154) <0.001
2 bmi 1.053 (0.969 to 1.143) 0.222
3 age * bmi 1.000 (0.998 to 1.001) 0.603
Snapshot: LRM tests - model with splines
variable OR_95CI Pvalue
1 bmi 1.030 (1.014 to 1.047) <0.001
2 RCSoverallP: age Wald test <0.001
Snapshot: CPH tests - simple model
variable HR_95CI Pvalue
1 age 1.020 (1.018 to 1.023) <0.001
2 sex=Female Ref -
3 sex=Male 0.965 (0.910 to 1.023) 0.235
Snapshot: CPH tests - model with interactions
variable HR_95CI Pvalue
1 age 1.021 (1.018 to 1.025) <0.001
2 sex=Female Ref -
3 sex=Male 1.093 (0.846 to 1.411) 0.496
4 age * sex=Male 0.998 (0.993 to 1.002) 0.327
Snapshot: CPH tests - model with splines
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.965 (0.910 to 1.023) 0.233
3 RCSoverallP: age LR test <0.001
Snapshot: CPH tests - model with splines and interactions
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.821 (0.419 to 1.607) 0.565
3 RCSoverallP: age LR test <0.001
4 RCSoverallP: age * sex LR test 0.593
Snapshot: MI OLS with splines and covariates
variable coef_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.271 (-0.061 to 0.604) 0.110
3 smoking=Never Ref -
4 smoking=Former 0.222 (-0.181 to 0.625) 0.280
5 smoking=Current 0.379 (-0.166 to 0.925) 0.173
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test <0.001
Snapshot: MI LRM with wald test
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.094 (0.934 to 1.281) 0.266
3 smoking=Never Ref -
4 smoking=Former 0.996 (0.751 to 1.320) 0.978
5 smoking=Current 1.917 (1.322 to 2.780) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test 0.101
Snapshot: MI CPH with wald test
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.968 (0.910 to 1.030) 0.308
3 smoking=Never Ref -
4 smoking=Former 0.960 (0.891 to 1.035) 0.290
5 smoking=Current 1.866 (1.724 to 2.021) <0.001
6 RCSoverallP: age Wald test <0.001
7 RCSoverallP: bmi Wald test <0.001
Snapshot: MI LRM with LR test
variable OR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 1.094 (0.934 to 1.281) 0.265
3 smoking=Never Ref -
4 smoking=Former 0.994 (0.750 to 1.317) 0.965
5 smoking=Current 1.913 (1.319 to 2.774) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test 0.103
Snapshot: MI CPH with LR test
variable HR_95CI Pvalue
1 sex=Female Ref -
2 sex=Male 0.969 (0.911 to 1.030) 0.311
3 smoking=Never Ref -
4 smoking=Former 0.960 (0.891 to 1.035) 0.290
5 smoking=Current 1.866 (1.723 to 2.020) <0.001
6 RCSoverallP: age LR test <0.001
7 RCSoverallP: bmi LR test <0.001
Snapshot: Variables with labels and special names
$summary
variable coef_95CI
1 bmi 0.058 (-0.358 to 0.475)
2 sex=Female Ref
3 sex=Male 0.279 (-0.032 to 0.590)
4 random1 0.067 (-0.089 to 0.223)
5 "random2" 0.011 (-0.144 to 0.166)
6 RCSoverallP: age (Factor+Higher Order Factors) F test
7 RCSoverallP: age * bmi (Factor+Higher Order Factors) F test
Pvalue
1 0.783
2 -
3 0.079
4 0.401
5 0.892
6 <0.001
7 0.464
$hidden
variable coef_95CI
1 bmi 0.058 (-0.358 to 0.475)
2 sex=Female Ref
3 sex=Male 0.279 (-0.032 to 0.590)
4 random1 0.067 (-0.089 to 0.223)
5 "random2" 0.011 (-0.144 to 0.166)
6 RCSoverallP: age (Factor+Higher Order Factors) F test
7 RCSoverallP: age * bmi (Factor+Higher Order Factors) F test
Pvalue
1 0.783
2 -
3 0.079
4 0.401
5 0.892
6 <0.001
7 0.464
Snapshot: Variables with reserved/special names
$structure
[1] "'data.frame':\t5000 obs. of 13 variables:"
[2] " $ age : num 33.4 50.5 40.8 52.5 67.1 58.9 58.4 47.2 52.4 64.5 ..."
[3] " $ bmi : num 26.1 21.5 22.4 25 31.4 27.5 21.5 25.7 29.6 23.3 ..."
[4] " $ sex : Factor w/ 2 levels \"Female\",\"Male\": 2 2 1 1 1 1 1 2 2 1 ..."
[5] " $ smoking : Factor w/ 3 levels \"Never\",\"Former\",..: 2 2 2 1 2 2 3 2 1 2 ..."
[6] " $ majorcomplication: int 0 0 0 0 0 0 0 0 1 0 ..."
[7] " $ lengthstay : num 17.9 29.2 39 25.7 30.1 ..."
[8] " $ time : num 102.1 223.5 27.3 226.3 19.3 ..."
[9] " $ event : int 1 1 1 1 1 1 1 0 1 0 ..."
[10] " $ if : num 2.371 -0.167 0.927 -0.568 0.225 ..."
[11] " ..- attr(*, \"label\")= chr \"Random variable with name 'if'\""
[12] " $ for : num -1.354 -0.579 -0.861 0.973 0.619 ..."
[13] " ..- attr(*, \"label\")= chr \"Random variable with name 'for'\""
[14] " $ while : num -0.836 -0.221 -2.104 -1.668 -1.098 ..."
[15] " ..- attr(*, \"label\")= chr \"Random variable with name 'while'\""
[16] " $ TRUE : num -0.795 -1.135 0.58 0.518 0.208 ..."
[17] " ..- attr(*, \"label\")= chr \"Random variable with name 'TRUE'\""
[18] " $ NULL : num -0.194 0.258 -0.538 -1.179 0.901 ..."
[19] " ..- attr(*, \"label\")= chr \"Random variable with name 'NULL'\""
$summary
variable
1 bmi
2 sex=Female
3 sex=Male
4 if
5 for
6 while
7 TRUE
8 NULL
9 RCSoverallP: age (Factor+Higher Order Factors)
10 RCSoverallP: age * bmi (Factor+Higher Order Factors)
coef_95CI Pvalue
1 0.058 (-0.359 to 0.475) 0.784
2 Ref -
3 0.277 (-0.034 to 0.588) 0.081
4 -0.041 (-0.197 to 0.114) 0.603
5 0.011 (-0.145 to 0.166) 0.894
6 0.016 (-0.138 to 0.171) 0.834
7 -0.090 (-0.247 to 0.067) 0.259
8 0.035 (-0.121 to 0.191) 0.660
9 F test <0.001
10 F test 0.484
$hidden
variable
1 bmi
2 sex=Female
3 sex=Male
4 if
5 for
6 while
7 TRUE
8 NULL
9 RCSoverallP: age (Factor+Higher Order Factors)
10 RCSoverallP: age * bmi (Factor+Higher Order Factors)
coef_95CI Pvalue
1 0.058 (-0.359 to 0.475) 0.784
2 Ref -
3 0.277 (-0.034 to 0.588) 0.081
4 -0.041 (-0.197 to 0.114) 0.603
5 0.011 (-0.145 to 0.166) 0.894
6 0.016 (-0.138 to 0.171) 0.834
7 -0.090 (-0.247 to 0.067) 0.259
8 0.035 (-0.121 to 0.191) 0.660
9 F test <0.001
10 F test 0.484
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