Nothing
tests/testthat/_snaps/h_logistic_regression.md
In tern: Create Common TLGs Used in Clinical Trials
h_get_interaction_vars works as expected
Code
res
Output
[1] "ARMCD" "RACE"
h_interaction_coef_name works as expected
Code
res
Output
[1] "ARMCDARM B:RACEWHITE"
h_or_cat_interaction works as expected
Code
res
Output
$or
ARMCDARM B
0.2413265
$ci
lcl ucl
0.022360 2.604584
h_or_cont_interaction works as expected with median increment
Code
res
Output
NULL
Code
res
Output
[1] "or" "ci"
Code
res
Output
[1] "or" "ci"
Code
res
Output
[1] "or" "ci"
Code
res
Output
$or
[1] 1.309155
$ci
lcl ucl
1.002180 1.710157
h_or_cont_interaction works as expected with custom increments
Code
res
Output
[1] "25" "30" "40"
Code
res
Output
[1] "25" "30" "40"
h_simple_term_labels works correctly with factor input
Code
res
Output
[1] "B, n = 2" "C, n = 1"
h_interaction_term_labels works correctly with factor input
Code
res
Output
[1] "B * 2, n = 1" "C * 3, n = 0"
h_interaction_term_labels works correctly when any term can be fulfilled
Code
res
Output
[1] "B or 2, n = 3"
h_glm_simple_term_extract works for factor and numeric variables
Code
res
Output
variable variable_label term
1 RACE Race ASIAN
2 RACE Race BLACK OR AFRICAN AMERICAN
3 RACE Race WHITE
term_label interaction interaction_label reference
1 Reference ASIAN, n = 110
2 BLACK OR AFRICAN AMERICAN, n = 40
3 WHITE, n = 34
reference_label estimate std_error df pvalue is_variable_summary
1 2 0.7967307 TRUE
2 17.92262 4001.705 1 0.9964265 FALSE
3 -0.6562766 0.9735107 1 0.5002262 FALSE
is_term_summary
1 FALSE
2 TRUE
3 TRUE
Code
res
Output
variable variable_label term term_label interaction interaction_label
1 AGE Age AGE Age
reference reference_label estimate std_error df pvalue
1 0.1698216 0.09524116 1 0.07457501
is_variable_summary is_term_summary
1 FALSE TRUE
h_glm_simple_term_extract can extract continuous variable results from clogit objects
Code
res
Output
variable variable_label term
"AGE" "AGE" "AGE"
term_label interaction interaction_label
"AGE" "" ""
reference reference_label estimate
"" "" "0.018435221512945"
std_error df pvalue
"0.0242935223263706" "1" "0.447940270007941"
is_variable_summary is_term_summary
"FALSE" "TRUE"
h_glm_interaction_extract works for categorical interaction
Code
res
Output
variable variable_label
1 ARMCD:RACE Interaction of Planned Arm Code * Race
2 ARMCD:RACE Interaction of Planned Arm Code * Race
3 ARMCD:RACE Interaction of Planned Arm Code * Race
4 ARMCD:RACE Interaction of Planned Arm Code * Race
5 ARMCD:RACE Interaction of Planned Arm Code * Race
term term_label
1 ARMCD * RACE Reference ARM A or ASIAN, n = 136
2 ARM B * BLACK OR AFRICAN AMERICAN ARM B * BLACK OR AFRICAN AMERICAN, n = 13
3 ARM C * BLACK OR AFRICAN AMERICAN ARM C * BLACK OR AFRICAN AMERICAN, n = 12
4 ARM B * WHITE ARM B * WHITE, n = 12
5 ARM C * WHITE ARM C * WHITE, n = 11
interaction interaction_label reference reference_label estimate std_error
1
2 1.018378 10415.13
3 -17.92633 11842.72
4 -18.10507 8366.027
5 -17.10294 12735.87
df pvalue is_variable_summary is_term_summary
1 4 1 TRUE FALSE
2 1 0.999922 FALSE TRUE
3 1 0.9987922 FALSE TRUE
4 1 0.9982733 FALSE TRUE
5 1 0.9989285 FALSE TRUE
h_glm_interaction_extract works for continuous interaction
Code
res
Output
variable variable_label term term_label
1 ARMCD:AGE Interaction of Planned Arm Code * Age ARM A Reference ARM A, n = 64
2 ARMCD:AGE Interaction of Planned Arm Code * Age ARM B ARM B, n = 68
3 ARMCD:AGE Interaction of Planned Arm Code * Age ARM C ARM C, n = 52
interaction interaction_label reference reference_label estimate std_error
1
2 0.3081205 0.2062392
3 0.02948826 548.5923
df pvalue is_variable_summary is_term_summary
1 2 0.3275837 TRUE FALSE
2 1 0.1351767 FALSE TRUE
3 1 0.9999571 FALSE TRUE
h_logistic_simple_terms works
Code
res
Output
variable variable_label term term_label interaction
1 AGE Age AGE Age
2 SEX Sex F Reference F, n = 100
3 SEX Sex M M, n = 84
interaction_label reference reference_label estimate std_error df
1 0.1577267 0.09400483 1
2
3 0.6337791 0.9367545 1
pvalue is_variable_summary is_term_summary odds_ratio lcl ucl
1 0.09337495 FALSE TRUE 1.170846 0.9738292 1.407722
2 TRUE FALSE
3 0.4986794 FALSE TRUE 1.88472 0.3005245 11.8199
ci
1 0.9738292, 1.4077220
2
3 0.3005245, 11.8198956
Code
res
Output
variable variable_label term term_label interaction
1 SEX Sex F Reference F, n = 100
2 SEX Sex M M, n = 84
interaction_label reference reference_label estimate std_error df pvalue
1
2 0.6337791 0.9367545 1 0.4986794
is_variable_summary is_term_summary odds_ratio lcl ucl
1 TRUE FALSE
2 FALSE TRUE 1.88472 0.1687832 21.04575
ci
1
2 0.1687832, 21.0457529
h_logistic_simple_terms can extract continuous variable results from clogit objects
Code
res
Output
variable variable_label term
"AGE" "AGE" "AGE"
term_label interaction interaction_label
"AGE" "" ""
reference reference_label estimate
"" "" "0.018435221512945"
std_error df pvalue
"0.0242935223263706" "1" "0.447940270007941"
is_variable_summary is_term_summary odds_ratio
"FALSE" "TRUE" "1.01860619926387"
lcl ucl ci1
"0.971242395138309" "1.06827975629198" "0.971242395138309"
ci2
"1.06827975629198"
h_glm_inter_term_extract works as expected with categorical interaction
Code
res
Output
variable variable_label term term_label interaction
1 ARMCD Planned Arm Code ARM A Reference ARM A, n = 64
2 ARMCD Planned Arm Code ARM B ARM B, n = 68
ARM B1 ARMCD Planned Arm Code ARM B ARM B, n = 68 RACE
ARM B2 ARMCD Planned Arm Code ARM B ARM B, n = 68 RACE
ARM B3 ARMCD Planned Arm Code ARM B ARM B, n = 68 RACE
3 ARMCD Planned Arm Code ARM C ARM C, n = 52
ARM C1 ARMCD Planned Arm Code ARM C ARM C, n = 52 RACE
ARM C2 ARMCD Planned Arm Code ARM C ARM C, n = 52 RACE
ARM C3 ARMCD Planned Arm Code ARM C ARM C, n = 52 RACE
interaction_label reference reference_label
1
2
ARM B1 Race ASIAN ASIAN
ARM B2 Race BLACK OR AFRICAN AMERICAN BLACK OR AFRICAN AMERICAN
ARM B3 Race WHITE WHITE
3
ARM C1 Race ASIAN ASIAN
ARM C2 Race BLACK OR AFRICAN AMERICAN BLACK OR AFRICAN AMERICAN
ARM C3 Race WHITE WHITE
estimate std_error odds_ratio lcl ucl df pvalue
1 NA NA NA 2 0.5036187
2 -1.421604 1.213735 NA NA NA 1 0.2414927
ARM B1 NA NA 2.413265e-01 0.02236 2.604584 NA NA
ARM B2 NA NA 6.681606e-01 0.00000 Inf NA NA
ARM B3 NA NA 3.308830e-09 0.00000 Inf NA NA
3 17.53699 5222.122 NA NA NA 1 0.9973205
ARM C1 NA NA 4.132557e+07 0.00000 Inf NA NA
ARM C2 NA NA 6.775023e-01 0.00000 Inf NA NA
ARM C3 NA NA 1.543498e+00 0.00000 Inf NA NA
is_variable_summary is_term_summary is_reference_summary
1 TRUE FALSE FALSE
2 FALSE TRUE FALSE
ARM B1 FALSE FALSE TRUE
ARM B2 FALSE FALSE TRUE
ARM B3 FALSE FALSE TRUE
3 FALSE TRUE FALSE
ARM C1 FALSE FALSE TRUE
ARM C2 FALSE FALSE TRUE
ARM C3 FALSE FALSE TRUE
h_logistic_inter_terms works as expected
Code
res
Output
[1] "AGE" "ARMCD" "ARMCD" "ARMCD" "ARMCD" "ARMCD"
[7] "ARMCD" "ARMCD" "SEX" "SEX" "SEX" "SEX"
[13] "SEX" "ARMCD:SEX" "ARMCD:SEX" "ARMCD:SEX"
Code
res
Output
[1] "Age" "Reference ARM A, n = 64"
[3] "ARM B, n = 68" "ARM B, n = 68"
[5] "ARM B, n = 68" "ARM C, n = 52"
[7] "ARM C, n = 52" "ARM C, n = 52"
[9] "Reference F, n = 100" "M, n = 84"
[11] "M, n = 84" "M, n = 84"
[13] "M, n = 84" "Reference ARM A or F, n = 129"
[15] "ARM B * M, n = 31" "ARM C * M, n = 24"
Code
res
Output
[1] "F" "M" "ARM A" "ARM B" "ARM B" "ARM C" "ARM C" "AGE" "AGE"
[10] "AGE" "AGE" "ARM A" "ARM B" "ARM C"
Code
res
Output
[1] "Reference F, n = 100" "M, n = 84"
[3] "Reference ARM A, n = 64" "ARM B, n = 68"
[5] "ARM B, n = 68" "ARM C, n = 52"
[7] "ARM C, n = 52" "Age"
[9] "Age" "Age"
[11] "Age" "Reference ARM A, n = 64"
[13] "ARM B, n = 68" "ARM C, n = 52"
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h_get_interaction_vars works as expected
Code
res
Output
[1] "ARMCD" "RACE"
h_interaction_coef_name works as expected
Code
res
Output
[1] "ARMCDARM B:RACEWHITE"
h_or_cat_interaction works as expected
Code
res
Output
$or
ARMCDARM B
0.2413265
$ci
lcl ucl
0.022360 2.604584
h_or_cont_interaction works as expected with median increment
Code
res
Output
NULL
Code
res
Output
[1] "or" "ci"
Code
res
Output
[1] "or" "ci"
Code
res
Output
[1] "or" "ci"
Code
res
Output
$or
[1] 1.309155
$ci
lcl ucl
1.002180 1.710157
h_or_cont_interaction works as expected with custom increments
Code
res
Output
[1] "25" "30" "40"
Code
res
Output
[1] "25" "30" "40"
h_simple_term_labels works correctly with factor input
Code
res
Output
[1] "B, n = 2" "C, n = 1"
h_interaction_term_labels works correctly with factor input
Code
res
Output
[1] "B * 2, n = 1" "C * 3, n = 0"
h_interaction_term_labels works correctly when any term can be fulfilled
Code
res
Output
[1] "B or 2, n = 3"
h_glm_simple_term_extract works for factor and numeric variables
Code
res
Output
variable variable_label term
1 RACE Race ASIAN
2 RACE Race BLACK OR AFRICAN AMERICAN
3 RACE Race WHITE
term_label interaction interaction_label reference
1 Reference ASIAN, n = 110
2 BLACK OR AFRICAN AMERICAN, n = 40
3 WHITE, n = 34
reference_label estimate std_error df pvalue is_variable_summary
1 2 0.7967307 TRUE
2 17.92262 4001.705 1 0.9964265 FALSE
3 -0.6562766 0.9735107 1 0.5002262 FALSE
is_term_summary
1 FALSE
2 TRUE
3 TRUE
Code
res
Output
variable variable_label term term_label interaction interaction_label
1 AGE Age AGE Age
reference reference_label estimate std_error df pvalue
1 0.1698216 0.09524116 1 0.07457501
is_variable_summary is_term_summary
1 FALSE TRUE
h_glm_simple_term_extract can extract continuous variable results from clogit objects
Code
res
Output
variable variable_label term
"AGE" "AGE" "AGE"
term_label interaction interaction_label
"AGE" "" ""
reference reference_label estimate
"" "" "0.018435221512945"
std_error df pvalue
"0.0242935223263706" "1" "0.447940270007941"
is_variable_summary is_term_summary
"FALSE" "TRUE"
h_glm_interaction_extract works for categorical interaction
Code
res
Output
variable variable_label
1 ARMCD:RACE Interaction of Planned Arm Code * Race
2 ARMCD:RACE Interaction of Planned Arm Code * Race
3 ARMCD:RACE Interaction of Planned Arm Code * Race
4 ARMCD:RACE Interaction of Planned Arm Code * Race
5 ARMCD:RACE Interaction of Planned Arm Code * Race
term term_label
1 ARMCD * RACE Reference ARM A or ASIAN, n = 136
2 ARM B * BLACK OR AFRICAN AMERICAN ARM B * BLACK OR AFRICAN AMERICAN, n = 13
3 ARM C * BLACK OR AFRICAN AMERICAN ARM C * BLACK OR AFRICAN AMERICAN, n = 12
4 ARM B * WHITE ARM B * WHITE, n = 12
5 ARM C * WHITE ARM C * WHITE, n = 11
interaction interaction_label reference reference_label estimate std_error
1
2 1.018378 10415.13
3 -17.92633 11842.72
4 -18.10507 8366.027
5 -17.10294 12735.87
df pvalue is_variable_summary is_term_summary
1 4 1 TRUE FALSE
2 1 0.999922 FALSE TRUE
3 1 0.9987922 FALSE TRUE
4 1 0.9982733 FALSE TRUE
5 1 0.9989285 FALSE TRUE
h_glm_interaction_extract works for continuous interaction
Code
res
Output
variable variable_label term term_label
1 ARMCD:AGE Interaction of Planned Arm Code * Age ARM A Reference ARM A, n = 64
2 ARMCD:AGE Interaction of Planned Arm Code * Age ARM B ARM B, n = 68
3 ARMCD:AGE Interaction of Planned Arm Code * Age ARM C ARM C, n = 52
interaction interaction_label reference reference_label estimate std_error
1
2 0.3081205 0.2062392
3 0.02948826 548.5923
df pvalue is_variable_summary is_term_summary
1 2 0.3275837 TRUE FALSE
2 1 0.1351767 FALSE TRUE
3 1 0.9999571 FALSE TRUE
h_logistic_simple_terms works
Code
res
Output
variable variable_label term term_label interaction
1 AGE Age AGE Age
2 SEX Sex F Reference F, n = 100
3 SEX Sex M M, n = 84
interaction_label reference reference_label estimate std_error df
1 0.1577267 0.09400483 1
2
3 0.6337791 0.9367545 1
pvalue is_variable_summary is_term_summary odds_ratio lcl ucl
1 0.09337495 FALSE TRUE 1.170846 0.9738292 1.407722
2 TRUE FALSE
3 0.4986794 FALSE TRUE 1.88472 0.3005245 11.8199
ci
1 0.9738292, 1.4077220
2
3 0.3005245, 11.8198956
Code
res
Output
variable variable_label term term_label interaction
1 SEX Sex F Reference F, n = 100
2 SEX Sex M M, n = 84
interaction_label reference reference_label estimate std_error df pvalue
1
2 0.6337791 0.9367545 1 0.4986794
is_variable_summary is_term_summary odds_ratio lcl ucl
1 TRUE FALSE
2 FALSE TRUE 1.88472 0.1687832 21.04575
ci
1
2 0.1687832, 21.0457529
h_logistic_simple_terms can extract continuous variable results from clogit objects
Code
res
Output
variable variable_label term
"AGE" "AGE" "AGE"
term_label interaction interaction_label
"AGE" "" ""
reference reference_label estimate
"" "" "0.018435221512945"
std_error df pvalue
"0.0242935223263706" "1" "0.447940270007941"
is_variable_summary is_term_summary odds_ratio
"FALSE" "TRUE" "1.01860619926387"
lcl ucl ci1
"0.971242395138309" "1.06827975629198" "0.971242395138309"
ci2
"1.06827975629198"
h_glm_inter_term_extract works as expected with categorical interaction
Code
res
Output
variable variable_label term term_label interaction
1 ARMCD Planned Arm Code ARM A Reference ARM A, n = 64
2 ARMCD Planned Arm Code ARM B ARM B, n = 68
ARM B1 ARMCD Planned Arm Code ARM B ARM B, n = 68 RACE
ARM B2 ARMCD Planned Arm Code ARM B ARM B, n = 68 RACE
ARM B3 ARMCD Planned Arm Code ARM B ARM B, n = 68 RACE
3 ARMCD Planned Arm Code ARM C ARM C, n = 52
ARM C1 ARMCD Planned Arm Code ARM C ARM C, n = 52 RACE
ARM C2 ARMCD Planned Arm Code ARM C ARM C, n = 52 RACE
ARM C3 ARMCD Planned Arm Code ARM C ARM C, n = 52 RACE
interaction_label reference reference_label
1
2
ARM B1 Race ASIAN ASIAN
ARM B2 Race BLACK OR AFRICAN AMERICAN BLACK OR AFRICAN AMERICAN
ARM B3 Race WHITE WHITE
3
ARM C1 Race ASIAN ASIAN
ARM C2 Race BLACK OR AFRICAN AMERICAN BLACK OR AFRICAN AMERICAN
ARM C3 Race WHITE WHITE
estimate std_error odds_ratio lcl ucl df pvalue
1 NA NA NA 2 0.5036187
2 -1.421604 1.213735 NA NA NA 1 0.2414927
ARM B1 NA NA 2.413265e-01 0.02236 2.604584 NA NA
ARM B2 NA NA 6.681606e-01 0.00000 Inf NA NA
ARM B3 NA NA 3.308830e-09 0.00000 Inf NA NA
3 17.53699 5222.122 NA NA NA 1 0.9973205
ARM C1 NA NA 4.132557e+07 0.00000 Inf NA NA
ARM C2 NA NA 6.775023e-01 0.00000 Inf NA NA
ARM C3 NA NA 1.543498e+00 0.00000 Inf NA NA
is_variable_summary is_term_summary is_reference_summary
1 TRUE FALSE FALSE
2 FALSE TRUE FALSE
ARM B1 FALSE FALSE TRUE
ARM B2 FALSE FALSE TRUE
ARM B3 FALSE FALSE TRUE
3 FALSE TRUE FALSE
ARM C1 FALSE FALSE TRUE
ARM C2 FALSE FALSE TRUE
ARM C3 FALSE FALSE TRUE
h_logistic_inter_terms works as expected
Code
res
Output
[1] "AGE" "ARMCD" "ARMCD" "ARMCD" "ARMCD" "ARMCD"
[7] "ARMCD" "ARMCD" "SEX" "SEX" "SEX" "SEX"
[13] "SEX" "ARMCD:SEX" "ARMCD:SEX" "ARMCD:SEX"
Code
res
Output
[1] "Age" "Reference ARM A, n = 64"
[3] "ARM B, n = 68" "ARM B, n = 68"
[5] "ARM B, n = 68" "ARM C, n = 52"
[7] "ARM C, n = 52" "ARM C, n = 52"
[9] "Reference F, n = 100" "M, n = 84"
[11] "M, n = 84" "M, n = 84"
[13] "M, n = 84" "Reference ARM A or F, n = 129"
[15] "ARM B * M, n = 31" "ARM C * M, n = 24"
Code
res
Output
[1] "F" "M" "ARM A" "ARM B" "ARM B" "ARM C" "ARM C" "AGE" "AGE"
[10] "AGE" "AGE" "ARM A" "ARM B" "ARM C"
Code
res
Output
[1] "Reference F, n = 100" "M, n = 84"
[3] "Reference ARM A, n = 64" "ARM B, n = 68"
[5] "ARM B, n = 68" "ARM C, n = 52"
[7] "ARM C, n = 52" "Age"
[9] "Age" "Age"
[11] "Age" "Reference ARM A, n = 64"
[13] "ARM B, n = 68" "ARM C, n = 52"
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