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tests/testthat/_snaps/tbl_uvregression.md
In gtsummary: Presentation-Ready Data Summary and Analytic Result Tables
lm: no errors/warnings with standard use
Code
mtcars %>% tbl_uvregression(method = lm, y = mpg) %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 cyl 32 -2.9 -3.5, -2.2 <0.001
2 disp 32 -0.04 -0.05, -0.03 <0.001
3 hp 32 -0.07 -0.09, -0.05 <0.001
4 drat 32 7.7 4.6, 11 <0.001
5 wt 32 -5.3 -6.5, -4.2 <0.001
6 qsec 32 1.4 0.27, 2.6 0.017
7 vs 32 7.9 4.6, 11 <0.001
8 am 32 7.2 3.6, 11 <0.001
9 gear 32 3.9 1.3, 6.6 0.005
10 carb 32 -2.1 -3.2, -0.89 0.001
Code
mtcars %>% tbl_uvregression(method = lm, y = "mpg") %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 cyl 32 -2.9 -3.5, -2.2 <0.001
2 disp 32 -0.04 -0.05, -0.03 <0.001
3 hp 32 -0.07 -0.09, -0.05 <0.001
4 drat 32 7.7 4.6, 11 <0.001
5 wt 32 -5.3 -6.5, -4.2 <0.001
6 qsec 32 1.4 0.27, 2.6 0.017
7 vs 32 7.9 4.6, 11 <0.001
8 am 32 7.2 3.6, 11 <0.001
9 gear 32 3.9 1.3, 6.6 0.005
10 carb 32 -2.1 -3.2, -0.89 0.001
geeglm: no errors/warnings with standard use
Code
tbl_uvregression(na.omit(trial), y = age, method = geepack::geeglm,
method.args = list(id = response, corstr = "exchangeable"), include = -response) %>%
as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 Chemotherapy Treatment 173 <NA> <NA> <NA>
2 Drug A <NA> <NA> <NA> <NA>
3 Drug B <NA> 0.51 -3.7, 4.7 0.8
4 Marker Level (ng/mL) 173 0.28 -2.1, 2.6 0.8
5 T Stage 173 <NA> <NA> <NA>
6 T1 <NA> <NA> <NA> <NA>
7 T2 <NA> 2.0 -3.9, 7.8 0.5
8 T3 <NA> 3.0 -2.7, 8.7 0.3
9 T4 <NA> -1.7 -7.7, 4.3 0.6
10 Grade 173 <NA> <NA> <NA>
11 I <NA> <NA> <NA> <NA>
12 II <NA> 0.16 -5.5, 5.8 >0.9
13 III <NA> 2.3 -3.1, 7.8 0.4
14 Patient Died 173 2.3 -1.9, 6.5 0.3
15 Months to Death/Censor 173 -0.21 -0.61, 0.18 0.3
lm specifying tidy_fun: no errors/warnings with standard use
Code
mtcars %>% tbl_uvregression(method = lm, y = mpg, tidy_fun = broom::tidy) %>%
as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 cyl 32 -2.9 -3.5, -2.2 <0.001
2 disp 32 -0.04 -0.05, -0.03 <0.001
3 hp 32 -0.07 -0.09, -0.05 <0.001
4 drat 32 7.7 4.6, 11 <0.001
5 wt 32 -5.3 -6.5, -4.2 <0.001
6 qsec 32 1.4 0.27, 2.6 0.017
7 vs 32 7.9 4.6, 11 <0.001
8 am 32 7.2 3.6, 11 <0.001
9 gear 32 3.9 1.3, 6.6 0.005
10 carb 32 -2.1 -3.2, -0.89 0.001
coxph: no errors/warnings with standard use
Code
coxph_uv %>% as.data.frame()
Output
**Characteristic** **N** **log(HR)** **95% CI** **p-value**
1 inst 227 -0.01 -0.03, 0.01 0.3
2 age 228 0.02 0.00, 0.04 0.042
3 sex 228 -0.53 -0.86, -0.20 0.001
4 ph.ecog 227 0.48 0.25, 0.70 <0.001
5 ph.karno 227 -0.02 -0.03, 0.00 0.005
6 pat.karno 225 -0.02 -0.03, -0.01 <0.001
7 meal.cal 181 0.00 0.00, 0.00 0.6
8 wt.loss 214 0.00 -0.01, 0.01 0.8
glmer: no errors/warnings with standard use
Code
lme4_uv %>% as.data.frame()
Output
**Characteristic** **log(OR)** **95% CI** **p-value**
1 hp -0.01 -0.05, 0.03 0.5
2 No. Cylinders -0.51 -1.4, 0.39 0.3
Code
tbl %>% as.data.frame()
Output
**Characteristic** **log(OR)** **95% CI** **p-value**
1 hp -0.01 -0.05, 0.03 0.5
2 No. Cylinders -0.51 -1.4, 0.39 0.3
tbl_uvregression x= argument tests
Code
ux_x %>% as.data.frame()
Output
**Outcome** **N** **Beta** **95% CI** **p-value**
1 PATIENT AGE 183 3.8 -0.66, 8.3 0.094
2 Marker Level (ng/mL) 183 0.23 -0.04, 0.50 0.10
tbl_uvregression does not throw error with odd variable names in data=
Code
tbl %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 Chemotherapy Treatment 189 <NA> <NA> <NA>
2 Drug A <NA> <NA> <NA> <NA>
3 Drug B <NA> 0.44 -3.7, 4.6 0.8
4 Marker Level (ng/mL) 179 -0.05 -2.5, 2.4 >0.9
5 T Stage 189 <NA> <NA> <NA>
6 T1 <NA> <NA> <NA> <NA>
7 T2 <NA> 1.3 -4.2, 6.9 0.6
8 T3 <NA> 2.6 -3.3, 8.6 0.4
9 T4 <NA> -2.0 -7.8, 3.8 0.5
10 Grade 189 <NA> <NA> <NA>
11 I <NA> <NA> <NA> <NA>
12 II <NA> 1.4 -3.6, 6.4 0.6
13 III <NA> 2.0 -3.1, 7.0 0.4
14 Tumor Response 183 3.8 -0.66, 8.3 0.094
15 Patient Died 189 2.2 -2.0, 6.3 0.3
16 Months to Death/Censor 189 -0.14 -0.54, 0.26 0.5
tbl_uvregression works with survey object
Code
tbl_uvreg %>% as.data.frame()
Output
**Characteristic** **log(OR)** **95% CI** **p-value**
1 Age 0.02 0.00, 0.04 0.10
2 Marker Level (ng/mL) 0.30 -0.06, 0.65 0.10
3 Grade <NA> <NA> <NA>
4 I <NA> <NA> <NA>
5 II -0.06 -0.81, 0.70 0.9
6 III 0.09 -0.65, 0.83 0.8
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lm: no errors/warnings with standard use
Code
mtcars %>% tbl_uvregression(method = lm, y = mpg) %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 cyl 32 -2.9 -3.5, -2.2 <0.001
2 disp 32 -0.04 -0.05, -0.03 <0.001
3 hp 32 -0.07 -0.09, -0.05 <0.001
4 drat 32 7.7 4.6, 11 <0.001
5 wt 32 -5.3 -6.5, -4.2 <0.001
6 qsec 32 1.4 0.27, 2.6 0.017
7 vs 32 7.9 4.6, 11 <0.001
8 am 32 7.2 3.6, 11 <0.001
9 gear 32 3.9 1.3, 6.6 0.005
10 carb 32 -2.1 -3.2, -0.89 0.001
Code
mtcars %>% tbl_uvregression(method = lm, y = "mpg") %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 cyl 32 -2.9 -3.5, -2.2 <0.001
2 disp 32 -0.04 -0.05, -0.03 <0.001
3 hp 32 -0.07 -0.09, -0.05 <0.001
4 drat 32 7.7 4.6, 11 <0.001
5 wt 32 -5.3 -6.5, -4.2 <0.001
6 qsec 32 1.4 0.27, 2.6 0.017
7 vs 32 7.9 4.6, 11 <0.001
8 am 32 7.2 3.6, 11 <0.001
9 gear 32 3.9 1.3, 6.6 0.005
10 carb 32 -2.1 -3.2, -0.89 0.001
geeglm: no errors/warnings with standard use
Code
tbl_uvregression(na.omit(trial), y = age, method = geepack::geeglm,
method.args = list(id = response, corstr = "exchangeable"), include = -response) %>%
as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 Chemotherapy Treatment 173 <NA> <NA> <NA>
2 Drug A <NA> <NA> <NA> <NA>
3 Drug B <NA> 0.51 -3.7, 4.7 0.8
4 Marker Level (ng/mL) 173 0.28 -2.1, 2.6 0.8
5 T Stage 173 <NA> <NA> <NA>
6 T1 <NA> <NA> <NA> <NA>
7 T2 <NA> 2.0 -3.9, 7.8 0.5
8 T3 <NA> 3.0 -2.7, 8.7 0.3
9 T4 <NA> -1.7 -7.7, 4.3 0.6
10 Grade 173 <NA> <NA> <NA>
11 I <NA> <NA> <NA> <NA>
12 II <NA> 0.16 -5.5, 5.8 >0.9
13 III <NA> 2.3 -3.1, 7.8 0.4
14 Patient Died 173 2.3 -1.9, 6.5 0.3
15 Months to Death/Censor 173 -0.21 -0.61, 0.18 0.3
lm specifying tidy_fun: no errors/warnings with standard use
Code
mtcars %>% tbl_uvregression(method = lm, y = mpg, tidy_fun = broom::tidy) %>%
as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 cyl 32 -2.9 -3.5, -2.2 <0.001
2 disp 32 -0.04 -0.05, -0.03 <0.001
3 hp 32 -0.07 -0.09, -0.05 <0.001
4 drat 32 7.7 4.6, 11 <0.001
5 wt 32 -5.3 -6.5, -4.2 <0.001
6 qsec 32 1.4 0.27, 2.6 0.017
7 vs 32 7.9 4.6, 11 <0.001
8 am 32 7.2 3.6, 11 <0.001
9 gear 32 3.9 1.3, 6.6 0.005
10 carb 32 -2.1 -3.2, -0.89 0.001
coxph: no errors/warnings with standard use
Code
coxph_uv %>% as.data.frame()
Output
**Characteristic** **N** **log(HR)** **95% CI** **p-value**
1 inst 227 -0.01 -0.03, 0.01 0.3
2 age 228 0.02 0.00, 0.04 0.042
3 sex 228 -0.53 -0.86, -0.20 0.001
4 ph.ecog 227 0.48 0.25, 0.70 <0.001
5 ph.karno 227 -0.02 -0.03, 0.00 0.005
6 pat.karno 225 -0.02 -0.03, -0.01 <0.001
7 meal.cal 181 0.00 0.00, 0.00 0.6
8 wt.loss 214 0.00 -0.01, 0.01 0.8
glmer: no errors/warnings with standard use
Code
lme4_uv %>% as.data.frame()
Output
**Characteristic** **log(OR)** **95% CI** **p-value**
1 hp -0.01 -0.05, 0.03 0.5
2 No. Cylinders -0.51 -1.4, 0.39 0.3
Code
tbl %>% as.data.frame()
Output
**Characteristic** **log(OR)** **95% CI** **p-value**
1 hp -0.01 -0.05, 0.03 0.5
2 No. Cylinders -0.51 -1.4, 0.39 0.3
tbl_uvregression x= argument tests
Code
ux_x %>% as.data.frame()
Output
**Outcome** **N** **Beta** **95% CI** **p-value**
1 PATIENT AGE 183 3.8 -0.66, 8.3 0.094
2 Marker Level (ng/mL) 183 0.23 -0.04, 0.50 0.10
tbl_uvregression does not throw error with odd variable names in data=
Code
tbl %>% as.data.frame()
Output
**Characteristic** **N** **Beta** **95% CI** **p-value**
1 Chemotherapy Treatment 189 <NA> <NA> <NA>
2 Drug A <NA> <NA> <NA> <NA>
3 Drug B <NA> 0.44 -3.7, 4.6 0.8
4 Marker Level (ng/mL) 179 -0.05 -2.5, 2.4 >0.9
5 T Stage 189 <NA> <NA> <NA>
6 T1 <NA> <NA> <NA> <NA>
7 T2 <NA> 1.3 -4.2, 6.9 0.6
8 T3 <NA> 2.6 -3.3, 8.6 0.4
9 T4 <NA> -2.0 -7.8, 3.8 0.5
10 Grade 189 <NA> <NA> <NA>
11 I <NA> <NA> <NA> <NA>
12 II <NA> 1.4 -3.6, 6.4 0.6
13 III <NA> 2.0 -3.1, 7.0 0.4
14 Tumor Response 183 3.8 -0.66, 8.3 0.094
15 Patient Died 189 2.2 -2.0, 6.3 0.3
16 Months to Death/Censor 189 -0.14 -0.54, 0.26 0.5
tbl_uvregression works with survey object
Code
tbl_uvreg %>% as.data.frame()
Output
**Characteristic** **log(OR)** **95% CI** **p-value**
1 Age 0.02 0.00, 0.04 0.10
2 Marker Level (ng/mL) 0.30 -0.06, 0.65 0.10
3 Grade <NA> <NA> <NA>
4 I <NA> <NA> <NA>
5 II -0.06 -0.81, 0.70 0.9
6 III 0.09 -0.65, 0.83 0.8
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