Nothing
Code
print(.test_print$bayes$pool)
Output
Pool Object
-----------
Number of Results Combined: 50
Method: rubin
Confidence Level: 0.95
Alternative: two.sided
Results:
========================================================
parameter est se lci uci pval
--------------------------------------------------------
trt_visit_1 7.253 0.781 5.665 8.842 <0.001
lsm_ref_visit_1 7.254 0.566 6.102 8.406 <0.001
lsm_alt_visit_1 14.507 0.479 13.533 15.481 <0.001
trt_visit_3 7.984 0.258 7.448 8.52 <0.001
lsm_ref_visit_3 7.005 0.205 6.575 7.436 <0.001
lsm_alt_visit_3 14.989 0.167 14.641 15.338 <0.001
--------------------------------------------------------
Code
print(.test_print$approxbayes$pool)
Output
Pool Object
-----------
Number of Results Combined: 5
Method: rubin
Confidence Level: 0.9
Alternative: less
Results:
===================================================
parameter est se lci uci pval
---------------------------------------------------
trt_visit_1 7.253 0.781 6.232 Inf 1
lsm_ref_visit_1 7.254 0.566 6.513 Inf 1
lsm_alt_visit_1 14.507 0.479 13.881 Inf 1
trt_visit_2 7.406 0.388 6.898 Inf 1
lsm_ref_visit_2 7.011 0.282 6.643 Inf 1
lsm_alt_visit_2 14.417 0.238 14.106 Inf 1
trt_visit_3 5.359 1.092 3.929 Inf 1
lsm_ref_visit_3 6.723 0.835 5.624 Inf 1
lsm_alt_visit_3 12.082 0.658 11.222 Inf 1
---------------------------------------------------
Code
print(.test_print$condmean_boot$pool$percentile)
Output
Pool Object
-----------
Number of Results Combined: 1 + 5
Method: bootstrap (percentile)
Confidence Level: 0.95
Alternative: greater
Results:
=====================================================
parameter est se lci uci pval
-----------------------------------------------------
trt_visit_1 6.643 <NA> -Inf 7.383 <0.001
lsm_ref_visit_1 7.605 <NA> -Inf 8.126 <0.001
lsm_alt_visit_1 14.248 <NA> -Inf 15.088 <0.001
trt_visit_2 6.906 <NA> -Inf 7.944 <0.001
lsm_ref_visit_2 7.299 <NA> -Inf 7.666 <0.001
lsm_alt_visit_2 14.205 <NA> -Inf 14.977 <0.001
trt_visit_3 4.118 <NA> -Inf 4.257 <0.001
lsm_ref_visit_3 7.514 <NA> -Inf 8.083 <0.001
lsm_alt_visit_3 11.632 <NA> -Inf 11.837 <0.001
-----------------------------------------------------
Code
print(.test_print$condmean_boot$pool$normal)
Output
Pool Object
-----------
Number of Results Combined: 1 + 5
Method: bootstrap (normal)
Confidence Level: 0.95
Alternative: greater
Results:
======================================================
parameter est se lci uci pval
------------------------------------------------------
trt_visit_1 6.643 0.561 -Inf 7.565 <0.001
lsm_ref_visit_1 7.605 1.057 -Inf 9.343 <0.001
lsm_alt_visit_1 14.248 1.163 -Inf 16.161 <0.001
trt_visit_2 6.906 0.852 -Inf 8.308 <0.001
lsm_ref_visit_2 7.299 1.114 -Inf 9.13 <0.001
lsm_alt_visit_2 14.205 0.984 -Inf 15.823 <0.001
trt_visit_3 4.118 0.663 -Inf 5.208 <0.001
lsm_ref_visit_3 7.514 1.003 -Inf 9.165 <0.001
lsm_alt_visit_3 11.632 1.339 -Inf 13.834 <0.001
------------------------------------------------------
Code
print(.test_print$condmean_jack$pool)
Output
Pool Object
-----------
Number of Results Combined: 1 + 35
Method: jackknife
Confidence Level: 0.9
Alternative: two.sided
Results:
========================================================
parameter est se lci uci pval
--------------------------------------------------------
trt_visit_1 7.296 0.784 6.006 8.587 <0.001
lsm_ref_visit_1 7.051 0.766 5.792 8.311 <0.001
lsm_alt_visit_1 14.348 0.74 13.131 15.564 <0.001
trt_visit_2 7.363 0.373 6.749 7.977 <0.001
lsm_ref_visit_2 7.085 0.555 6.173 7.997 <0.001
lsm_alt_visit_2 14.448 0.599 13.463 15.433 <0.001
trt_visit_3 4.593 1.063 2.844 6.342 <0.001
lsm_ref_visit_3 6.469 0.815 5.129 7.809 <0.001
lsm_alt_visit_3 11.062 0.929 9.534 12.59 <0.001
--------------------------------------------------------
Code
print(.test_print$bmlmi$pool)
Output
Pool Object
-----------
Number of Results Combined: 24
Method: bmlmi
Confidence Level: 0.9
Alternative: two.sided
Results:
========================================================
parameter est se lci uci pval
--------------------------------------------------------
trt_visit_1 7.039 0.5 6.032 8.047 <0.001
lsm_ref_visit_1 6.993 1.38 4.212 9.773 0.004
lsm_alt_visit_1 14.032 1.178 11.658 16.406 <0.001
trt_visit_2 7.494 0.403 6.681 8.306 <0.001
lsm_ref_visit_2 6.694 1.278 4.119 9.27 0.003
lsm_alt_visit_2 14.188 1.013 12.146 16.23 <0.001
trt_visit_3 4.737 1.142 2.43 7.044 0.009
lsm_ref_visit_3 6.53 1.097 4.318 8.742 0.002
lsm_alt_visit_3 11.267 1.753 7.734 14.8 0.001
--------------------------------------------------------
Code
print(drawobj_ab)
Output
Draws Object
------------
Number of Samples: 3
Number of Failed Samples: 0
Model Formula: outcome ~ 1 + group + visit + age + sex + visit * group
Imputation Type: random
Method:
name: Approximate Bayes
covariance: ar1
threshold: 0.5
same_cov: TRUE
REML: TRUE
n_samples: 3
Code
print(impute_ab)
Output
Imputation Object
-----------------
Number of Imputed Datasets: 3
Fraction of Missing Data (Original Dataset):
visit_1: 0%
visit_2: 0%
visit_3: 42%
References:
TRT -> Placebo
Placebo -> Placebo
Code
print(analysis_ab)
Output
Analysis Object
---------------
Number of Results: 3
Analysis Function: ancova
Delta Applied: FALSE
Analysis Estimates:
trt_visit_1
lsm_ref_visit_1
lsm_alt_visit_1
trt_visit_2
lsm_ref_visit_2
lsm_alt_visit_2
trt_visit_3
lsm_ref_visit_3
lsm_alt_visit_3
Code
print(drawobj_b)
Output
Draws Object
------------
Number of Samples: 50
Number of Failed Samples: 0
Model Formula: outcome ~ 1 + group + visit + age + sex + visit * group
Imputation Type: random
Method:
name: Bayes
burn_in: 200
burn_between: 1
same_cov: TRUE
n_samples: 50
seed: 859
Code
print(impute_b)
Output
Imputation Object
-----------------
Number of Imputed Datasets: 50
Fraction of Missing Data (Original Dataset):
visit_1: 0%
visit_2: 0%
visit_3: 42%
References:
TRT -> TRT
Placebo -> Placebo
Code
print(analysis_b)
Output
Analysis Object
---------------
Number of Results: 50
Analysis Function: rbmi::ancova
Delta Applied: TRUE
Analysis Estimates:
trt_visit_1
lsm_ref_visit_1
lsm_alt_visit_1
trt_visit_3
lsm_ref_visit_3
lsm_alt_visit_3
Code
print(drawobj_cmb)
Output
Draws Object
------------
Number of Samples: 1 + 0
Number of Failed Samples: 0
Model Formula: outcome ~ 1 + group + visit + age + sex + visit * group
Imputation Type: condmean
Method:
name: Conditional Mean
covariance: ar1
threshold: 0.2
same_cov: TRUE
REML: TRUE
type: bootstrap
n_samples: 0
Code
print(impute_cmb)
Output
Imputation Object
-----------------
Number of Imputed Datasets: 1 + 0
Fraction of Missing Data (Original Dataset):
visit_1: 0%
visit_2: 0%
visit_3: 42%
References:
TRT -> TRT
Placebo -> Placebo
Code
print(analysis_cmb)
Output
Analysis Object
---------------
Number of Results: 1 + 0
Analysis Function: ancova
Delta Applied: FALSE
Analysis Estimates:
trt_visit_1
lsm_ref_visit_1
lsm_alt_visit_1
trt_visit_2
lsm_ref_visit_2
lsm_alt_visit_2
trt_visit_3
lsm_ref_visit_3
lsm_alt_visit_3
Code
print(drawobj_cmj)
Output
Draws Object
------------
Number of Samples: 1 + 35
Number of Failed Samples: 0
Model Formula: outcome ~ 1 + group + visit + age + sex + visit * group
Imputation Type: condmean
Method:
name: Conditional Mean
covariance: us
threshold: 0.5
same_cov: FALSE
REML: TRUE
type: jackknife
Code
print(impute_cmj)
Output
Imputation Object
-----------------
Number of Imputed Datasets: 1 + 35
Fraction of Missing Data (Original Dataset):
visit_1: 0%
visit_2: 0%
visit_3: 46%
References:
TRT -> Placebo
Placebo -> Placebo
Code
print(analysis_cmj)
Output
Analysis Object
---------------
Number of Results: 1 + 35
Analysis Function: ancova
Delta Applied: FALSE
Analysis Estimates:
trt_visit_1
lsm_ref_visit_1
lsm_alt_visit_1
trt_visit_2
lsm_ref_visit_2
lsm_alt_visit_2
trt_visit_3
lsm_ref_visit_3
lsm_alt_visit_3
Code
print(drawobj_bml)
Output
Draws Object
------------
Number of Samples: 6
Number of Failed Samples: 0
Model Formula: outcome ~ 1 + group + visit + age + sex + visit * group
Imputation Type: random
Method:
covariance: cs
threshold: 0.05
same_cov: TRUE
REML: TRUE
B: 6
D: 4
Code
print(impute_bml)
Output
Imputation Object
-----------------
Number of Imputed Datasets: 24
Fraction of Missing Data (Original Dataset):
visit_1: 0%
visit_2: 0%
visit_3: 42%
References:
TRT -> Placebo
Placebo -> Placebo
Code
print(analysis_bml)
Output
Analysis Object
---------------
Number of Results: 24
Analysis Function: compare_prop_lastvisit
Delta Applied: FALSE
Analysis Estimates:
trt
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