update egt05 #535

clarkliming · 2023-06-09T05:23:37Z

close #413

in preprocessing, remove filter of PARAMCD == "QT" (users could use filters or in pre function to modify it)

also split parameter by page
found bug and raised at

insightsengineering/rtables#653

also blocked by

insightsengineering/rtables#651

github-actions · 2023-06-09T05:32:24Z

🧪 $Test coverage: 98.38%$

Code Coverage Summary

Filename                     Stmts    Miss  Cover    Missing
-------------------------  -------  ------  -------  ----------------
R/ael01_nollt.R                 17       1  94.12%   61
R/aet01_aesi.R                 147       1  99.32%   209
R/aet01.R                       92       1  98.91%   156
R/aet02.R                       57       0  100.00%
R/aet03.R                       76       0  100.00%
R/aet04.R                       88       0  100.00%
R/aet10.R                       42       0  100.00%
R/assertions.R                  99       6  93.94%   88-93
R/cfbt01.R                     116       0  100.00%
R/checks.R                      14       0  100.00%
R/chevron_tlg-S4class.R         21       0  100.00%
R/chevron_tlg-S4methods.R      109       0  100.00%
R/cmt01a.R                      76       0  100.00%
R/coxt02.R                      40       1  97.50%   114
R/dmt01.R                       26       0  100.00%
R/dst01.R                       94       0  100.00%
R/dtht01.R                     102       6  94.12%   48, 52-56
R/egt02.R                       36       0  100.00%
R/egt03.R                       61       1  98.36%   127
R/egt05_qtcat.R                 60       0  100.00%
R/ext01.R                       46       4  91.30%   110-111, 115-116
R/fstg01.R                      42       1  97.62%   95
R/kmg01.R                       28       1  96.43%   69
R/lbt04.R                       69       0  100.00%
R/lbt05.R                       66       5  92.42%   125-130
R/lbt06.R                       63       3  95.24%   132-135
R/lbt07.R                       93       0  100.00%
R/lbt14.R                       57       0  100.00%
R/mht01.R                       71       0  100.00%
R/mng01.R                      113       1  99.12%   128
R/pdt01.R                       59       0  100.00%
R/pdt02.R                       66       0  100.00%
R/rmpt01.R                      46       2  95.65%   90, 110
R/rspt01.R                      73       3  95.89%   156-159
R/rtables_utils.R              161       2  98.76%   41, 98
R/standard_rules.R              11       0  100.00%
R/ttet01.R                     126       3  97.62%   226-229
R/utils.R                       50       0  100.00%
R/vst02.R                       46       1  97.83%   106
TOTAL                         2659      43  98.38%

Diff against main

Filename           Stmts    Miss  Cover
---------------  -------  ------  --------
R/egt05_qtcat.R       -3       0  +100.00%
TOTAL                 -3       0  -0.00%

Results for commit: 18e64a932a384a95c9da4b3a50d97d7d39fe3368

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

github-actions · 2023-06-09T05:33:42Z

Unit Tests Summary

    1 files   49 suites 3m 16s ⏱️
216 tests 159 ✔️   57 💤 0 ❌
436 runs 303 ✔️ 133 💤 0 ❌

Results for commit ea7fcab.

♻️ This comment has been updated with latest results.

barnett11

I'm getting the below immediate error,
Error:
! adam_db$adeg$AVALCAT1 is not of type factor

clarkliming · 2023-06-12T08:55:00Z

I'm getting the below immediate error, Error: ! adam_db$adeg$AVALCAT1 is not of type factor

this means that AVALCAT1 has to be of type factor, so after converting it to factor it will work. The reason to only allow factor is that the order is very important and we can't specify order for each parameter (if there is split_rows_by(PARAMCD)). we must make sure the order is correct (at least within each subgroup of data) and prune the 0 rows)

barnett11 · 2023-06-12T08:58:14Z

I'm getting the below immediate error, Error: ! adam_db$adeg$AVALCAT1 is not of type factor

this means that AVALCAT1 has to be of type factor, so after converting it to factor it will work. The reason to only allow factor is that the order is very important and we can't specify order for each parameter (if there is split_rows_by(PARAMCD)). we must make sure the order is correct (at least within each subgroup of data) and prune the 0 rows)

Thanks @clarkliming , yes I understand this, but this should be within egt05_pre shouldn't it? Otherwise this will fail everytime for every user unless they update their data?

clarkliming · 2023-06-12T09:41:39Z

I'm getting the below immediate error, Error: ! adam_db$adeg$AVALCAT1 is not of type factor

this means that AVALCAT1 has to be of type factor, so after converting it to factor it will work. The reason to only allow factor is that the order is very important and we can't specify order for each parameter (if there is split_rows_by(PARAMCD)). we must make sure the order is correct (at least within each subgroup of data) and prune the 0 rows)

Thanks @clarkliming , yes I understand this, but this should be within egt05_pre shouldn't it? Otherwise this will fail everytime for every user unless they update their data?

this is really study specific: if we convert it to factor in pre, it is likely that the order is totally wrong. In my design, users should create script for this egt05, and they should update the pre after finding this error message. Once updated the script works. Is that ok?

barnett11 · 2023-06-12T09:48:06Z

Hi @clarkliming - this is the only template I've seen where we expect it to fail every time until the user does a step that is not automatic/instructed. Is this correct? Can we not set to a factor so the template runs, and then the user can determine the order after review? Of apply the order based on what we know already in standards (ie. '<=450 msec', '>450<=480 msec', '>480<=500 msec', '>500 msec')

clarkliming · 2023-06-12T12:01:35Z

Hi @clarkliming - this is the only template I've seen where we expect it to fail every time until the user does a step that is not automatic/instructed. Is this correct? Can we not set to a factor so the template runs, and then the user can determine the order after review? Of apply the order based on what we know already in standards (ie. '<=450 msec', '>450<=480 msec', '>480<=500 msec', '>500 msec')

retriction has been loosen so it should work by default

barnett11 · 2023-06-12T13:14:24Z

Thanks @clarkliming , I now get the below error which is due to CHGCAT1 not present for BASELINE

Error in run(egt05_qtcat, adam_db = db, arm_var = "TRT01A") : 
  1 assertions failed:
 * Variable 'adam_db$adeg$CHGCAT1': All elements must have at least 1 characters.```

clarkliming · 2023-06-12T13:56:35Z

Thanks @clarkliming , I now get the below error which is due to CHGCAT1 not present for BASELINE
Error in run(egt05_qtcat, adam_db = db, arm_var = "TRT01A") : 
  1 assertions failed:
 * Variable 'adam_db$adeg$CHGCAT1': All elements must have at least 1 characters.```

oh this reminds me why I add this restriction. AVALCAT1 and CHGCAT1 are needed to be valid values but rtables is not taking "" as valid values, and in SAS data it has to be "". We need to add a step of converting "" to NA in pre functions

clarkliming · 2023-06-12T14:57:07Z

please note that there are still issues in rtables so the page_by is not correct right now

barnett11 · 2023-06-12T16:25:58Z

Thanks @clarkliming . A couple of observations,

I was expecting prune_0 as F to show all categories, but this does not happen? It only works if the user has set AVALCAT1 to factor prior to template?
I do not think the options for visitvar are meant to be AVISIT or ATPTN - could we update documentation to be AVISIT or user-defined visit incorporating ATPT?

clarkliming · 2023-06-13T02:34:23Z

Thanks @clarkliming . A couple of observations,

I was expecting prune_0 as F to show all categories, but this does not happen? It only works if the user has set AVALCAT1 to factor prior to template?

it should return all levels; could you please provide your example and expected output?

I do not think the options for visitvar are meant to be AVISIT or ATPTN - could we update documentation to be AVISIT or user-defined visit incorporating ATPT?

will be fixed

barnett11 · 2023-06-13T12:54:03Z

Example using prune_0, I was thinking all levels for AVALCAT1 and CHGCAT1 would appear for every visit?

run(egt05_qtcat, adam_db = db, arm_var="TRT01A", prune_0=F)

    Analysis Visit                                  Placebo     RO12345678 10mg
    Category                                        (N=438)         (N=452)    
  —————————————————————————————————————————————————————————————————————————————
  QTcF - Fridericia's Correction Formula (msec)                                
    BASELINE                                                                   
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                438 (100%)      452 (100%)   
      Change from Baseline Category 1                                          
        n                                              0               0       
    Day 2                                                                      
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                430 (98.2%)     437 (96.7%)  
        >450<=480 msec                             8 (1.8%)        15 (3.3%)   
      Change from Baseline Category 1                                          
        n                                             438             452      
        <=30 msec                                 430 (98.2%)     437 (96.7%)  
        >60 msec                                   8 (1.8%)        15 (3.3%)   
    Day 3                                                                      
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                390 (89.0%)     409 (90.5%)  
        >450<=480 msec                            48 (11.0%)       43 (9.5%)   
      Change from Baseline Category 1                                          
        n                                             438             452      
        <=30 msec                                 390 (89.0%)     409 (90.5%)  
        >60 msec                                  48 (11.0%)       43 (9.5%)   
    Day 4                                                                      
      Analysis Value Category 1                                                
        n                                             426             441      
        <=450 msec                                416 (97.7%)     429 (97.3%)  
        >500 msec                                  10 (2.3%)       12 (2.7%)   
      Change from Baseline Category 1                                          
        n                                             426             441      
        <=30 msec                                 416 (97.7%)     429 (97.3%)  
        >60 msec                                   10 (2.3%)       12 (2.7%)   
    Follow Up Day 14                                                           
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                413 (94.3%)     432 (95.6%)  
        >450<=480 msec                             11 (2.5%)       12 (2.7%)   
        >500 msec                                  14 (3.2%)       8 (1.8%)

clarkliming · 2023-06-13T13:56:03Z

hi @barnett11 this is what I get

could you please reinstall latest and restart session and try again?

(and I think this table with prune_0=F is not correct, it may display other categories that is not for the parameter)

barnett11 · 2023-06-13T15:18:13Z

Indeed @clarkliming , it doesn't work very well for what the user may intend. I still cannot get every category displaying, the below is what I get currently,

> db <- data
> # Treatment group formatting
> db$adsl <- db$adsl %>% 
+   filter(SAFFL=="Y") %>%
+   mutate(TRT01A = factor(case_when(
+     TRT01A=="PLACEBO" ~ "Placebo",
+     TRT01A=="MPDL3280A" ~ "RO12345678 10mg"
+   )))
> db$adeg <- db$adeg %>% 
+   filter(SAFFL=="Y") %>% 
+   filter(PARAMCD=="QTCF") %>% 
+   mutate(TRT01A = factor(case_when(
+     TRT01A=="PLACEBO" ~ "Placebo",
+     TRT01A=="MPDL3280A" ~ "RO12345678 10mg"
+   ))) 
> run(egt05_qtcat, adam_db = db, arm_var="TRT01A", prune_0=F)
    Analysis Visit                                  Placebo     RO12345678 10mg
    Category                                        (N=438)         (N=452)    
  —————————————————————————————————————————————————————————————————————————————
  QTcF - Fridericia's Correction Formula (msec)                                
    BASELINE                                                                   
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                438 (100%)      452 (100%)   
      Change from Baseline Category 1                                          
        n                                              0               0       
    Day 2                                                                      
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                430 (98.2%)     437 (96.7%)  
        >450<=480 msec                             8 (1.8%)        15 (3.3%)   
      Change from Baseline Category 1                                          
        n                                             438             452      
        <=30 msec                                 430 (98.2%)     437 (96.7%)  
        >60 msec                                   8 (1.8%)        15 (3.3%)   
    Day 3                                                                      
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                390 (89.0%)     409 (90.5%)  
        >450<=480 msec                            48 (11.0%)       43 (9.5%)   
      Change from Baseline Category 1                                          
        n                                             438             452      
        <=30 msec                                 390 (89.0%)     409 (90.5%)  
        >60 msec                                  48 (11.0%)       43 (9.5%)   
    Day 4                                                                      
      Analysis Value Category 1                                                
        n                                             426             441      
        <=450 msec                                416 (97.7%)     429 (97.3%)  
        >500 msec                                  10 (2.3%)       12 (2.7%)   
      Change from Baseline Category 1                                          
        n                                             426             441      
        <=30 msec                                 416 (97.7%)     429 (97.3%)  
        >60 msec                                   10 (2.3%)       12 (2.7%)   
    Follow Up Day 14                                                           
      Analysis Value Category 1                                                
        n                                             438             452      
        <=450 msec                                413 (94.3%)     432 (95.6%)  
        >450<=480 msec                             11 (2.5%)       12 (2.7%)   
        >500 msec                                  14 (3.2%)       8 (1.8%)    
      Change from Baseline Category 1                                          
        n                                             438             452      
        <=30 msec                                 413 (94.3%)     432 (95.6%)  
        >60 msec                                   25 (5.7%)       20 (4.4%)

and then with applying factor myself it works better,

> db$adeg <- db$adeg %>% 
+   filter(SAFFL=="Y") %>% 
+   filter(PARAMCD=="QTCF") %>% 
+   mutate(TRT01A = factor(case_when(
+     TRT01A=="PLACEBO" ~ "Placebo",
+     TRT01A=="MPDL3280A" ~ "RO12345678 10mg"
+   ))) %>% 
+   mutate(AVALCAT1 = factor(AVALCAT1)) %>% 
+   mutate(CHGCAT1 = factor(CHGCAT1))
> run(egt05_qtcat, adam_db = db, arm_var="TRT01A", prune_0=F)
    Analysis Visit                                  Placebo     RO12345678 10mg
    Category                                        (N=438)         (N=452)    
  —————————————————————————————————————————————————————————————————————————————
  QTcF - Fridericia's Correction Formula (msec)                                
    BASELINE                                                                   
      AVALCAT1                                                                 
        n                                             438             452      
        <=450 msec                                438 (100%)      452 (100%)   
        >450<=480 msec                                 0               0       
        >500 msec                                      0               0       
      CHGCAT1                                                                  
        n                                              0               0       
        <=30 msec                                      0               0       
        >60 msec                                       0               0       
    Day 2                                                                      
      AVALCAT1                                                                 
        n                                             438             452      
        <=450 msec                                430 (98.2%)     437 (96.7%)  
        >450<=480 msec                             8 (1.8%)        15 (3.3%)   
        >500 msec                                      0               0       
      CHGCAT1                                                                  
        n                                             438             452      
        <=30 msec                                 430 (98.2%)     437 (96.7%)  
        >60 msec                                   8 (1.8%)        15 (3.3%)   
    Day 3                                                                      
      AVALCAT1                                                                 
        n                                             438             452      
        <=450 msec                                390 (89.0%)     409 (90.5%)  
        >450<=480 msec                            48 (11.0%)       43 (9.5%)   
        >500 msec                                      0               0       
      CHGCAT1                                                                  
        n                                             438             452      
        <=30 msec                                 390 (89.0%)     409 (90.5%)  
        >60 msec                                  48 (11.0%)       43 (9.5%)   
    Day 4                                                                      
      AVALCAT1                                                                 
        n                                             426             441      
        <=450 msec                                416 (97.7%)     429 (97.3%)  
        >450<=480 msec                                 0               0       
        >500 msec                                  10 (2.3%)       12 (2.7%)   
      CHGCAT1                                                                  
        n                                             426             441      
        <=30 msec                                 416 (97.7%)     429 (97.3%)  
        >60 msec                                   10 (2.3%)       12 (2.7%)

clarkliming · 2023-06-16T08:56:17Z

@barnett11 I get your point. Actually, I did not convert anything to factor. characters are allowed here. I totally understand your concern that the rows are not printed( and if you may run into issues if a level is only owned by a arm, which I think is not so good).

I wonder, shall we provide some documentation to say that, please use 'factors' if custom sorting is needed? and we still allow the variables to be in character?

barnett11 · 2023-06-16T09:30:42Z

@barnett11 I get your point. Actually, I did not convert anything to factor. characters are allowed here. I totally understand your concern that the rows are not printed( and if you may run into issues if a level is only owned by a arm, which I think is not so good).

I wonder, shall we provide some documentation to say that, please use 'factors' if custom sorting is needed? and we still allow the variables to be in character?

Yes, as long as the user knows how to achieve this then that's fine, documentation would suffice

clarkliming · 2023-07-11T06:48:06Z

@barnett11 documentation added; and let's don't wait for tern's bug (anyway we can, by default don't use page by)

github-actions · 2023-07-11T06:55:38Z

🧪 $Test coverage: 97.72%$

Code Coverage Summary

Filename                     Stmts    Miss  Cover    Missing
-------------------------  -------  ------  -------  -------------------------------------------------
R/ael01_nollt.R                 17       1  94.12%   61
R/aet01_aesi.R                 149       1  99.33%   211
R/aet01.R                       94       1  98.94%   158
R/aet02.R                       60       0  100.00%
R/aet03.R                       77       0  100.00%
R/aet04.R                       89       0  100.00%
R/aet05_all.R                   11       0  100.00%
R/aet05.R                       36       1  97.22%   101
R/aet10.R                       43       0  100.00%
R/assertions.R                  99       6  93.94%   88-93
R/cfbt01.R                     104       0  100.00%
R/checks.R                      14       0  100.00%
R/chevron_tlg-S4class.R         18       0  100.00%
R/chevron_tlg-S4methods.R      103       0  100.00%
R/cmt01a.R                      77       0  100.00%
R/coxt01.R                      48       1  97.92%   126
R/dmt01.R                       27       0  100.00%
R/dst01.R                       95       0  100.00%
R/dtht01.R                     103       6  94.17%   48, 52-56
R/egt02.R                       37       0  100.00%
R/egt03.R                       61       1  98.36%   127
R/egt05_qtcat.R                 77       0  100.00%
R/ext01.R                       61       1  98.36%   40
R/fstg01.R                      42       1  97.62%   95
R/kmg01.R                       28       1  96.43%   69
R/lbt04.R                       69       0  100.00%
R/lbt05.R                       67       5  92.54%   125-130
R/lbt06.R                       63       3  95.24%   131-134
R/lbt07.R                       94       0  100.00%
R/lbt14.R                       57       0  100.00%
R/mht01.R                       72       0  100.00%
R/mng01.R                       97       1  98.97%   110
R/pdt01.R                       61       0  100.00%
R/pdt02.R                       69       0  100.00%
R/rmpt01.R                      65      11  83.08%   91-100, 143
R/rspt01.R                      73       3  95.89%   156-159
R/rtables_utils.R              246      17  93.09%   41, 98, 210, 230, 416, 431-433, 435, 453-459, 469
R/standard_rules.R              11       0  100.00%
R/ttet01.R                     129       3  97.67%   229-232
R/utils.R                       65       0  100.00%
R/vst02.R                       47       1  97.87%   107
TOTAL                         2855      65  97.72%

Diff against main

Filename           Stmts    Miss  Cover
---------------  -------  ------  --------
R/egt05_qtcat.R      +13       0  +100.00%
TOTAL                +13       0  +0.01%

Results for commit: b85463c627d3140d308312a9d3b90431cc956fd6

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

BFalquet

Please see related PR: insightsengineering/dunlin#106
Nice to see this template being finalized

R/standard_rules.R

R/egt05_qtcat.R

Co-authored-by: b_falquet <64274616+BFalquet@users.noreply.github.com> Signed-off-by: Liming <36079400+clarkliming@users.noreply.github.com>

barnett11

Lovely, that's looking really good now thanks

remove filter of egt05

f98efa9

clarkliming requested a review from barnett11 June 9, 2023 05:23

match standard output

e41e4e5

clarkliming changed the title ~~remove filter of egt05~~ update egt05 Jun 9, 2023

clarkliming added the blocked label Jun 9, 2023

barnett11 requested changes Jun 12, 2023

View reviewed changes

remove restrictions on AVALCAT1 or CHGCAT1

78f0247

add empty_as_na function

f4f14a3

update docs

b4ab7d8

clarkliming added 2 commits July 11, 2023 05:52

Merge branch 'main' into 413_qtcat@main

16f4330

update row_split_var

eaac767

update snapshots; remove emty_as_na function

8568ed3

BFalquet approved these changes Jul 11, 2023

View reviewed changes

R/standard_rules.R Show resolved Hide resolved

R/egt05_qtcat.R Outdated Show resolved Hide resolved

R/egt05_qtcat.R Outdated Show resolved Hide resolved

clarkliming and others added 4 commits July 11, 2023 13:21

trigger action

f1771de

Update R/egt05_qtcat.R

9f8075d

Co-authored-by: b_falquet <64274616+BFalquet@users.noreply.github.com> Signed-off-by: Liming <36079400+clarkliming@users.noreply.github.com>

Merge branch 'main' into 413_qtcat@main

80c811c

update documnetations

391c33d

clarkliming requested a review from barnett11 July 12, 2023 07:27

update visit_var to visitvar

ea7fcab

barnett11 approved these changes Jul 14, 2023

View reviewed changes

clarkliming merged commit 24717f7 into main Jul 14, 2023
23 checks passed

clarkliming deleted the 413_qtcat@main branch July 14, 2023 09:06

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

update egt05 #535

update egt05 #535

clarkliming commented Jun 9, 2023 •

edited by BFalquet

Loading

github-actions bot commented Jun 9, 2023

github-actions bot commented Jun 9, 2023 •

edited

Loading

barnett11 left a comment

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 12, 2023

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 13, 2023

barnett11 commented Jun 13, 2023

clarkliming commented Jun 13, 2023

barnett11 commented Jun 13, 2023

clarkliming commented Jun 16, 2023

barnett11 commented Jun 16, 2023

clarkliming commented Jul 11, 2023

github-actions bot commented Jul 11, 2023 •

edited

Loading

BFalquet left a comment

barnett11 left a comment

update egt05 #535

update egt05 #535

Conversation

clarkliming commented Jun 9, 2023 • edited by BFalquet Loading

github-actions bot commented Jun 9, 2023

Code Coverage Summary

Diff against main

github-actions bot commented Jun 9, 2023 • edited Loading

Unit Tests Summary

barnett11 left a comment

Choose a reason for hiding this comment

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 12, 2023

clarkliming commented Jun 12, 2023

barnett11 commented Jun 12, 2023

clarkliming commented Jun 13, 2023

barnett11 commented Jun 13, 2023

clarkliming commented Jun 13, 2023

barnett11 commented Jun 13, 2023

clarkliming commented Jun 16, 2023

barnett11 commented Jun 16, 2023

clarkliming commented Jul 11, 2023

github-actions bot commented Jul 11, 2023 • edited Loading

Code Coverage Summary

Diff against main

BFalquet left a comment

Choose a reason for hiding this comment

barnett11 left a comment

Choose a reason for hiding this comment

clarkliming commented Jun 9, 2023 •

edited by BFalquet

Loading

github-actions bot commented Jun 9, 2023 •

edited

Loading

github-actions bot commented Jul 11, 2023 •

edited

Loading