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Creates Tables of Individual Observations from PKNCA Result

Source: R/NCA_Server.R
mk_table_ind_obs.Rd

Takes the output of PKNCA and creates a tabular view of the individual observation data. This can be spread out of over several tables (pages) if necessary.

Usage

mk_table_ind_obs(
  nca_res,
  obnd = NULL,
  not_sampled = "NS",
  blq = "BLQ",
  digits = 3,
  text_format = "text",
  max_height = 7,
  max_width = 6.5,
  max_row = NULL,
  max_col = 9,
  notes_detect = NULL,
  rows_by = "time"
)

Arguments

nca_res

Output of PKNCA.

obnd

onbrand reporting object.

not_sampled

Character string to use for missing data when pivoting.

blq

Character string to use to indicate data below the level of quantification (value of 0 in the dataset).

digits

Number of significant figures to report (set to NULL to disable rounding)

text_format

Either "md" for markdown or "text" (default) for plain text.

max_height

Maximum height of the final table in inches (A value of NULL will use 100 inches).

max_width

Maximum width of the final table in inches (A value of NULL will use 100 inches).

max_row

Maximum number of rows to have on a page. Spillover will hang over the side of the page..

max_col

Maximum number of columns to have on a page. Spillover will be wrapped to multiple pages.

notes_detect

Vector of strings to detect in output tables (example c("NC", "BLQ")).

rows_by

Can be either "time" or "id". If it is "time", there will be a column for time and separate column for each subject ID. If rows_by is set to "id" there will be a column for ID and a column for each individual time.

Value

List containing the following elements

  • isgood: Boolean indicating the exit status of the function.

  • one_table: Dataframe of the entire table with the first lines containing the header.

  • one_body: Dataframe of the entire table (data only).

  • one_header: Dataframe of the entire header (row and body, no data).

  • tables: Named list of tables. Each list element is of the output

  • msgs: Vector of text messages describing any errors that were found. format from build_span.

Examples

# We need a state variable to be define
sess_res = NCA_test_mksession()
#> → ASM: including file
#> → ASM:   source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → ASM:   dest:   file.path("config","report.docx")
#> → ASM: including file
#> → ASM:   source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → ASM:   dest:   file.path("config","report.pptx")
#> → ASM: including file
#> → ASM:   source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → ASM:   dest:   file.path("config","report.yaml")
#> → ASM: State initialized
#> → ASM: setting word placeholders: 
#> → ASM:   -> setting docx ph: HEADERLEFT = left header
#> → ASM:   -> setting docx ph: HEADERRIGHT = right header
#> → ASM:   -> setting docx ph: FOOTERLEFT = left footer
#> → ASM: module isgood: TRUE
#> → UD: including file
#> → UD:   source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → UD:   dest:   file.path("config","report.docx")
#> → UD: including file
#> → UD:   source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → UD:   dest:   file.path("config","report.pptx")
#> → UD: including file
#> → UD:   source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → UD:   dest:   file.path("config","report.yaml")
#> → UD: State initialized
#> → UD: module checksum updated:897d952fecbc804999396a96f9df4b20
#> → UD: module isgood: TRUE
#> → DW: including file
#> → DW:   source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → DW:   dest:   file.path("config","report.docx")
#> → DW: including file
#> → DW:   source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → DW:   dest:   file.path("config","report.pptx")
#> → DW: including file
#> → DW:   source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → DW:   dest:   file.path("config","report.yaml")
#> → DW: State initialized
#> → DW: module checksum updated:5b0f0b05ee3ac7336a74c564bb6efdad
#> → DW: loading data view idx: 1
#> → DW: setting name: Observations
#> → DW: module checksum updated:1ac3e0afcc601f848943f92b854b3830
#> → DW:   -> filter
#> → DW: module checksum updated:67aff6e926eba73b3ecb361d26624844
#> → DW:   -> filter
#> → DW: module checksum updated:0234f6d458ef7487a3b2e991b2d0957b
#> → DW:   -> mutate
#> → DW: module checksum updated:37d0958f042076b974fdd3f894157822
#> → DW: loading data view idx: 2
#> → DW: setting name: PK 3mg SD IV
#> → DW: module checksum updated:4e7ca05728d66df3adfcf87387f9543a
#> → DW:   -> filter
#> → DW: module checksum updated:2d95bc56262f46b7f135dd33fc4722b3
#> → DW:   -> filter
#> → DW: module checksum updated:b8a30837145926d2d9cc6f788c10b7ed
#> → DW:   -> filter
#> → DW: module checksum updated:24b554ee8736ebc84979c896ac2e93c3
#> → DW:   -> filter
#> → DW: module checksum updated:daad88263faf7cbf90871ed00a0dd275
#> → DW: loading data view idx: 3
#> → DW: setting name: PK 3mg SD IV (NCA)
#> → DW: module checksum updated:a7b3ea35cdba272682716aa4619d3983
#> → DW:   -> filter
#> → DW: module checksum updated:e8d2f77c0bd731995d845ee8be623e22
#> → DW:   -> filter
#> → DW: module checksum updated:24cc7b591ca756a0abf560fb5295e04d
#> → DW:   -> filter
#> → DW: module checksum updated:f79ef26bdb4dac420c24650b9e96f721
#> → DW: loading data view idx: 4
#> → DW: setting name: PKPD 3mg SD IV (NCA)
#> → DW: module checksum updated:c737e8b3a28ba600a83ddf58a969c90a
#> → DW:   -> filter
#> → DW: module checksum updated:4c0d054f8ec47ae97fd1c650d8ddad55
#> → DW:   -> filter
#> → DW: module checksum updated:1e3d65ec1bd6ee5850d67bd2250e3223
#> → DW:   -> filter
#> → DW: module checksum updated:1e3d65ec1bd6ee5850d67bd2250e3223
#> → DW: module isgood: TRUE
#> → NCA: including file
#> → NCA:   source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → NCA:   dest:   file.path("config","report.docx")
#> → NCA: including file
#> → NCA:   source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → NCA:   dest:   file.path("config","report.pptx")
#> → NCA: including file
#> → NCA:   source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → NCA:   dest:   file.path("config","report.yaml")
#> ! NCA: Parameter specified in YAML is not a valid PKNCA parameter: sparse_se
#> ! NCA: Parameter specified in YAML is not a valid PKNCA parameter: sparse_df
#> → NCA: including file
#> → NCA:   source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → NCA:   dest:   file.path("config","report.docx")
#> → NCA: including file
#> → NCA:   source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → NCA:   dest:   file.path("config","report.pptx")
#> → NCA: including file
#> → NCA:   source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → NCA:   dest:   file.path("config","report.yaml")
#> → NCA: State initialized
#> → NCA: State initialized
#> → NCA: loading element idx: 1
#> → NCA:   -> setting name: PK Example
#> → NCA:   -> notes found and set
#> → NCA:   -> setting data source: DW_myDS_3
#> → NCA: NCA_add_int: append
#> → NCA: added element idx: 1
#> → NCA: module isgood: TRUE

state = sess_res$state

# Pulls out the active analysis
current_ana = NCA_fetch_current_ana(state)

# This is the raw PKNCA output
pknca_res = NCA_fetch_ana_pknca(state, current_ana)

# Building the figure
mk_res = mk_table_ind_obs(nca_res = pknca_res)
mk_res$tables[["Table 1"]]$ft

Time
Concentration (ng/mL) by ID
(day)
1
2
3
4
5
6
7
0
BLQ
BLQ
BLQ
BLQ
BLQ
BLQ
BLQ
1
690
750
670
638
855
611
554
2
588
577
576
517
668
521
476
3
506
508
501
438
549
456
425
4
438
476
441
384
472
409
390
7
303
425
320
300
360
325
332
21
123
274
139
173
228
194
210
28
95.5
220
104
135
188
155
169
35
75.8
177
77.8
105
156
125
136
42
60.6
142
58.6
82.2
128
100
109