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GOSe-6mo-imputation
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Kevin Kunzmann
GOSe-6mo-imputation
Commits
3c1955ba
Commit
3c1955ba
authored
Sep 08, 2020
by
Kristien Wouters
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generalisation for 3/6/12 month imputation
parent
69324e04
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Run-3-6-12m-imputation-report.R
Run-3-6-12m-imputation-report.R
+14
-0
imputation-report.Rmd
imputation-report.Rmd
+31
-30
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Run-3-6-12m-imputation-report.R
0 → 100644
View file @
3c1955ba
rmarkdown
::
render
(
input
=
'imputation-report.Rmd'
,
params
=
list
(
imputation_time
=
90
,
per_protocol_window
=
c
(
77
,
126
)),
output_file
=
'Imputation_GOSE_3month.html'
)
rmarkdown
::
render
(
input
=
'imputation-report.Rmd'
,
params
=
list
(
imputation_time
=
180.0
,
per_protocol_window
=
c
(
150
,
240
)),
output_file
=
'Imputation_GOSE_6month.html'
)
rmarkdown
::
render
(
input
=
'imputation-report.Rmd'
,
params
=
list
(
imputation_time
=
360.0
,
per_protocol_window
=
c
(
300
,
420
)),
output_file
=
'Imputation_GOSE_12month.html'
)
imputation-report.Rmd
View file @
3c1955ba
---
title: "
Impute 6-months GOSe for CENTER-TBI
"
title: "
`r sprintf('Impute %i month GOSe for CENTER-TBI',params$imputation_time/30)`
"
date: "`r Sys.time()`"
author: "Kevin Kunzmann (kevin.kunzmann@mrc-bsu.cam.ac.uk)"
author:
- Kevin Kunzmann (kevin.kunzmann@mrc-bsu.cam.ac.uk)
- Kristien Wouters (kristien.wouters@uza.be)
output:
html_document:
...
...
@@ -12,6 +14,7 @@ output:
params:
seed: 42
age_range: !r c(0, Inf)
imputation_time: 180.0
per_protocol_window: !r c(150.0, 240)
---
...
...
@@ -84,9 +87,9 @@ tbl_combined <- readr::read_csv("tbl_gose.csv", col_types = "cinncD") %>%
!is.na(Outcomes.DerivedCompositeGOSE),
# throw out all observations without a precise timestamp
!is.na(Outcomes.DerivedCompositeGOSEDaysPostInjury),
# throw out all observations after 18 months
# (for 12 months imputation
!
)
Outcomes.DerivedCompositeGOSEDaysPostInjury <
18*30
# throw out all observations after 18 months
for 3 and 6 months imputation
# (for 12 months imputation
: throw out observations > 24 months
)
Outcomes.DerivedCompositeGOSEDaysPostInjury <
ifelse(params$imputation_time < 360,18*30,24*30)
) %>%
mutate(
Subject.PatientType = case_when(
...
...
@@ -136,7 +139,7 @@ tbl_combined <- tbl_combined %>%
group_by(gupi) %>%
filter(
# all GOSEs before 180 days post injury must be > 1 (dead)
all(Outcomes.DerivedCompositeGOSE[Outcomes.DerivedCompositeGOSEDaysPostInjury <=
180
] > 1),
all(Outcomes.DerivedCompositeGOSE[Outcomes.DerivedCompositeGOSEDaysPostInjury <=
params$imputation_time
] > 1),
# ensure age-bracket
Subject.Age >= params$age_range[1],
Subject.Age <= params$age_range[2],
...
...
@@ -164,11 +167,11 @@ tbl_gose_msm <- tbl_combined %>%
gose = Outcomes.DerivedCompositeGOSE
) %>%
rbind(
# add censored states at
18
0.1 days to make prediction for
# add censored states at
imputation time +
0.1 days to make prediction for
tibble(
gupi = unique(.$gupi),
# needed to offset to get a prediction in all cases
days_post_injury =
180
+ .1,
days_post_injury =
params$imputation_time
+ .1,
gose = 99
)
) %>%
...
...
@@ -208,7 +211,7 @@ fit <- msm::msm(
gen.inits = TRUE,
qmatrix = Q,
censor = 99,
pci = c(
90
, 270),
pci = c(
ifelse(params$imputation_time==90,80,90)
, 270),
censor.states = 2:7, # cannot be dead since these were filtered previously
control = list(
fnscale = 12000,
...
...
@@ -235,7 +238,7 @@ tbl_posteriors <- tibble(
`2_or_3` = `3`
) %>%
filter(
t ==
18
0.1
t ==
params$imputation_time +
0.1
) %>%
select(
gupi, `1`, `2_or_3`, `4`, `5`, `6`, `7`, `8`
...
...
@@ -252,7 +255,7 @@ tbl_posteriors <- tibble(
```
```{r final-imputations}
# start by adding confirmed
<= 180d deaths
back in
# start by adding confirmed
deaths (<= imputation time)
back in
tbl_final_imputations <- readr::read_csv(
"tbl_gose.csv",
col_types = "cinncD"
...
...
@@ -272,7 +275,7 @@ tbl_final_imputations <- readr::read_csv(
) %>%
mutate(
probability = ifelse(
is.na(death_days) | (death_days >
180
),
is.na(death_days) | (death_days >
params$imputation_time
),
probability,
ifelse(gose != "gose_1_probability", 0.0, 1.0)
)
...
...
@@ -312,8 +315,8 @@ tbl_final_imputations <- readr::read_csv(
) %>%
group_by(gupi) %>%
summarize(
gose = gose[which.min(abs(days -
180
))],
days = days[which.min(abs(days -
180
))],
gose = gose[which.min(abs(days -
params$imputation_time
))],
days = days[which.min(abs(days -
params$imputation_time
))],
.groups = "drop"
) %>%
transmute(
...
...
@@ -346,7 +349,6 @@ tbl_final_imputations <- readr::read_csv(
)
```
```{r plausi-check}
tbl_final_imputations %>%
select(
...
...
@@ -374,25 +376,24 @@ tbl_final_imputations %>%
coord_fixed(expand = FALSE) +
scale_fill_continuous(low = "#FFFFFF", high = "#555555") +
theme_bw() +
ggtitle(
"Confusion matrix: imputed vs. per-protocol"
)
ggtitle(
sprintf("Confusion matrix: imputed vs. per-protocol: %i days",params$imputation_time)
)
```
```{r save-imputed-values}
tbl_final_imputations %>% {
tmp <- .
names(tmp) <- gsub("gose", "Subject.DerivedImputed180DaysGOSE"
, x = names(.))
names(tmp) <- gsub("gose", sprintf("Subject.DerivedImputed%iDaysGOSE",params$imputation_time)
, x = names(.))
tmp } %>%
rename(
"Subject.GOSE6monthEndpointDerived" = "Subject.DerivedImputed180DaysGOSE_map_per_protocol_combined"
!! sprintf("Subject.GOSE%imonthEndpointDerived",round(params$imputation_time/30)) := sprintf("Subject.DerivedImputed%iDaysGOSE_map_per_protocol_combined",params$imputation_time)
) %>%
write_csv("tbl_gose_imputed.csv"
)
write_csv(sprintf("tbl_gose_imputed%i.csv",params$imputation_time)
)
```
<!-- # Session Info# -->
# Session Info
```{r session-info}
sessionInfo() %>%
knitr::kable()
```
<!-- ```{r session-info} -->
<!-- sessionInfo() %>% -->
<!-- knitr::kable() -->
<!-- ``` -->
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