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3 changes: 0 additions & 3 deletions vignettes/binary-outcomes.Rmd
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Expand Up @@ -95,9 +95,6 @@ informs the comparator intercept, whereas STC regresses on the IPD alone.)


``` r
library(mlumr)
library(ggplot2)

# IPD + AgD bundled with mlumr (copied from multinma's plaque_psoriasis, GPL-3).
data("psoriasis_ipd")
data("psoriasis_agd")
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3 changes: 0 additions & 3 deletions vignettes/binary-outcomes.Rmd.orig
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Expand Up @@ -116,9 +116,6 @@ still differ: ML-UMR fits a joint likelihood in which the aggregate outcome
informs the comparator intercept, whereas STC regresses on the IPD alone.)

```{r data}
library(mlumr)
library(ggplot2)

# IPD + AgD bundled with mlumr (copied from multinma's plaque_psoriasis, GPL-3).
data("psoriasis_ipd")
data("psoriasis_agd")
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1 change: 0 additions & 1 deletion vignettes/choosing-a-method.Rmd
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Expand Up @@ -48,7 +48,6 @@ secukinumab) with three prognostic covariates:


``` r
library(mlumr)
data("psoriasis_ipd") # bundled with mlumr (from multinma, GPL-3)
data("psoriasis_agd")

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1 change: 0 additions & 1 deletion vignettes/choosing-a-method.Rmd.orig
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Expand Up @@ -69,7 +69,6 @@ the plaque-psoriasis PASI 75 endpoint (UNCOVER-2 ixekizumab vs FIXTURE
secukinumab) with three prognostic covariates:

```{r data}
library(mlumr)
data("psoriasis_ipd") # bundled with mlumr (from multinma, GPL-3)
data("psoriasis_agd")

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3 changes: 0 additions & 3 deletions vignettes/continuous-outcomes.Rmd
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Expand Up @@ -79,9 +79,6 @@ mlumr precisely because no aggregation bias arises from a nonlinear link


``` r
library(mlumr)
library(ggplot2)

data("shoulder_ipd") # index IPD (ASD), bundled with mlumr
data("shoulder_agd") # comparator AgD (ET)

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3 changes: 0 additions & 3 deletions vignettes/continuous-outcomes.Rmd.orig
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Expand Up @@ -100,9 +100,6 @@ mlumr precisely because no aggregation bias arises from a nonlinear link
(contrast the log odds ratio in `vignette("binary-outcomes")`).

```{r data}
library(mlumr)
library(ggplot2)

data("shoulder_ipd") # index IPD (ASD), bundled with mlumr
data("shoulder_agd") # comparator AgD (ET)

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3 changes: 0 additions & 3 deletions vignettes/count-outcomes.Rmd
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Expand Up @@ -77,9 +77,6 @@ $\mathrm{RR}=\bar\lambda_{\text{index}}/\bar\lambda_{\text{comparator}}$


``` r
library(mlumr)
library(ggplot2)

data("caries_ipd") # index IPD (SDF), bundled with mlumr
data("caries_agd") # comparator AgD (NSF)

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3 changes: 0 additions & 3 deletions vignettes/count-outcomes.Rmd.orig
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Expand Up @@ -98,9 +98,6 @@ $\mathrm{RR}=\bar\lambda_{\text{index}}/\bar\lambda_{\text{comparator}}$
(null = 1), reported in both populations.

```{r data}
library(mlumr)
library(ggplot2)

data("caries_ipd") # index IPD (SDF), bundled with mlumr
data("caries_agd") # comparator AgD (NSF)

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1 change: 0 additions & 1 deletion vignettes/fitting-and-diagnostics.Rmd
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Expand Up @@ -37,7 +37,6 @@ in `vignette("binary-outcomes")`):


``` r
library(mlumr)
data("psoriasis_ipd") # bundled with mlumr (from multinma, GPL-3)
data("psoriasis_agd")

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1 change: 0 additions & 1 deletion vignettes/fitting-and-diagnostics.Rmd.orig
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Expand Up @@ -58,7 +58,6 @@ of this vignette inspects, tunes, and diagnoses (the data preparation is covered
in `vignette("binary-outcomes")`):

```{r data}
library(mlumr)
data("psoriasis_ipd") # bundled with mlumr (from multinma, GPL-3)
data("psoriasis_agd")

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3 changes: 0 additions & 3 deletions vignettes/survival-outcomes.Rmd
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Expand Up @@ -131,9 +131,6 @@ We adjust for age, ISS stage III, complete/very-good-partial response, and sex.


``` r
library(mlumr)
library(ggplot2)

data("ndmm_ipd") # bundled with mlumr (copied from multinma, GPL-3)
data("ndmm_agd") # reconstructed pseudo-IPD (KM)
data("ndmm_agd_covs") # covariate moments for the AgD arm
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3 changes: 0 additions & 3 deletions vignettes/survival-outcomes.Rmd.orig
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Expand Up @@ -151,9 +151,6 @@ Surv(lower, upper, type = "interval2") # interval censoring
We adjust for age, ISS stage III, complete/very-good-partial response, and sex.

```{r data}
library(mlumr)
library(ggplot2)

data("ndmm_ipd") # bundled with mlumr (copied from multinma, GPL-3)
data("ndmm_agd") # reconstructed pseudo-IPD (KM)
data("ndmm_agd_covs") # covariate moments for the AgD arm
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