Skip to contents

Specific waterfall plots

Source: R/xset_plots.R
waterfalls.Rd

Differences are second listed model minus first listed. Eg, in eta_waterfall(run1,run2), the when etas in run2 are greater than those in run1, the difference will be positive.

Usage

prm_waterfall(
  xpdb_s,
  ...,
  .inorder = FALSE,
  type = "bh",
  max_nind = 0.7,
  scale_diff = TRUE,
  show_n = TRUE,
  title = "Parameter changes between models | @run",
  subtitle = "Based on @nobs observations in @nind individuals",
  caption = "@dir",
  tag = NULL,
  facets = NULL,
  facet_scales = "free_x",
  .problem,
  .subprob,
  .method,
  quiet
)

eta_waterfall(
  xpdb_s,
  ...,
  .inorder = FALSE,
  type = "bh",
  max_nind = 0.7,
  scale_diff = TRUE,
  show_n = TRUE,
  title = "Eta changes between models | @run",
  subtitle = "Based on @nobs observations in @nind individuals",
  caption = "@dir",
  tag = NULL,
  facets = NULL,
  facet_scales = "free_x",
  .problem,
  .subprob,
  .method,
  quiet
)

iofv_waterfall(
  xpdb_s,
  ...,
  .inorder = FALSE,
  type = "bh",
  max_nind = 0.7,
  scale_diff = FALSE,
  show_n = TRUE,
  title = "iOFV changes between models | @run",
  subtitle = "Based on @nobs observations in @nind individuals",
  caption = "@dir",
  tag = NULL,
  facets = NULL,
  facet_scales = "free_x",
  .problem,
  .subprob,
  .method,
  quiet
)

Arguments

xpdb_s

<xpose_set> object

...

See <two_set_dots>

.inorder

See <two_set_dots>

type

See Details.

max_nind

If less than 1, the percentile of absolute change values above which to plot. If above 1, the absolute number of subjects is included. To show all, use an extreme positive number like 9999.

scale_diff

<logical> Scale change to the standard deviation of the model 1 column values. Respects faceting.

show_n

<logical> For faceting variables, show N per facet. Not implemented

title

Plot title

subtitle

Plot subtitle

caption

Plot caption

tag

Plot tag

facets

<character> Faceting variables

facet_scales

<character> Forwarded to facet_*(scales = facet_scales)

.problem

The problem to be used, by default returns the last one.

.subprob

The subproblem to be used, by default returns the last one.

.method

The estimation method to be used, by default returns the last one.

quiet

Silence extra debugging output

Value

<xpose_plot> object

Details

For type-based customization of plots:

  • b bar plot (from geom_bar)

  • h hline at 0 (from geom_hline)

  • t text of change value (from geom_text)

Examples


# Parameter value changes
pheno_set %>%
  # Ensure param is set
  focus_qapply(set_var_types, param=c(CL,V)) %>%
  prm_waterfall(run5,run6)
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Tidying data by ID, TIME, AMT, WT, APGR ... and 16 more variables



# EBE value changes
pheno_set %>%
  eta_waterfall(run5,run6)
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Tidying data by ID, TIME, AMT, WT, APGR ... and 16 more variables


# iOFV changes
pheno_set %>%
  focus_qapply(backfill_iofv) %>%
  # Note the default scaling is flipped here
  iofv_waterfall(run5,run6)
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Tidying data by ID, TIME, AMT, WT, APGR ... and 17 more variables