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Individual contributions to dOFV

Source: R/xset_shark.R
shark_plot.Rd

This is intended to match the overall behavior of dOFV.vs.id() in xpose4, within the framework of the xpose_set object.

dofv_vs_id is an alias of the function shark_plot, for recognition.

Usage

shark_plot(
  xpdb_s,
  ...,
  .inorder = FALSE,
  type = "plt",
  alpha = 0.05,
  df = "guess",
  text_cutoff = 0.8,
  title = "Individual contributions to dOFV | @run",
  subtitle = "Based on @nind individuals, OFVs: @ofv",
  caption = "@dir",
  tag = NULL,
  ylab = "dOFV",
  xlab = "Number of individuals removed",
  opt,
  facets = NULL,
  .problem,
  .subprob,
  .method,
  quiet
)

dofv_vs_id(
  xpdb_s,
  ...,
  .inorder = FALSE,
  type = "plt",
  alpha = 0.05,
  df = "guess",
  text_cutoff = 0.8,
  title = "Individual contributions to dOFV | @run",
  subtitle = "Based on @nind individuals, OFVs: @ofv",
  caption = "@dir",
  tag = NULL,
  ylab = "dOFV",
  xlab = "Number of individuals removed",
  opt,
  facets = NULL,
  .problem,
  .subprob,
  .method,
  quiet
)

Arguments

xpdb_s

<xpose_set> object

...

See <two_set_dots>

.inorder

See <two_set_dots>

type

See Details.

alpha

alpha for LRT

df

degrees of freedom for LRT. If "guess" (default), then use the difference in the number of unfixed parameters.

text_cutoff

If less than 1, the percentile of absolute individual dOFV values above which to show labels of IDs. If above 1, the absolute number of IDs to show. To show all, use an extreme positive number like 9999.

title

Plot title

subtitle

Plot subtitle

caption

Plot caption

tag

Plot tag

ylab

y-axis label

xlab

x-axis label

opt

User-specified data options. Only some of these will be used.

facets

<character> vector selecting facets, or NULL (default).

.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:

  • p points (using aesthetics for sharkup and sharkdn)

  • l lines for dOFV (both total dOFV and significance are plotted)

  • t text (using aesthetics for shkuptxt and shkdntxt)

In xpose4, users can control sig.drop, but this function uses alpha and df to determine the critical delta by the likelihood ratio test. It is acknowledged there are situations where this may not be valid, but it is suggested that df or alpha be adjusted to meet the desired sig.drop.

my_alpha <- 0.05
my_df <- 1.34 # fractional, perhaps to account for different IIVs

my_sigdrop <- -stats::qchisq(1-my_alpha, my_df)
my_sigdrop
#> [1] -4.633671
# Then use alpha=my_alpha, df=my_df in `shark_plot` call.

See also

shark_colors()

Examples

# \donttest{

pheno_set %>%
  # Make sure set has iofv var types defined
  focus_xpdb(everything()) %>%
  focus_function(backfill_iofv) %>%
  # Pick two models or consistent with two_set_dots()
  shark_plot(run6,run11)
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID
#> Returning parameter estimates from $prob no.1, subprob no.1, method foce
#> Returning parameter estimates from $prob no.1, subprob no.1, method foce


pheno_set %>%
  # As before
  focus_xpdb(everything()) %>%
  focus_function(backfill_iofv) %>%
  # Add indicator (or use established covariate)
  mutate(APGRtest = as.numeric(as.character(APGR))<5) %>%
  # Pick two models or consistent with two_set_dots()
  shark_plot(run6,run11, facets = "APGRtest")
#> Using data from $prob no.1
#> Removing duplicated rows based on: ID, APGRtest
#> Returning parameter estimates from $prob no.1, subprob no.1, method foce
#> Returning parameter estimates from $prob no.1, subprob no.1, method foce


# }