Fit element-wise generalized additive models no model-level p-value for GAMs, so there is no correct.p.value.model argument.

Fit element-wise generalized additive models no model-level p-value for GAMs, so there is no correct.p.value.model argument.

Usage

ModelArray.gam(
  formula,
  data,
  phenotypes,
  scalar,
  element.subset = NULL,
  full.outputs = FALSE,
  var.smoothTerms = c("statistic", "p.value"),
  var.parametricTerms = c("estimate", "statistic", "p.value"),
  var.model = c("dev.expl"),
  changed.rsq.term.index = NULL,
  correct.p.value.smoothTerms = c("fdr"),
  correct.p.value.parametricTerms = c("fdr"),
  num.subj.lthr.abs = 10,
  num.subj.lthr.rel = 0.2,
  verbose = TRUE,
  pbar = TRUE,
  n_cores = 1,
  on_error = "stop",
  write_results_name = NULL,
  write_results_file = NULL,
  write_results_flush_every = 1000L,
  write_results_storage_mode = "double",
  write_results_compression_level = 4L,
  return_output = TRUE,
  ...
)

Arguments

formula: Formula (passed to gam).
data: A ModelArray object.
phenotypes: A data.frame of the cohort with columns of independent variables and covariates to be added to the model. It must contain a column called "source_file" whose entries match those in sources(data)[[scalar]].
scalar: Character. The name of the element-wise scalar to analyse. Must be one of names(scalars(data)).
element.subset: Integer vector of element indices (1-based) to run. Default is NULL, i.e. all elements in data.
full.outputs: Logical. If TRUE, return the full set of statistics (ignoring var.* arguments). If FALSE (default), only return those requested in var.* and correct.p.value.*.
var.smoothTerms: Character vector. Statistics to save for smooth terms, from broom::tidy(parametric = FALSE). See Details.
var.parametricTerms: Character vector. Statistics to save for parametric terms, from broom::tidy(parametric = TRUE). See Details.
var.model: Character vector. Statistics to save for the overall model, from broom::glance() and summary(). See Details.
changed.rsq.term.index: A list of positive integers. Each value is the index of a term on the right-hand side of formula for which delta adjusted R-squared and partial R-squared should be computed. Usually the term of interest is a smooth term or interaction term. Default NULL (not computed). See Details for warnings.
correct.p.value.smoothTerms: Character vector. P-value correction method(s) for each smooth term. Default: "fdr".
correct.p.value.parametricTerms: Character vector. P-value correction method(s) for each parametric term. Default: "fdr".
num.subj.lthr.abs: Integer. Lower threshold for the absolute number of subjects with finite scalar values (not NaN, NA, or Inf) required per element. Elements below this threshold are skipped (outputs set to NaN). Default is 10.
num.subj.lthr.rel: Numeric between 0 and 1. Lower threshold for the proportion of subjects with finite values. Used together with num.subj.lthr.abs (the effective threshold is the maximum of the two). Default is 0.2.
verbose: Logical. Print progress messages. Default TRUE.
pbar: Logical. Show progress bar. Default TRUE.
n_cores: Positive integer. Number of CPU cores for parallel processing via mclapply. Default is 1 (serial).
on_error: Character: one of "stop", "skip", or "debug". When an error occurs fitting one element: "stop" halts execution; "skip" returns all-NaN for that element; "debug" drops into browser (if interactive) then skips. Default: "stop".
write_results_name: Optional character. If provided, results are incrementally written to results/<write_results_name>/results_matrix in the HDF5 file specified by write_results_file.
write_results_file: Optional character. HDF5 file path for incremental result writes. Required when write_results_name is provided.
write_results_flush_every: Positive integer. Number of elements per write block. Default 1000.
write_results_storage_mode: Character. Storage mode for HDF5 writes (e.g. "double"). Default "double".
write_results_compression_level: Integer 0–9. Gzip compression level for HDF5 writes. Default 4.
return_output: Logical. If TRUE (default), return the combined data.frame. If FALSE, return invisible(NULL); useful when writing large outputs directly to HDF5.
...: Additional arguments passed to gam.

Value

A tibble with one row per element. The first column is element_id (0-based). Remaining columns contain the requested statistics, named as <term>.<statistic>. If changed.rsq.term.index was requested, additional columns <term>.delta.adj.rsq and <term>.partial.rsq are appended.

Examples

{
if (FALSE) { # \dontrun{
ma <- ModelArray("path/to/data.h5", scalar_types = c("FD"))
phenotypes <- read.csv("cohort.csv")

results <- ModelArray.gam(
  FD ~ s(age, fx = TRUE) + sex,
  data = ma,
  phenotypes = phenotypes,
  scalar = "FD"
)
head(results)

# With changed R-squared for the smooth term (term index 1)
results_rsq <- ModelArray.gam(
  FD ~ s(age, fx = TRUE) + sex,
  data = ma,
  phenotypes = phenotypes,
  scalar = "FD",
  changed.rsq.term.index = list(1)
)
} # }
}

Fit element-wise generalized additive models no model-level p-value for GAMs, so there is no `correct.p.value.model` argument.

Usage

Arguments

Value

See also

Examples