Create Gazepoint trial-level regressors for modeling — create_gazepoint_trial

Prepares a long-format trial table by joining stimulus/event design information with event-window summaries from numeric Gazepoint channels. The output is intended for downstream GLM, LMM, or mixed-model workflows.

Usage

create_gazepoint_trial_regressors(
  data,
  design,
  pre = 0,
  post = 5,
  time_col = NULL,
  event_time_col = NULL,
  event_id_col = NULL,
  signal_cols = NULL,
  subject_col = NULL,
  design_subject_col = NULL,
  carry_design_cols = NULL
)

Arguments

data: Data frame containing time-series signals, or a list of data frames.
design: Numeric event timestamps, a design data frame, or a list with an events data frame.
pre: Seconds before event onset to summarize.
post: Seconds after event onset to summarize.
time_col: Time column in data.
event_time_col: Event-time column in design.
event_id_col: Trial/event identifier column in design.
signal_cols: Numeric signal columns to summarize. If NULL, all numeric columns except the time column are used.
subject_col: Optional subject/participant column in data.
design_subject_col: Optional subject/participant column in design.
carry_design_cols: Design columns to carry into the output. If NULL, all non-time design columns are carried.

Value

A data frame with one row per trial/event and signal summary regressors.

Examples

dat <- data.frame(time_s = seq(0, 10, by = 1), GSR = seq(0, 1, length.out = 11))
design <- data.frame(trial = "T1", onset = 5, condition = "A")
create_gazepoint_trial_regressors(dat, design, pre = 1, post = 2)
#>   trial onset condition trial_id event_time pre post n_samples GSR_mean
#> 1    T1     5         A       T1          5   1    2         4     0.55
#>      GSR_sd GSR_min GSR_max GSR_range GSR_missing_prop
#> 1 0.1290994     0.4     0.7       0.3                0