Creates a group dataset from tabular data containing pre-extracted statistics such as ROI means, effect sizes, and standard errors. This format is useful for ROI-based analyses or when working with summary statistics.
Usage
group_data_from_csv(
data,
effect_cols,
subject_col = "subject",
roi_col = NULL,
contrast_col = NULL,
covariate_cols = NULL,
wide_format = FALSE
)Arguments
- data
Either a path to a CSV file or a data frame containing the data
- effect_cols
Named vector or list specifying column names for effect statistics. E.g., c(beta = "mean_activation", se = "std_error") or c(t = "t_stat", df = "df")
- subject_col
Character string specifying the column containing subject IDs
- roi_col
Character string specifying the column containing ROI names (optional)
- contrast_col
Character string specifying the column containing contrast names (optional)
- covariate_cols
Character vector of column names to use as covariates (optional)
- wide_format
Logical. If TRUE, expects wide format with ROIs as columns (default: FALSE)
Examples
if (FALSE) { # \dontrun{
# Long format: one row per subject-ROI combination
gd <- group_data_from_csv(
"roi_statistics.csv",
effect_cols = c(beta = "mean_beta", se = "se_beta"),
subject_col = "participant_id",
roi_col = "roi_name",
covariate_cols = c("age", "sex", "group")
)
# Wide format: one row per subject, ROIs as columns
gd <- group_data_from_csv(
"subject_summary.csv",
effect_cols = c(beta = "roi_"), # Prefix for ROI columns
subject_col = "subject",
wide_format = TRUE
)
# From data frame with multiple contrasts
df <- read.csv("contrast_results.csv")
gd <- group_data_from_csv(
df,
effect_cols = c(beta = "estimate", se = "std_error", t = "t_value"),
subject_col = "subject_id",
contrast_col = "contrast_name",
roi_col = "region"
)
} # }