% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/analyze.R
\name{split_survey_data}
\alias{split_survey_data}
\title{Split Survey Data into Quantitative and Qualitative Components}
\usage{
split_survey_data(survey, emp_id_col = NULL)
}
\arguments{
\item{survey}{A glint_survey object or data frame containing survey data}

\item{emp_id_col}{Character string specifying the employee ID column name}
}
\value{
A named list with two elements:
\describe{
\item{quantitative}{A tibble with all standard respondent columns plus
one numeric response column per question. Comment, topic, and sensitive
flag columns are excluded.}
\item{qualitative}{A tibble with the employee ID column plus the comment,
topic, and sensitive flag columns for every question. Numeric response
columns are excluded.}
}
}
\description{
Separates a survey dataset into two data frames: one containing only numeric
response data (for statistical analysis) and one containing only comment
and topic data (for qualitative analysis). Both outputs retain the employee
ID column so they can be rejoined at any time.
}
\examples{
survey_path <- system.file("extdata", "survey_export.csv", package = "vivaglint")
survey <- read_glint_survey(survey_path, emp_id_col = "EMP ID")
parts  <- split_survey_data(survey)

# Analyze numeric responses
summary <- summarize_survey(parts$quantitative, scale_points = 5,
                            emp_id_col = "EMP ID")

# Work with comments separately
comments <- parts$qualitative
}
