grmtree_long_data: Synthetic Longitudinal MOS-SS Social Support Survey Data

In grmtree: Recursive Partitioning for Graded Response Models

Synthetic Longitudinal MOS-SS Social Support Survey Data

Description

A synthetic dataset containing responses to the eight MOS-SS emotional domain items measured at two time points (baseline and one-year follow-up), together with baseline demographic and clinical covariates. The data are provided for testing and demonstration of the longitudinal GRMTree functions (longitudinal_grmtree, rs_characterize) within the grmtree package.

Usage

grmtree_long_data

Format

A tibble with 1,500 rows and 23 variables:

MOS_Listen

Baseline: someone you can count on to listen when you need to talk (1–5)

MOS_Info

Baseline: someone to give you information to help you understand a situation (1–5)

MOS_Advice_Crisis

Baseline: someone to give good advice in a crisis (1–5)

MOS_Confide

Baseline: someone to confide in or talk to about yourself or your problems (1–5)

MOS_Advice_Want

Baseline: someone whose advice you really want (1–5)

MOS_Fears

Baseline: someone to share your private worries or fears (1–5)

MOS_Personal

Baseline: someone to turn to for suggestions about a personal problem (1–5)

MOS_Understand

Baseline: someone who understands your problems (1–5)

MOS_Listen_year1

One-year follow-up: listen item (1–5)

MOS_Info_year1

One-year follow-up: information item (1–5)

MOS_Advice_Crisis_year1

One-year follow-up: crisis advice item (1–5)

MOS_Confide_year1

One-year follow-up: confide item (1–5)

MOS_Advice_Want_year1

One-year follow-up: advice wanted item (1–5)

MOS_Fears_year1

One-year follow-up: fears item (1–5)

MOS_Personal_year1

One-year follow-up: personal suggestions item (1–5)

MOS_Understand_year1

One-year follow-up: understand item (1–5)

sex

Sex (Male, Female)

age

Age in years (numeric)

residency

Residence location (Urban, Rural)

job

Employment status (Employed, Unemployed)

education

Education level (Primary/High school, College/University)

ever_smoker

Ever-smoker status (Yes, No)

comorbidity_count

Number of chronic conditions (0–5)

bmi

Body mass index (numeric)

Details

The data were simulated from a two-factor longitudinal graded response model. Response shift was intentionally built into the older subgroup (age > 61): the MOS_Info item exhibits reprioritization (a discrimination change over time) and the MOS_Fears item exhibits recalibration (a threshold change over time). Younger patients show no response shift. As a result, longitudinal_grmtree produces an age split, and rs_characterize detects response shift within the older subgroup. Items are coded 1–5, representing None of the time, A little of the time, Some of the time, Most of the time, and All of the time, respectively.

Source

Synthetic data generated from a two-factor longitudinal graded response model for package testing and demonstration. Contains no real patient data.

Examples

library(grmtree)
library(dplyr)

  # Load the synthetic longitudinal data and take a glimpse
  data("grmtree_long_data", package = "grmtree")
  glimpse(grmtree_long_data)

grmtree documentation built on Sept. 2, 2026, 1:07 a.m.