study_hours: Study hours and quiz scores under two study strategies
In latents: Multilevel Latent Profile, Class and Transition Models

study_hours

R Documentation

Study hours and quiz scores under two study strategies

Description

A simulated dataset for mixture_regression(), built so that every nesting of the mixture regression has a model that generated some of its columns, and the truth is kept for checking recovery.

Usage

study_hours

Format

A data frame with 900 rows (150 students by 6 weeks) and 10 columns:

student: Integer student identifier, 1 to 150.
week: Integer study week, 1 to 6.
hours: Hours studied that week, 0 to 12.
sleep: Hours slept the night before the quiz.
motivation: Standardized motivation, constant within student.
score: Quiz score.
passed: Integer 0/1: passed the weekly check.
questions: Count of questions the student asked that week.
strategy: Factor, "deep" or "surface": the week's generating strategy. Not for fitting; kept to check recovery.
student_type: Factor, "steady" or "erratic": the student's generating kind. Not for fitting; kept to check recovery.

Details

150 students each report six study weeks. In every week a student studies with one of two strategies, and the strategy decides how hours become a quiz score: a deep week gains about 4.5 points per hour from a base of 35, a surface week under one point per hour from a base of 55. Students are of two kinds that differ in their mix of strategies – steady students study deeply in about 85% of weeks, erratic ones in about 25% – and higher motivation makes a student more likely to be steady. More sleep makes a deep week more likely.

So score ~ hours is a two-class mixture at the level of the week (class_level = "observation"), whose class shares differ by student (the two-level model, id = "student", n_group_classes = 2). passed depends on the student's kind, not the week's strategy, so it is a mixture at the level of the student (class_level = "group"). questions is a count whose Poisson regression depends on the week's strategy.

Source

Simulated by data-raw/study-hours.R in the source repository.

Examples

fit <- mixture_regression(score ~ hours, data = study_hours, n_classes = 2,
                          n_starts = 3, seed = 1)
get_results(fit, "coefficients")

latents documentation built on Oct. 16, 2026, 5:09 p.m.