MHserviceDemo: Artificial mental-health service outcomes dataset

MHserviceDemoR Documentation

Artificial mental-health service outcomes dataset

Description

Artificial dataset of treatment outcomes (N = 3739) of 13 mental-health services to illustrate fitting of (G)LMM trees with constant fits in terminal nodes.

Usage

data("MHserviceDemo")

Format

A data frame containing 3739 observations on 8 variables:

age

numeric. Variable representing age in years (range: 4.8 - 23.6, M = 11.46).

impact

numeric. Continuous variable representing severity of and impairment due to mental-health problems at baseline. Higher values indicate higher severity and impairment.

gender

factor. Indicator for gender.

emotional

factor. Indicator for presence of emotional disorder at baseline.

autism

factor. Indicator for presence of autistic disorder at baseline.

conduct

factor. Indicator for mental-health service provider.

cluster_id

factor. Binarized treatment outcome variable (0 = recovered, 1 = not recovered.

outcome

numeric. Variable representing treatment outcome as measured by a total mental-health difficulties score assessed about 6 months after baseline, corrected for the baseline assessment. Higher values indicate poorer outcome.

Details

Dataset was modelled after Edbrooke-Childs et al. (2017), who analyzed a sample of $N = 3,739$ young people who received treatment at one of 13 mental-health service providers in the UK. Note that the data were artificially generated and do not reflect actual empirical findings.

References

Fokkema M, Edbrooke-Childs J & Wolpert M (2021). “Generalized linear mixed-model (GLMM) trees: A flexible decision-tree method for multilevel and longitudinal data.” Psychotherapy Research, 31(3), 329-341. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10503307.2020.1785037")}

See Also

lmertree, glmertree

Examples


data("MHserviceDemo", package = "glmertree")
summary(MHserviceDemo)
lt <- lmertree(outcome ~ 1 | cluster_id | age + gender + emotional + 
               autism + impact + conduct, data = MHserviceDemo)
plot(lt)

gt <- glmertree(factor(outcome > 0) ~ 1 | cluster_id | age + gender + 
                emotional + autism + impact + conduct, 
                data = MHserviceDemo, family = "binomial")
plot(gt)


glmertree documentation built on June 28, 2024, 5:08 p.m.