EconPapers    
Economics at your fingertips  
 

MULTISPLINE: Stata module to perform nonlinear multilevel spline modeling

Subir Hait

Statistical Software Components from Boston College Department of Economics

Abstract: multispline fits nonlinear multilevel regression models using natural cubic spline basis expansion. It provides a unified workflow for fitting, predicting, visualizing, and summarizing nonlinear effects in hierarchical or longitudinal data. The command is particularly suited to large-scale education and health datasets such as ECLS-K, HSLS, and PISA where outcomes are expected to have nonlinear relationships with predictors such as socioeconomic status (SES) or treatment dosage. While Stata provides mixed for multilevel models and mkspline for spline construction, no existing Stata command provides a unified workflow for fitting, predicting, visualizing, and computing ICCs from nonlinear multilevel models. multispline fills this gap.

Language: Stata
Requires: Stata version 14.1
Keywords: splines; panel data (search for similar items in EconPapers)
Date: 2026-03-02
Note: This module should be installed from within Stata by typing "ssc install multispline". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
References: Add references at CitEc
Citations:

Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/m/multispline.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/m/multispline.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/m/multispline_example.do program code (text/plain)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s459620

Ordering information: This software item can be ordered from
http://repec.org/docs/ssc.php

Access Statistics for this software item

More software in Statistical Software Components from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().

 
Page updated 2026-03-20
Handle: RePEc:boc:bocode:s459620