Analysis of longitudinal data in craniofacial research: some strategies. Academic Article

abstract

• Although it is generally acknowledged that longitudinal data provide the most information on growth and development and other time-dependent phenomena, such data are often analyzed by conventional (cross-sectional) statistical methods. This widespread practice ignores the distinctive characteristics (e.g., covariance structure) of longitudinal data and may yield misleading results. The purpose of this article is to present some strategies and make available computer programs for the appropriate analysis of longitudinal data. User-friendly PC programs for the estimation of average growth curves, computation of tracking indices, prediction of future values, diagnosis, classification, clustering, estimation of missing values, and testing hypotheses concerning individual and group differences are presented. Benefits of these methods over the usual techniques are illustrated with the example of maxillary growth in the rhesus monkey.

authors

• Schneiderman, Emet

published proceedings

• Crit Rev Oral Biol Med

author list (cited authors)

• Schneiderman, E. D., & Kowalski, C. J.

citation count

• 7

complete list of authors

• Schneiderman, ED||Kowalski, CJ

publication date

• September 1994

publisher

• SAGE Publications  Publisher

published in

• Journal of Dental Research  Journal

keywords

• Animals
• Cross-Sectional Studies
• Data Interpretation, Statistical
• Facial Bones
• Female
• Forecasting
• Longitudinal Studies
• Macaca Mulatta
• Male
• Maxilla
• Skull
• Software
• User-Computer Interface

PubMed Central ID

• 7703322

Digital Object Identifier (DOI)

• 10.1177/10454411940050030101

start page

• 187

end page

• 202

volume

• 5

issue

• 3-4

URL

• http://dx.doi.org/10.1177/10454411940050030101