Multivariate cubic spline smoothing in multiple prediction.

Abstract:

:Given longitudinal data for several variables, including a given outcome variable, it is desired to predict the outcome for a specific individual, or more generally experimental unit, in such a way that the predicted value is both accurate and resistant (i.e. has good cross-validation). There are certain data-analytic difficulties associated with long-term multivariate longitudinal data that must be overcome in the prediction process. This paper provides a program written in the Statistical Analysis System (SAS) programming language, based generally on the Roche-Wainer-Thissen stature prediction model, that enables the researcher to overcome these difficulties.

authors

Khamis H,Kepler M

doi

10.1016/s0169-2607(01)00114-6

subject

Has Abstract

pub_date

2002-02-01 00:00:00

pages

131-6

issue

2

eissn

0169-2607

issn

1872-7565

pii

S0169260701001146

journal_volume

67

pub_type

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