Results 231 to 240 of about 2,396,506 (265)

Piecewise Growth Modeling Using SAS PROC MIXED

Measurement: Interdisciplinary Research and Perspectives, 2021
Typical longitudinal growth models assume constant functional growth over time. However, there are often conditions where trajectories may not be constant over time.
Sara Tomek, Cecil Robinson
openaire   +1 more source

Interval Estimation in Mixed Model by Use of PROC MIXED [PDF]

Ungyong T'onggye Yon'gu = the Korean Journal of Applied Statistics, 2006
PROC MIXED in SAS can be utilized to make inferences on parameters in a mixed model by use of Restricted Maximum Likelihood Estimation Method or Maximum Likelihood Estimation Method which has more merits than ANOVA method. A regression model with unbalanced nested error structure that belongs to a mixed model is used to construct confidence intervals ...
exaly   +2 more sources

Recovering Information in Augmented Designs, Using SAS PROC GLM and PROC Mixed

Agronomy Journal, 1997
AbstractThe SAS GLM and MIXED procedures can be useful for experimenters desiring to analyze data from screening experiments using a member of the class of augmented experiment designs. Since application of the procedures is typically not straightforward for these designs, several programs of possible interest are described.
Walter T Federer
exaly   +2 more sources

PROC MIXED and Early Phase Trials

Pharmaceutical Programming, 2011
AbstractPROC MIXED is commonly being used to compare treatment or other differences in phase 1 crossover trials. In such trials there is variation between subjects and also variation within subjects — these two sources of variation can be described by random effects.
exaly   +2 more sources

Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models

Journal of Educational and Behavioral Statistics, 1998
SAS PROC MIXED is a flexible program suitable for fitting multilevel models, hierarchical linear models, and individual growth models. Its position as an integrated program within the SAS statistical package makes it an ideal choice for empirical researchers and applied statisticians seeking to do data reduction, management, and analysis within a ...
Judith Singer
exaly   +2 more sources

Misleading Confidence Interval for Sum of Variances Calculated by PROC MIXED of SAS [PDF]

Ungyong T'onggye Yon'gu = the Korean Journal of Applied Statistics, 2004
exaly   +2 more sources

Estimating Actor, Partner, and Interaction Effects for Dyadic Data Using PROC MIXED and HLM: A User–Friendly Guide

Personal Relationships, 2002
Data collected from both members of a dyad provide abundant opportunities as well as data analytic challenges. The Actor–Partner Interdependence Model (APIM; Kashy & Kenny, 2000) was developed as a conceptual framework for collecting and analyzing dyadic data, primarily by stressing the importance of considering the interdependence that exists ...
Deborah A Kashy, Lorne Campbell
exaly   +2 more sources

Estimating Genotypic Correlations and Their Standard Errors Using Multivariate Restricted Maximum Likelihood Estimation With SAS Proc MIXED

Crop Science, 2006
Plant breeders traditionally have estimated genotypic and phenotypic correlations between traits using the method of moments on the basis of a multivariate analysis of variance (MANOVA). Drawbacks of using the method of moments to estimate variance and covariance components include the possibility of obtaining estimates outside of parameter bounds ...
Jim Holland
exaly   +2 more sources

PROC GLM versus PROC MIXED

2015
In vielen Fallbeispielen werden die Varianzanalysen und Mittelwertvergleiche entweder mit den SAS-Prozeduren GLM oder MIXED ausgefuhrt. Wahrend GLM nach der Methode der kleinsten Quadrate (least squares, LS-Methode) vorgeht und zwei der vier beschriebenen Varianztypen – Typ I und Typ III – standardmasig liefert, verwendet MIXED voreingestellt die ...
openaire   +1 more source

Generalised linear mixed models with the new proc nlmixed procedure

In this Thesis, we study the Generalised Linear Mixed Models with application in SAS with the new Proc Nlmixed Procedure. Firstly, we talk about Fixed Models and afterwards we pass in the definition of Mixed Models, explaining the Random Effects Models, Covariance Pattern Models and Random Coefficient Models.
openaire   +1 more source