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Linear mixed modeling, using SAS PROC MIXED [ 54] will test time and group interactions to asses whether within-subject change in BMI differs by condition.
Linear mixed modeling, using SAS PROC MIXED [ 41] will test time and group interactions to asses whether within-subject change in body weight differs by condition.
To partition trait variation into components of genetic and environmental variance, we performed linear mixed modeling using ASReml v3.0 (Gilmour et al. 1995).
Linear mixed modeling, using SAS PROC MIXED [ 67] will test time and group interactions to assess whether within-subject change in Juniper ACQ scores differs by condition (equation 3).
For example, in a retrospective cohort study of over 800,000 Veterans with type 2 diabetes with longitudinal data over 5 years, fitting REM via generalized linear mixed modeling using currently available standard procedures in SAS (e.g. PROC GLIMMIX) was very difficult and same problems exist in Stata's gllamm or R's lme packages.
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All models were fitted as nonlinear mixed models using the SAS macro NLINMIX.
Data were analysed as a mixed model using the PROC MIXED of SAS.
Data were analyzed in linear mixed models using repeated measures within herd where MFP was considered the outcome variable.
Plasma glucose levels over time were compared between groups with a linear mixed model using SAS software.
We performed linear mixed models using S4 classes version 0.999375-28 in R. The data we used are included in the Appendix S1.
Statistical analysis was done with mixed models using the PROC MIXED module of SAS™.
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