Statistical analysis of repeated measures data using SAS procedures.

@article{Littell1998StatisticalAO,
  title={Statistical analysis of repeated measures data using SAS procedures.},
  author={Ramon C. Littell and Pamela R. Henry and Clarence B. Ammerman},
  journal={Journal of animal science},
  year={1998},
  volume={76 4},
  pages={
          1216-31
        }
}
Mixed linear models were developed by animal breeders to evaluate genetic potential of bulls. Application of mixed models has recently spread to all areas of research, spurred by availability of advanced computer software. Previously, mixed model analyses were implemented by adapting fixed-effect methods to models with random effects. This imposed limitations on applicability because the covariance structure was not modeled. This is the case with PROC GLM in the SAS System. Recent versions of… 
View on PubMed
stat.ncsu.edu
2,684 Citations
Highly Influential Citations
156
Background Citations
215
Methods Citations
986
Results Citations
13

2,684 Citations

Citation Type

Citation Type

The use of MIXED models in the analysis of animal experiments with repeated measures data
TLDR
The objective of this paper is to provide a background understanding of mixed model methodology in a repeated measures analysis and to use balanced steer data from a growth study to illustrate the use of PROC MIXED in the SAS system using five covariance structures.
Statistical modeling for growth data in linear mixed models - Implications derived from an example of a population comparison of Golden Hamsters
Using statistical modeling to determine the structure of expectation and covariance employed during analysis is a common feature of analytical research. This paper describes the necessary methodology…
The use of linear mixed model theory for the genetic analysis of repeated measures from clonal tests of forest trees. I. A focus on spatially repeated data
TLDR
Results indicate that the covariance is also a component of the genetic variance estimator and plays a significant role in assessing the variance of specific (micro) environmental effects.
Graphical Approaches to Support Mixed Model for Analysis of Growth Performance in Awassi Lambs
A b s t r a c t K e y w o r d s In this study, repeated records of body-weight of Awassi lambs were considered for analysis. Records included Up to five repeated records of body-weight per lamb,…
Power Analysis on Repeated Measures Designs
A simulation study comparing powers of the multivariate analysis (PROC GLM) with using a mixed model (PROC MIXED) using a variety of covariance structures for various treatment, time, and interaction…
Estimating and Predicting Feed Conversion in Broiler Chickens by Modeling Covariance Structure
Modeling covariance structure was used to estimate and to predict feed conversion in broile r chickens from one experiment under repeated-measures design. Eight treatments that consisted in a…
The effect of heritability estimates on high-density single nucleotide polymorphism analyses with related animals.
TLDR
The uncertainty of heritability estimates has a limited impact on SNP effect estimates in association analyses, but a large impact on significance tests, and efficient computational strategies to combine SNP test results across lines or breeds are developed.
Fixed effects arrays and residual covariance structures to analyze sequential weights of Canchim beef cattle
The aim of this work was to evaluate arrays of fixed effects and residual covariance structures that best fit the herd and the animal variability to weights at birth, weaning, twelve and eighteen…
Variogram investigation of covariance shape within longitudinal data with possible use of a krigeage technique as an interpolation tool: Sheep growth data as an example
Most quantitative traits considered in livestock evolve over time and several continuous functions have been proposed to model this change. For individual records (longitudinal data), it is evident…
A comparative study of different covariance structure models for the analysis of repeated measurement data
In repeated measurement data, the variables are not independent, and a certain auto-correlation typically exists between different levels of repeated measurement factors. The random error is composed…
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 14 REFERENCES
An approach to the analysis of repeated measurements.
TLDR
An approach to data analysis is presented which involves preliminary analysis by ordinary least squares, use of the empirical semi-variogram of residuals to suggest a suitable correlation structure, and formal inference using likelihood-based methods.
Conditions under Which Mean Square Ratios in Repeated Measurements Designs Have Exact F-Distributions
Abstract Investigation is made of the character of the covariance matrix which will result in exact F-distributions for the treatments and interaction variance ratios in repeated measurements…
Linear and Nonlinear Models for the Analysis of Repeated Measurements
The MANOVA model ANOVA and MANOVA for repeated measures crossover experiments the generalized multivariate analysis of variance (GMANOVA) model linear mixed-effects models for repeated measurements…
A Unified Approach to Mixed Linear Models
Abstract The mixed model equations as presented by C. R. Henderson offers the base for a methodology that provides flexibility of fitting models with various fixed and random elements with the…
Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
Abstract Recent developments promise to increase greatly the popularity of maximum likelihood (ml) as a technique for estimating variance components. Patterson and Thompson (1971) proposed a…
Relative bioavailability of magnesium sources for ruminants as measured by urinary magnesium excretion
Statistical Methods
TLDR
Principles of Statistical TechniquesA First Course, from the Beginnings, for Schools and Universities, for schools and Universities.
SAS ® System for Mixed Models. pp 31−63. SAS Inst. Inc
  • SAS ® System for Mixed Models. pp 31−63. SAS Inst. Inc
  • 1996
Analysis of messy data
SAS System for Linear Models
...
1
2
...