Volume 1, Issue 2, November 2015, Page: 18-26
Analysis of Repeated Measures Data of Iraqi Awassi Lambs Using Mixed Model
Firas Rashad Al-Samarai, Department of Veterinary Public Health, College of Veterinary Medicine, University of Baghdad, Baghdad, Iraq
Fatten Ahmed Mohammed, Department of Veterinary and Animal Resource, Directorate of Baghdad Agriculture, Ministry of Agriculture, Baghdad, Iraq
Falah Hamed Al-Zaidi, Department of Veterinary and Animal Resource, Directorate of Baghdad Agriculture, Ministry of Agriculture, Baghdad, Iraq
Abbas Fawzy Al-Kalisy, Department of Veterinary Public Health, College of Veterinary Medicine, University of Baghdad, Baghdad, Iraq
Received: Oct. 30, 2015;       Accepted: Nov. 7, 2015;       Published: Nov. 13, 2015
DOI: 10.11648/j.ajasr.20150102.13      View  3573      Downloads  89
Abstract
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, measured between birth weight and 4th month of age, were used in the analysis. Most statistical approaches in such data are based on analysis of variance (ANOVA). However, the assumption that datum are independent is usually violated since several measures are performed on the same subject. As a result, standard regression and ANOVA may produce invalid results of repeated measures data because they require mathematical assumptions that were inconsistent with repeated data. The newest approach to analyzing of the repeated measurements is a mixed-model analysis. Advocates of this approach claimed that it provides the “best” approach to the analysis of repeated measurements. Therefore, the objective of the study was to investigate the effect of flock on growth performance of Awassi lambs using the mixed model. Three models was used: the first model consist of the effect of flock, time and flock by time interaction, the second model includes the same factors besides the quadratic effect of time, and the third model includes all factors in second model besides the time by time by flock interaction. Results revealed that the third model was better than other models and the effect of all factors on body weight of lambs was significant (P< 0.05) except the effect of flock, which was non-significant.
Keywords
Awassi, Growth Performance, Repeated ANOVA, Mixed Model
To cite this article
Firas Rashad Al-Samarai, Fatten Ahmed Mohammed, Falah Hamed Al-Zaidi, Abbas Fawzy Al-Kalisy, Analysis of Repeated Measures Data of Iraqi Awassi Lambs Using Mixed Model, American Journal of Applied Scientific Research. Vol. 1, No. 2, 2015, pp. 18-26. doi: 10.11648/j.ajasr.20150102.13
Copyright
Copyright © 2015 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Akbaş Y., Fırat M.Z., and Yakupoğlu C. 2001. Comparison of different models used in the analysis of repeated measurements in animal science and their SAS applications. Agricultural Information Technology Symposium, Sütçü İmam University, Agricultural Faculty, Kahramanmaraş, 20-22 September.
[2]
Algina J., and Kesselman H.J. 1997. Detecting repeated measures effects with univariate and multivariate statistics. Psychological Methods., 2: 208-218.
[3]
Eyduran E., Tatliyer A., Waheed, A., Tariq M. M. 2013. Determination of the most appropriate covariance structure for data with missing observations in repeated measures design., Ksu. J. Nat. Sci., 16(3): 32-37.
[4]
Eyduran E., and Akbaş Y. 2010. Comparison of diıfferent covariance structure used for experimental design with repeated measurement. J. Anim. Plant Sci., 20(1): 44-51.
[5]
Ganesan R., Dhanavanthan P., Kiruthika C., Kumarasamy P., and Balasubramanyam D. 2014. Comparative study of linear mixed-effects and artificial neural network models for longitudinal unbalanced growth data of Madras Red sheep. Veterinary World., 7(1): 52 – 58.
[6]
Greenhouse S. W., and Geisser S. 1959. On methods in the analysis of profile data. Psychometrika., 24: 95-112.
[7]
Huynh H., and Feldt L. 1970. Conditions under which mean square ratios in repeated measurements designs have exact F distributions. Journal of the American Statistical Association, 65: 1582-1589.
[8]
Huynh H., and Feldt L. S. 1976. Estimation of the Box correction for degrees of freedom from sample data in randomized block and split-plot designs. Journal of Educational Statistics, 1: 69-82.
[9]
Kebede K., and Gebretsadik G. 2010. Statistical modeling of growth performance data on sheep using mixed linear models. Livestock Research for Rural Development. Volume 22, Article #80.
[10]
Keskin S., and Mendeş M. 2001. Experimental Designs including repeated measurement in one’s levels of their factors. S.Ü. J. Agricultural Faculty., 15(25): 42-53.
[11]
Lal K. 2010. Analysis of repeated measures data using SAS. Indian Agricultural Statistics Research Institute. Library Avenue, Pusa, New Delhi., 113-120.
[12]
Little R. C., Henry P. R., and Ammerman C. B. 1998. Statistical analysis of repeated measures data using SAS procedures. J. Anim. Sci., 76:1216-1231. http://jas.fass.org/cgi/reprint/76/4/1216.
[13]
Littell R. C., Milliken G. A., Stroup W. W., and Wolfinger R. D. 1996. SAS system for mixed models, Cary, NC: SAS Institute.
[14]
Orhan H., Eyduran E., Akbaş Y. 2010. Defining The Best Covariance Structure for Sequential Variation on Live Weights of Aanatolian Merinos Male Lambs. J. Anim. and Plant Sci., 20(3), 158-163.
[15]
SAS Institute. 2010. SAS / STAT Users Guide for Personal Computer. Release 9.1, 2010; Inc., Cary, N.C., USA.
Browse journals by subject