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Title: USING DIFFERENT TRANSFORMATIONS IN ANALYSES OF FECAL EGG COUNT DATA

Author
item Silva, Marcos
item Van Tassell, Curtis - Curt
item Sonstegard, Tad
item Gasbarre, Louis

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 3/23/2007
Publication Date: 4/25/2007
Citation: Silva, M.V., Van Tassell, C.P., Sonstegard, T.S., Gasbarre, L.C. 2007. Using different transformations in analyses of fecal egg count data. BARC Poster Day.

Interpretive Summary:

Technical Abstract: Fecal egg count (FEC) is used to identify and quantify gastrointestinal parasite infestations. However, FEC values are not distributed normally, and a small percentage of the herd is responsible for a majority of parasite transmission. Non-normality is a possible source of error when (co)variance components and genetic parameters are estimated. Logarithmic transformations have been used for these data before analysis. A total of 6,378 FEC measures were determined for 409 animals between 1992 and 2003 from Beltsville Agricultural Research Center Wye Angus herd. In this study, original data were transformed using various strategies: log transformation, an extension of the Box-Cox transformation using lambda parameter estimated by maximum likelihood (ML), and different values for lambda parameter (1; 0.5; -0.5 and -1) to approach normality and to estimate (co)variance components. Transformation of bovine FEC data utilizing the lambda parameter estimated by ML was effective in reducing the coefficients of asymmetry and kurtosis for all the variables studied, which improved estimates of variance components. These results indicate that after transforming data by the Box-Cox procedure using lambda parameter estimated by ML the genetic parameters may be more exact. As a result, the estimated heritability of FEC indicates the feasibility of obtaining genetic gain through selection.