The Effect of Selective Reporting on Estimates of Weaning Weight Parameters in Beef Cattle

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1 The Effect of Selective eporting on Estimates of Weaning Weight Parameters in Beef Cattle C. H. Mallinckrodt, B. L. Golden, and. M. Bourdon Department of Animal Science, Colorado State University, ort Collins 8023 ABSTACT: The effect of selective reporting on estimates of weaning weight parameters in beef cattle was evaluated by comparing EML estimates from unaltered and altered simulated data. Selective reporting reduced estimates of weaning weight direct (WWD), maternal milk (MAT), and error variances. However, heritability estimates were not greatly affected because the reductions in variance estimates were relatively proportionate. When the true value for the direct-maternal (DM) correlation was zero or negative, selective reporting caused estimates of DM to be less positive or more negative in 0 of 62 comparisons, with an average change of When the true value for DM was positive, selective reporting increased the positive magnitude ofdm estimates in 12 of 20 comparisons, with an average change of In BLUP of unaltered data with a true DM value of -.09, using a -.28 and a zero DM correlation reduced the correlation of MAT EPD with true values.06 and.041, respectively. These results suggest that the reliability of parameter estimates (and BLUPs) would be improved by estimating parameters from representative subsets of data free of reporting bias. Key Words: Beef Cattle, Variance Components, Data Biases, Weaning Weight J. Anim. Sci : Introduction Evidence of Selective eporting in ield Data. Elzo et al. (1987) and Garrick et al. (1989) reported that more than 60% of the observations in the American Association (ASA) data set were from females. Evidently, selective reporting of weaning data was more prevalent for bulls than for heifers. Garrick ( 1988) also reported that this differential reporting was not consistent among sire groups. Some sires had as few as 39% of progeny records from heifer calves, whereas others had more than 80% of their data from heifer calves. The ASA requires weaning data for registry and has always encouraged performance testing. Nevertheless, only 2% of the animals with weaning data also had yearling weights reported and only 60% had birth weights reported (Elzo et al., 1987; Garrick et al., 1989). Similar trends (unpublished) were reported to exist in other breed association data sets. Mallinckrodt et al. (1992) reported that altering simulated data by random nonreporting and selective reporting of performance data both caused important reductions in correlations of true values with EPD, but the changes were greater for selective reporting. eceived July 14, Accepted December 17, Because EPD (EBV) are used in the calculations of EML estimates of (co)variation, selective reporting could also influence EML estimates. Objectives of This Study. Meyer et al. ( 1993 noted the widespread concerns about potential biases to estimates of direct-maternal ( DM) correlations. One assumption of BLUP is that the (colvariance structure of the random effects is known (Henderson, 1984). In practice this means that reasonably good estimates must be available (Quaas and Pollak, 1980; Gianola and ernando, 1986). The accuracy of estimates of (colvariance depends on the methodology, the model, and the choice of data (Misztal, 1990). Comparing methods and models was beyond the scope of thistudy. Our objectives were to use currently ( 1994) accepted methodology to evaluate the effect of selective reporting of performance data on the reliability of weaning weight parameter estimates. Experimental Procedure Data Simulation. A procedure described by Van Vleck and Gregory (1992) and detailed by Mallinckrodt (1993) was used to simulate weaning weight ( WW) data with pedigree and contemporary group structures from real data sets. Observations included additive direct ( WWD) and temporary environmental 1264 Downloaded from

2 ( E) effects of calves and additive maternal ( MAT) and permanent maternal environmental ( PE) effects of dams. These values were summed and contemporary group structures from real data sets and contemporary group solutions from BLUP of those data were used to add on fixed effects and create the final observations. Sex effects were not simulated. Selection based on phenotype or predicted breeding value was not simulated. Data. Descriptive information for the combinations of pedigree and contemporary group structures (called herds for convenience) are listed in Table 1. Herd XYZ was a breed association data set. Herd BS was a data set from a private ranch that was part of a breed association data set and reported all data. Herd was a research herd. It had characteristics similar to those of the other herds but was not part of any breed association. Years from the birth date of the oldest animal to the birth date of the youngest animal were 29, 30, and 3 yr for the XYZ, BS, and herds, respectively. Data were generated using the parameters in Table 2. our levels of direct-maternal genetic covariance were used across the three herds to test results over the range of conditions that were likely to exist in real data. Data Problems. This investigation focused on the effect of selective reporting of performance data on estimates of genetic and environmental parameters for weaning weight. However, other problems may also bias field data. or example, Mallinckrodt et al. ( 1992) reported that random nonreporting of performance data, selective reporting of pedigree information, misrepresenting contemporary groups, misidentifying parents, and guessing at or willfully falsifying data were all problems typically found in field data. These data problems could interact to cancel or enhance the effects of selective reporting of performance data, Investigating the joint effects of these data problems on parameter estimates was beyond the scope of this project but may warrant investigation. Specific alterations that were introduced into the simulated data and their reference names were select 2 (2% of observations deleted by randomly removing 0% of the lowest 0%' of phenotypic observations), and trunc 2 (lowest 2% of observations deleted). Average weaning weights from the select 2 Table 1. Description of herds No. of Herd Animals WW obsa Dams Inbreds Sires 12,770 18,331 3,142 3, BS 8,7149,481 2,732 6, XYZ,32 39,991 23,991 2,182 94,641 obs = weaning weight observations. EECT EPOTING O SELECTIVE 126 Table 2. Parameters used to simulate weaning weight dataa PE WWD MAT PE WWD (+20, -20, -61) MAT 16 avariances on diagonal (kilograms squared), covariance above diagonal (kilograms). PE = permanent maternal environmental variance, WWD = additive direct variance, MAT = additive maternal, error variance = 248. and trunc 2 data sets were 6 and 13 kg greater, respectively, than the corresponding fully reported data sets. Deletions were based on absolute level of performance, not on performance within contemporary group. Pedigree information was not deleted for animals whose observations were removed. If an individual had a record deleted, it was still allowed to become a parent. This occurred in breed association data sets whenever animals with popular pedigrees or attractive visual characteristics were kept or sold as replacements despite poor actual performance. Parameter Estimation. Observational components of (co)variation were estimated in altered and unaltered data with an exact (no approximations) EML using a sire-maternal grandsire ( s-mgs) model and the expectation maximization algorithm outlined by Harville ( 197 7). Estimates of genetic and environmental (cohariances were obtained by equating the observational components to corresponding causal components and simultaneously solving the system of equations (Garrick, 1988). The Animal Breeders Tool Kit software (Golden et al., 1992) was used to assemble and solve the mixed- model equations in all analyses. Evaluating esults. The effect of selective reporting of performance data on parameter estimates was evaluated by comparing estimates from unaltered data to estimates from the same data sets after they were altered by selective reporting. Average changes in parameter estimates were calculated and their reliability evaluated by comparing the average change for each parameter to the corresponding standard error of the average change (standard deviation of changes divided by the square root of the number of replicates). The effect of selective reporting was also evaluated by comparing the correlations between WWD and MAT true breeding values when the true values of all animals were included, versus that same correlation when only the true values of animals that had an observation in the selectively reported data were used. This analysis allowed us to ascertain whether selectively reported subsamples of data accurately represented the corresponding entire populations. Experimental Design. The number of comparisons (i.e., the number of simulated data sets) by herd, Downloaded from

3 1266 MALLINCKODT ET AL. level of DM, and type of reporting bias (trunc 2 or Table 4. Average and standard error select 2) are listed in Table 3. Considering only the BS and herds, the design was completely balanced. The computational demands of estimating parameters from the large XYZ herd prevented us Standard from using it as often as the other herds. The XYZ error of herd was included simply to verify that results from the BS and herds were indicative of results from breed association data structures. of changes in heritability estimates of weaning weight direct due to selective reporting No. Average average of Bias change change comparisons Select Trunc esults and Discussion Changes in Heritability Estimates Due to Selective eporting. Average and standard error of changes in heritability estimates of WWD and MAT due to altering data by selective reporting are listed in Tables 4 and, respectively. Selective reporting consistently reduced estimates of all genetic and residual variances. When data were eliminated by truncation (trunc 21, variance estimates were reduced more than when the same number of records wereliminated as a random subset of a larger proportion of the data (select 2). Changes in genetic and residual variance estimates were relatively proportionate, however, leading to inconsistent changes in heritability estimates. Selective reporting tended to reduce heritability estimates for WWD but had little overall impact on estimates of MAT heritability. Changes in Estimates of the Direct-Materna7 Correlation Due to Selective eporting. The effect of selective reporting on estimates ofdm depended on the true value of DM. Average and standard error of changes are listed by true value and type of reporting bias (trunc 2 vs select 2) in Table 6. When the true value of DM was zero or negative, selective reporting caused estimates ofdm to be less positive or more negative in altered data than in corresponding unaltered data in 0 of 62 (80.6%) comparisons. The average change in DM estimates pooled across all comparisons when the true value of DM was zero or negative was As the standard errors indicate, Table 3. Number of simulations by herd, true of the direct-maternal correlation and type of reporting biasa value True value of the direct-maternal correlation Herd Type Total BS Select 220 BS Trunc 2 20 Select 2 20 Trunc 220 XYZ Select Totals adescriptions of types of reporting bias are described in the text. these changes were almost certainly not due to chance alone. When the true value for DM was positive, selective reporting tended to have the opposite effect; 12 of 20 (60%) estimates of DM were more positive or less negative in altered data than in corresponding unaltered data. The average change across all comparisons when the true value of DM was positive was As explained below, case study and small examples suggested data structure could influence the effect of selective reporting on estimates of DM. However, average changes in estimates ofdm were not significantly different for the herds used in this study. Average changes in estimates of the direct-maternal covariance are listed in Table 7. Changes in these values were generally in the same direction as changes in estimates of DM. Some differences existed because selective reporting tended to reduce estimates of the weaning weight direct genetic variance. Causes of Bias rom Selective epovting. We identified two ways by which selective reporting biased estimates of DM (and the direct-maternal covariance). irst, selective reporting created a subset of data that did not accurately represent the entire population. Second, selective reporting caused unfair performance comparisons that altered EPD. In Table 8 correlations between WWD and MAT true breeding values from all animals in a data set were compared to the same correlations when only the true breeding values of animals with an observation in selectively reported data (trunc 2) were included. In all comparisons the correlation between true breeding values for only those animals with an observation in Table. Average and standard error of changes in heritability estimates of maternal milk due to selective reporting Standard error of No. Average average of Bias change change comparisons Select 2,009, Trunc 2 -.om Downloaded from

4 EECT O SELECTIVE EPOTING Table 6. Average and standard error of changes in estimates of the direct-maternal correlation due to selective reportinga 1267 True value of the direct-maternal correlation Bias Select (.068)a -.l69(.029) (.036) -.l38(.044) Trunc (.071) (.046) -.l4(.043) (.03) astandard errors in parentheses. the selectively reported subset was less positive or more negative than in the corresponding full data set. These results agree with and help explain changes in estimates ofdm when the true value for DM was zero or negative. However, when the true value of DM in unalteredata was positive, changes in the correlations between the true values in the selectively reported subsets was opposite of the average changes in estimates of DM. Case studies of individuals in the BS and herds and small examples using selection indices suggested selective reporting also biased estimates of DM by creating unfair performance comparisons. The effect was different for parents and nonparents. The scenario depicted in Table 9 is representative of results from case studies and examples. In this example the only information initially available on sires 1 and 2 came from the one contemporary group described in Table 9. Selective reporting of sire l s progeny biased sire l s WWD EPD upward and biased sire 2 s WWD EPD downward. With only progeny information available, MAT EPD of sires 1 and 2 were biased in the opposite direction of WWD EPD because a negative DM correlation was used. When a zero DM correlation was used, MAT EPD of sires 1 and 2 were not altered. Biases to EPD were greater for sire 2 (complete reporting) than for sire 1 (selective reporting). Sire 2 s EPD were affected more than sire l s EPD because sire 2 had more data affected by the bias ( reported progeny vs 10 reported progeny). The WWD and total maternal EPD of sire l s progeny were also biased upward by selective reporting, and the WWD EPD of sire 2 s progeny were biased downward. The biases to progeny EPD resulted in maternal grandprogeny of sire 1, on average, not performing as well as predicted. This lowered the WWD and MAT EPD of sire 1 and his daughters. The MAT EPD were reduced more than WWD EPD because MAT EPD were lower in accuracy. Maternal grandprogeny of sire 2, on average, performed better than predicted. This increased the WWD and MAT EPD of sire 2 and his daughters. The MAT EPD were raised more than WWD EPD because MAT EPD were lower in accuracy. After including maternal grandprogeny, bias existed in MAT EPD of sires 1 and 2 regardless of the value of DM used to calculated the EPD. The end result was that bias to MAT EPD was greater than, and in the opposite direction of, WWD EPD. This caused the cross product of sire by maternal grandsire solutions in the s-mgs EML quadratic to be unduly negative (less positive) and, all else equal, forced a corresponding change in the estimate of DM. The effect of selective reporting on the EPD of nonparents was different because they did not have progeny and grandprogeny that failed to perform as expected. If a nonparent benefited from selective reporting, its WWD EPD was again too high, but its MAT EPD was usually also too high because its dam was given undue credit for milk from the biased calf record. or similar reasons, a nonparent with a record adversely affected by selective reporting had WWD and MAT EPD that were too low. The magnitude of the bias to WWD and especially MAT EPD depended on the sign and magnitude of the true value of DM. Such changes consistently occurred in case studies of individual animals. These results suggested that the effect of selective reporting may be influenced by pedigree structure, true parameters, and the proportion of dat altered. Extrapolations from the case studies to overall changes in the herds used in this study were hindered by the confounding influences of changes in other observational components of variance and prediction error (colvariance and by the sampling bias to the correlation between true values explained earlier. In general, however, the direction and magnitude overall changes to sire by maternal grandsire solutions in the EML quadratic depended on the true Table 7. Average changes in estimates of the direct-maternal covariance due to selective reporting True value of the direct-maternal covariance Bias Select Trunc of Downloaded from

5 1268 AL. ET MALLINCKODT Table 8. Correlations between true values for direct and maternal components of weaning weight from unaltered data and selectively reported subsets of data Herd BS XYZ BS BS XYZ BS No. of comparisons 1 1 Average correlations between true breeding values True value All animals Top 7%a agreeding values deleted for those who had an observation deleted with 2% truncation l l l846 -.l value of DM. When the true value of DM was positive, the positive magnitude of changes to the sire by maternal grandsire quadratic was large enough to offset the negative sampling bias and resulted in positive average changes in estimates ofdm. When the true value of DM was negative, the changes to the crossproduct and sampling bias were both negative and resulted in more consistent changes in estimates of DM. Our study estimates of In contrast, Discussion suggested that selective reporting biased DM. Biased data yielded biased results. Bertrand and Kriese ( 1990) and See ( 1990) reported that selective reporting did not influence estimates of genetic correlations. However, Bertrand and Kriese investigated the relationship between direct effects for weaning weight and post- weaning gain in data simulated without maternal effects for weaning weight. See reported on a directmaternal correlation but selective reporting was based on performance in another trait. These were very different conditions from those investigated here. Meyer et al. (1993) reported results that strengthened earlier speculations that many of the negative estimates of DM were likely biased and not the result of antagonistic genetic relationships, especially in field data. Ou results also strengthen that conclusion. Published estimates ofdm are listed individually in Table 10. In addition to those estimates, Meyer et al. ( 1993) reported that the best results were obtained from models assuming a zero value for DM when estimating parameters in s and the composite breed Wokalup. This investigation focused on only one aspect of how choice of data can influence estimates of DM. Many of the other issues concerning choice of data, methods, and models need further investigation. or example: Do genotype x environment, or more complex interactions, have an important effect on estimates ofdm? What statistical procedures, computational techniques, and data structures yield reliable estimates of DM? Most importantly, how reliably must DM be estimated so that the gain in reliability of WWD and MAT EPD from including DM in BLUP is greater than the error introduced by including an estimate that does not exactly describe the true genetic relationship? Some usable critera for judging completeness and accuracy of reporting are: 1) overall male to female Table 9. Description of case study scenario Subsequent Initial Initial Complete Total No. Selected EPDe Selected EPDd Selected complete EPDC progeny averagea reported averageb WWD MAT WWD MAT WWD MAT Sire Sire l +l +4 Group aaverage weaning weight of all calves. baverage weaning weight of reported calves. EPD calculated from all initial data. depd calculated from selectively reported initial data. eepd calculated from initial selectively reported data plus subsequent data from five maternal grandprogeny for each sire. Downloaded from

6 Table 10. Estimates of direct-maternal correlations for weaning weight Source Breed Type Correlation Skaar (198) Johnson et al. (1992) Mallinckrodtb ( 1993) Waldron (personal comm.) Waldron (personal C0mm.J Kriese et al. (1991 ) Bertrand + Kriese (1990) Knese et al. (1991) Kriese et al. (1991) Cantet et al. (1988) Hohenboken + Brinks (1971) Waldron (personal comm.) Kriese et al. (1991) Bertrand 11988) Skaar (198) Johnson et al. (1992) Bertrand + Kriese (1990) Kriese et al. (1991) Wright et al. (1991) Wright et al. (1984) Quaas et al. (1984) Garrick (1988) Beefmaster Brangus Brangus Brahman Brown Swiss Charolais Gelbvieh Limousin Limousin Marc 111 ed Poll Pinzgauer Santa Gertrudis Senepol EECT EPOTING O SELECTIVE l c.06.oo l g7 +.l a is for field data, is for research data. bthis estimate has not previously been reported. It is from the John ouse, Colorado State University research herd in Saratoga, W. Heritability estimates of WWD and MAT were.30 and.21, respectively. ratio, 2) male to female ratio by sire group, 3) proportion of dams with calf data reported in consecutive years, 4) normality of distribution of weights within and across contemporary groups, and ) proportion of standard and(or) round number weights. Of course, if we knew how much bias existed we could adjust for it and it would not be a problem. Implications Although we noted that other data problems may also influence parameter estimates, this study suggested that the reliability of estimates of DM could be improved if data were free of reporting bias. Educational efforts that promote proper data reporting, simple reporting procedures, and economic incentives to report all data should be implemented. More reliable parameter estimates could be obtained from subsets of data deemed to be complete and accurate. We believe inventory-based reporting and fees would improve the quality of data used in national cattle evaluations. Literature Cited Bertrand, J. K A comparison of two methods of parameter estimation for the reduced animal model. J. Anim. Sci. 66(Suppl. 1):14 (Abstr.). Bertrand, J. K., and L. A. Kriese Two methods for parameter estimation using multiple-trait models and beef cattle field data. J. Anim. Sci. 68:2310. Boldman, K. G., L. D. Van Vleck, K. E. Gregory, and L. V. Cundiff Estimates of direct and maternal parameters for 200 d weight in purebred and composite lines of beef cattle. J. him. Sci. 69(Suppl. 1):203 (Abstr.). Cantet,.J.C., D.D. Kress, D. C. Anderson, D. E. Doornbos, P. J. Burfening, and. L. Blackwell Direct and maternal variances and covariances and maternal phenotypic effects on preweaning growth of beef cattle. J. Anim. Sci. 66:648. Elzo, M.A.,. L. Quaas, and E. J. Pollak Effects of age of dam on traits in the population. J. Anim. Sci. 64: 992. Garrick, D. J estricted maximum likelihood estimation of variance components for multiple traits with missing observations and an application to beef cattle. Ph.D. Dissertation. Cornell Univ., Ithaca, NY. Garrick, D. J., E. J. Pollak,. L. Quaas, and L. D. Van Vleck Variance heterogeneity in direct and maternal weight traits by sex and percent purebred for -sired calves. J. Anim. Sci. 67:21. Gianola, D., and. L. ernando Bayesian methods in animal breeding theory. J. Anim. Sci. 63:217. Golden, B. L., W. S. Snelling, and C. H. Mallinckrodt Animal Breeder s Toolkit: Users guide and reference manual. Colorado State Univ. Agric. Exp. Sta. Tech. Bull. LTB92-2. Harville, D.A Maximum likelihood approaches to variance component estimation and related problems. J. Am. Stat. Assoc. 72:320. Henderson, C Applications of Linear Models in Animal Breeding. Univ. of Guelph Press, Canada. Hohenboken, W. D., and J. S. 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Donnelly Genetic parameters for growth traits of Australian beef cattle from a multibreed selection experiment. J. Anim. Sci. 71:2614. Misztal, I estricted maximum likelihood estimation of variance components in animal model using sparse matrix inversion and a supercomputer. J. Dairy Sci. 73:163. Quaas,. L., M. A. Elzo, and E. J. Pollak Analysis of data: Estimation of direct and maternal genetic (co)variances. J. Anim. Sci. 61(Suppl. 1):221 (Abstr.). Quaas,. L., and E. J. Pollak Mixed model methodology for farm and ranch beef cattle testing programs. J. Anim. Sci. 1: Downloaded from

7 1270 MALLINCKODT ET AL. See, M. T Differential reporting of records in the Yorkshire with underlying multivariate normal distributions. J. him. sow productivity program and its effects on variance and covariance component estimation. Ph.D. Dissertation. Univ. of Geor- Sci. 70:7. Wright, D. W., Z. B. Johnson, C. J. Brown, and S. Waldus gia, Athens. Variance and covariance estimates for weaning weight of Skaar, B.., 198. Direct genetic and maternal variance and covariance components from and field data. Ph.D. Dissertation. Iowa State Univ., Ames. Senepol cattle. J. Anim. Sci. 69:394. Wright, H. B., E. J. Pollak, and. L. Quaas Estimation of variance and covariance components to determine heritabilities Van Vleck, L. D., and K. E. Gregory Multiple-trait restricted and repeatability of weaning weight in American maximum likelihood for simulated measures of ovulation rate cattle. J. Anim. Sci. 6:97. Downloaded from