Impact of Censored or Penalized Data in the Genetic Evaluation of Two Longevity Indicator Traits Using Random Regression Models in North American Angus Cattle

Oliveira, Hinayah Rojas de; Miller, Stephen; Brito, Luiz F.; Schenkel, F.S.

doi:10.3390/ani11030800

Cited by 5 publications

(5 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e Bayesian framework for analyzing censored survival data [55]; the β-substitution method compared with the Bayesian method [42]; search-and-score-hillclimbing algorithm and constraint-based conditional independence algorithm on censored survival data [43,44]; frequentist and Bayesian approaches to handling censored data and the Markov chain Monte Carlo for imputed data (MCMCid) [46,47]; quantile regression [43,48,49]; random effects hierarchical Cox proportional hazards [50].…”

Section: Discussionmentioning

confidence: 99%

“…Reference [42] penned down a study aimed at evaluating the impact of different proportions (i.e., 20%, 40%, 60% and 80%) of censored (CEN) or penalized (PEN) data in the prediction of breeding values (EBVs), genetic parameters, and computational efficiency for two longevity indicators (i.e., traditional and functional longevity; TL and FL, respectively). ree different criteria were proposed for PEN: (1) assumed that all cows with censored records were culled one year after their last reported calving; (2) assumed that cows with censored records older than nine years were culled one year after their last reported calving, while censored (missing) records were kept for cows younger than nine years; (3) assumed that cows with censored records older than nine years were culled one year after their last reported calving, while cows younger than nine years were culled two years after their last reported calving.…”

Section: Developments Made To Handle Censored Datamentioning

confidence: 99%

“…Reference [42] has noted that classical statistical methods used for analyzing exposure data with values below the detection limits were well described in the occupational hygiene literature but revealed that evaluation of such data using the Bayesian approach was currently lacking. ey proceeded to describe a Bayesian framework for analyzing censored data and presented the results of a simulation study conducted to compare the β-substitution method with a Bayesian method for exposure datasets drawn from lognormal distributions and mixed lognormal distributions with varying sample sizes, geometric standard deviations (GSDs) and censoring for single and multiple limits of detection.…”

Section: Developments Made To Handle Censored Datamentioning

confidence: 99%

See 2 more Smart Citations

Handling Censoring and Censored Data in Survival Analysis: A Standalone Systematic Literature Review

Turkson

Ayiah-Mensah

Nimoh

2021

International Journal of Mathematics and Mathematical Sciences

View full text Add to dashboard Cite

The study recognized the worth of understanding the how’s of handling censoring and censored data in survival analysis and the potential biases it might cause if researchers fail to identify and handle the concepts with utmost care. We systematically reviewed the concepts of censoring and how researchers have handled censored data and brought all the ideas under one umbrella. The review was done on articles written in the English language spanning from the late fifties to the present time. We googled through NCBI, PubMed, Google scholar and other websites and identified theories and publications on the research topic. Revelation was that censoring has the potential of biasing results and reducing the statistical power of analyses if not handled with the appropriate techniques it requires. We also found that, besides the four main approaches (complete-data analysis method; imputation approach; dichotomizing the data; the likelihood-based approach) to handling censored data, there were several other innovative approaches to handling censored data. These methods include censored network estimation; conditional mean imputation method; inverse probability of censoring weighting; maximum likelihood estimation; Buckley-Janes least squares algorithm; simple multiple imputation strategy; filter algorithm; Bayesian framework; β -substitution method; search-and-score-hill-climbing algorithm and constraint-based conditional independence algorithm; frequentist; Markov chain Monte Carlo for imputed data; quantile regression; random effects hierarchical Cox proportional hazards; Lin’s Concordance Correlation Coefficient; classical maximum likelihood estimate. We infer that the presence of incomplete information about subjects does not necessarily mean that such information must be discarded, rather they must be incorporated into the study for they might carry certain relevant information that holds the key to the understanding of the research. We anticipate that through this review, researchers will develop a deeper understanding of this concept in survival analysis and select the appropriate statistical procedures for such studies devoid of biases.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Developments Made To Handle Censored Datamentioning

confidence: 99%

Section: Developments Made To Handle Censored Datamentioning

confidence: 99%

See 1 more Smart Citation

Handling Censoring and Censored Data in Survival Analysis: A Standalone Systematic Literature Review

Turkson

Ayiah-Mensah

Nimoh

2021

International Journal of Mathematics and Mathematical Sciences

View full text Add to dashboard Cite

show abstract

“…Traits that have censored records (e.g., age at first calving and slaughter, longevity) are frequently evaluated in animal breeding programs (Santos et al, 2015;Costa et al, 2019;Oliveira, Miller, Brito, & Schenkel, 2021). In the presence of censoring, the value for a given trait is greater or less than a certain threshold, or belongs to an interval, and it is not possible to observe an exact value for response.…”

Section: Introductionmentioning

confidence: 99%

Alternative measures to evaluate the accuracy and bias of genomic predictions with censored records

Pereira,

Martins Filho,

Veroneze

et al. 2023

Acta Sci. Anim. Sci.

Self Cite

View full text Add to dashboard Cite

This study aimed to propose and compare metrics of accuracy and bias of genomic prediction of breeding values for traits with censored data. Genotypic and censored-phenotypic information were simulated for four traits with QTL heritability and polygenic heritability, respectively: C1: 0.07-0.07, C2: 0.07-0.00, C3: 0.27-0.27, and C4: 0.27-0.00. Genomic breeding values were predicted using the Mixed Cox and Truncated Normal models. The accuracy of the models was estimated based on the Pearson (PC), maximal (MC), and Pearson correlation for censored data (PCC) while the genomic bias was calculated via simple linear regression (SLR) and Tobit (TB). MC and PCC were statistically superior to PC for the trait C3 with 10 and 40% censored information, for 70% censorship, PCC yielded better results than MC and PC. For the other traits, the proposed measures were superior or statistically equal to the PC. The coefficients associated with the marginal effects (TB) presented estimates close to those obtained for the SLR method, while the coefficient related to the latent variable showed almost unchanged pattern with the increase in censorship in most cases. From a statistical point of view, the use of methodologies for censored data should be prioritized, even for low censoring percentages.

show abstract

“…The analysis of this database can guide effective management actions for reducing early involuntary culling of dairy cows and perhaps refining current breeding goals. For instance, recent studies in North American Angus cattle reported different variance components and heritabilities estimated for longevity depending on the culling reason ( Oliveira et al, 2020a , 2020b ). Thus, the main objectives of this study were to describe the frequencies of different culling reasons in Canadian Holstein cows and evaluate the impact of systematic factors such as cow age, year, season, province, climate, and ecozone on the frequencies of different culling reasons.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive characterization of longevity and culling reasons in Canadian Holstein cattle based on various systematic factors

de Souza,

Pinto,

da Cruz

et al. 2023

Translational Animal Science

Self Cite

View full text Add to dashboard Cite

The decision of premature culling cows directly impacts the profitability of dairy farms. A comprehensive characterization of the primary causes of culling reasons would greatly improve both management and selection objectives in dairy cattle breeding programs. Therefore, this study aimed to analyze the temporal frequencies of 34 culling reasons in Canadian Holstein cows. After data editing and quality control, records from 3,096,872 cows culled from 9,683 herds spread across Canada were used for the analyses covering the periods from 1996 to 2020. Reproductive issues were the main culling reason accounting for 23.02%, followed by milk production (20.82%), health (20.39%), conformation problems (13.69%), economic factors (13.10%), accidents (5.67%), age-related causes (1.67%), and workability (1.63%). Nearly fifty-eight percent of cows were culled after 47 months of age. The observed frequencies of culling due to economic factors were lower than expected from 1996 to 2014 and higher than expected between 2015 and 2020. Reproduction issues had the highest culling frequencies during fall (24.54%), winter (24.02%), and spring (22.51%), while health issues were the most frequent (22.51%) culling reason in the summer season. Health issues (25.50%) and milk production (27.71%) were the most frequent culling reasons in the provinces of Quebec and Ontario, respectively. Reproductive issues showed the highest frequency across climates based on the Köppen climate classification, except for Csb (Dry-summer subtropical or Mediterranean climate) and Bsk (Middle latitude steppe climate), which correspond to small regions in Canada, where production was the most frequent culling reason (29.42% and 21.56%, respectively). Reproductive and milk performance issues were the two main culling reasons in most ecozones, except in Boreal Shield and Atlantic Marine, where health issues had the highest frequencies (25.12 and 23.75%, respectively). These results will contribute to improving management practices and selective decisions to reduce involuntary culling of Holstein cows.

show abstract

Impact of Censored or Penalized Data in the Genetic Evaluation of Two Longevity Indicator Traits Using Random Regression Models in North American Angus Cattle

Cited by 5 publications

References 35 publications

Handling Censoring and Censored Data in Survival Analysis: A Standalone Systematic Literature Review

Handling Censoring and Censored Data in Survival Analysis: A Standalone Systematic Literature Review

Alternative measures to evaluate the accuracy and bias of genomic predictions with censored records

A comprehensive characterization of longevity and culling reasons in Canadian Holstein cattle based on various systematic factors

Contact Info

Product

Resources

About