Results 41 to 50 of about 3,863,679 (333)

How to capitalize on a priori contrasts in linear (mixed) models: A tutorial [PDF]

open access: yesJournal of Memory and Language, 2018
Factorial experiments in research on memory, language, and in other areas are often analyzed using analysis of variance (ANOVA). However, for effects with more than one numerator degrees of freedom, e.g., for experimental factors with more than two ...
D. Schad   +3 more
semanticscholar   +1 more source

A review of R-packages for random-intercept probit regression in small clusters

open access: yesFrontiers in Applied Mathematics and Statistics, 2016
Generalized Linear Mixed Models (GLMMs) are widely used to model clustered categorical outcomes. To tackle the intractable integration over the random effects distributions, several approximation approaches have been developed for likelihood-based ...
Haeike Josephy, Tom Loeys, Yves Rosseel
doaj   +1 more source

Prediction of genetic gains with selection between and within S2 progenies of papaya using the REML/Blup analysis [PDF]

open access: yesPesquisa Agropecuária Brasileira, 2017
: The objective of this work was to predict the genetic gains with selection of superior individuals within papaya (Carica papaya) progenies using the REML/Blup analysis.
Tamiris Pereira da Silva   +2 more
doaj   +1 more source

Mixed Shock Models

open access: yesBernoulli, 2001
The author studies system lifetimes that are associated with a cumulative shock model as follows: The system fails when the cumulative damage exceeds some threshold, or when a single large shock occurs. \textit{H. Li} and the reviewer [Stochastic Processes Appl. 58, No. 2, 205-216 (1995; Zbl 0833.60088); Appl. Probab. 34, No.
openaire   +2 more sources

Do Non-Cognitive Skills Produce Heterogeneous Returns Across Different Wage Levels Amongst Youth Entering the Workforce? A Quantile Mixed Model Approach

open access: yesEconomies
This study estimates the labor market returns to non-cognitive skills among the youth under 30 years old during the early career stage. Using data from the Russian Longitudinal Monitoring Survey (RLMS-HSE) for 2016 and 2019, it examines the effects of ...
Garen Avanesian
doaj   +1 more source

Half-Normal Plots and Overdispersed Models in R: The hnp Package

open access: yesJournal of Statistical Software, 2017
Count and proportion data may present overdispersion, i.e., greater variability than expected by the Poisson and binomial models, respectively. Different extended generalized linear models that allow for overdispersion may be used to analyze this type of
Rafael A Moral   +2 more
doaj   +1 more source

Genotypic superiority of Psidium Guajava S1 families using mixed modeling for truncated and simultaneous selection

open access: yesScientia Agricola, 2020
: The purpose of this study was to conduct selection, genetic parameter estimation, and prediction of genetic values for 18 S1 families of guava trees using mixed model methodology and simultaneous selection of traits by means of the additive selection ...
Moisés Ambrósio   +7 more
doaj   +1 more source

Genetic parameters of traits at the juvenile stage of different assai palm tree progenies [PDF]

open access: yesPesquisa Agropecuária Brasileira, 2018
: The objective of this work was to estimate genetic parameters of traits at the juvenile stage of different assai palm (Euterpe oleracea) tree progenies, as well as to select among and within the most promising for fruit production.
Patricia Cardoso Andrade Navegantes   +2 more
doaj   +1 more source

Accounting for Population Structure and Phenotypes From Relatives in Association Mapping for Farm Animals: A Simulation Study

open access: yesFrontiers in Genetics, 2021
Population structure or genetic relatedness should be considered in genome association studies to avoid spurious association. The most used methods for genome-wide association studies (GWAS) account for population structure but are limited to genotyped ...
Enrico Mancin   +5 more
doaj   +1 more source

Nonlinear quantile mixed models

open access: yes, 2019
In regression applications, the presence of nonlinearity and correlation among observations offer computational challenges not only in traditional settings such as least squares regression, but also (and especially) when the objective function is non ...
Geraci, Marco
core   +1 more source

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