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Thus, if a variable with missing data is continuous, then a normal model is used.
Both a normal model and a diseased model with BO obstruction were developed for experimentation.
Anatomical datasets for biomechanical analysis of an orthopaedic intervention usually describe the anatomy of a normal model, from which surgical manipulation of muscles and the corresponding biomechanical effect can be calculated [20, 23].
This study provides a normal model of cat Muc1 pattern expression as a starting point to evaluate and compare the expression of this epithelial mucin in pathological feline tissues.
Briefly, we first calculated QTL genotype probabilities, conditional on the available marker data ("calc.genoprob" function), and then used Haley-Knott regression ("scanone" function) to perform single-QTL genome scans with a normal model [60].
Covariances cov(V i, V j) can be estimated using a normal model as follows.
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We tested two models on a transformation of cost: a Log Normal model and a Square-root Normal model, and three generalized linear models on untransformed cost, defined by distributional assumption and link function: Normal with identity link (OLS); Gamma with log link; and Gamma with square-root link.
We carried out a meta-analysis to estimate sensitivity and specificity of rapid tests, using a bivariate normal model with a complementary log-log link function.
We also compare this 4-component normal mixture model to two competitors from the existing literature: a contaminated normal model and a 2-component normal mixture model.
This approach allows the detection of heterogeneity in birthweight that cannot be found with a contaminated normal model or a 2-component normal mixture model.
Thus, the present framework can reveal heterogeneity in birthweight that is undetectable via a contaminated normal model or a 2-component normal mixture model.
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