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Variable selection–a review and recommendations for the practicing statistician
Statistical models support medical research by facilitating individualized outcome
prognostication conditional on independent variables or by estimating effects of risk factors …
prognostication conditional on independent variables or by estimating effects of risk factors …
Model averaging in ecology: A review of Bayesian, information‐theoretic, and tactical approaches for predictive inference
In ecology, the true causal structure for a given problem is often not known, and several
plausible models and thus model predictions exist. It has been claimed that using weighted …
plausible models and thus model predictions exist. It has been claimed that using weighted …
Model averaging prediction by K-fold cross-validation
This paper considers the model averaging prediction in a quasi-likelihood framework that
allows for parameter uncertainty and model misspecification. We propose an averaging …
allows for parameter uncertainty and model misspecification. We propose an averaging …
Constrained maximum likelihood-based Mendelian randomization robust to both correlated and uncorrelated pleiotropic effects
With the increasing availability of large-scale GWAS summary data on various complex traits
and diseases, there have been tremendous interests in applications of Mendelian …
and diseases, there have been tremendous interests in applications of Mendelian …
Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model
Z Lin, Y Deng, W Pan - PLoS genetics, 2021 - journals.plos.org
With the increasing availability of large-scale GWAS summary data on various traits,
Mendelian randomization (MR) has become commonly used to infer causality between a …
Mendelian randomization (MR) has become commonly used to infer causality between a …
When problem solving followed by instruction works: Evidence for productive failure
When learning a new concept, should students engage in problem solving followed by
instruction (PS-I) or instruction followed by problem solving (I-PS)? Noting that there is a …
instruction (PS-I) or instruction followed by problem solving (I-PS)? Noting that there is a …
Dose-response analysis using R
Dose-response analysis can be carried out using multi-purpose commercial statistical
software, but except for a few special cases the analysis easily becomes cumbersome as …
software, but except for a few special cases the analysis easily becomes cumbersome as …
Text preprocessing for unsupervised learning: Why it matters, when it misleads, and what to do about it
Despite the popularity of unsupervised techniques for political science text-as-data research,
the importance and implications of preprocessing decisions in this domain have received …
the importance and implications of preprocessing decisions in this domain have received …
Model averaging and its use in economics
MFJ Steel - Journal of Economic Literature, 2020 - aeaweb.org
The method of model averaging has become an important tool to deal with model
uncertainty, for example in situations where a large amount of different theories exist, as are …
uncertainty, for example in situations where a large amount of different theories exist, as are …
[KIRJA][B] Distance sampling: methods and applications
This is the fourth book dedicated to distance sampling. The first (Buckland et al. 1993)
appeared at around the same time as the first version of the Distance software (Laake et al …
appeared at around the same time as the first version of the Distance software (Laake et al …