1,354,599 research outputs found
Alessio Farcomeni and Marco Geraci's contribution to the 'First Discussion Meeting on Statistical Aspects of the Covid-19 Pandemic'
No full textRecapture models under equality constraints for the conditional capture probabilities
No full textWe introduce a general class of capture-recapture models in which capture probabilities depend on capture history. We discuss constrained versions of the saturated model based on equality constraints. Inference can be performed through a simple estimating equation. The approach is illustrated on a dataset concerning Great Copper butterflies in Willamette Valley of Oregon. Copyright 2011, Oxford University Press.
Fully general Chao and Zelterman estimators with application to a whale shark population
No full textWe introduce generalized Chao (GC) and Zelterman (GZ) estimators which include
individual, time-varying and behavioural effects. Under mild assumptions in the presence of unobserved
heterogeneity, the GC estimator asymptotically provides a lower bound for the population
size, and is unbiased otherwise. Corrected versions guarantee bounded estimates. In order to
include the best set of predictors we propose a biased empirical Focused Information Criterion
(bFIC). Simulations indicate that bFIC might give considerable improvements over other selection
criteria in our context. We illustrate with an original application to size estimation of a whale shark
(Rhincodon typus) population in South Ari atoll, in the Maldives
A MANOVA test for multivariate lognormal observations with a spike at zero, with application to ecological niches of South Africa
No full textWe develop an asymptotic likelihood ratio test for multivariate lognormal data with a point mass at zero in each dimension. The test generalizes Wilks' lambda and Hotelling T-test to the case of semicontinuous data. Simulations show that the resulting test statistic attains the nominal Type I error rate and has good power for reasonable alternatives. We conclude with an application to exploration of ecological niches of trees of South Africa
FDR Control with Pseudo-Gatekeeping Based on a Possibly Data Driven Order of the Hypotheses
No full textWe propose a multiple testing procedure controlling the false discovery rate. The procedure is based on a possibly data driven ordering of the hypotheses, which are tested at the uncorrected level q until a suitable number is not rejected. When the order is data driven, larger effect sizes are considered first, therefore selecting more interesting hypotheses with larger probability. The proposed procedure is valid under independence for the test statistics. We also propose a modification which makes our procedure valid under arbitrary dependence. It is shown in simulation that we compare particularly well when the sample size is small. We conclude with an application to identification of molecular signatures of intracranial ependymoma. The methods are implemented in an R package (someMTP), freely available on CRAN. © 2013, The International Biometric Society
Penalized estimation in latent Markov models, with application to monitoring serum calcium levels in end-stage kidney insufficiency
No full textWe introduce a penalized likelihood form for latent Markov models. We motivate its use for biomedical
applications where the sample size is in the order of the tens, or at most hundreds, and there are only few
repeated measures. The resulting estimates never break down, while spurious solutions are often obtained
by maximizing the likelihood itself. We discuss model choice based on the Takeuchi Information Criterion.
Simulations and a real-data application to monitoring serum Calcium levels in end-stage kidney disease are
used for illustration
Generalized linear mixed models based on latent Markov heterogeneity structures
No full textWe describe a generalized linear mixed model in which all random effects may evolve
over time. Random effects have a discrete support and follow a first-order Markov chain. Con-
straints control the size of the parameter space and possibly yield blocks of time-constant random
effects. We illustrate with an application to the relationship between health education and depres-
sion in a panel of adolescents, where the random effects are highly dimensional and separately
evolve over time
Contribution to the discussion of the paper by Stefan Wellek: a critical evaluation of the current p-value controversy
No full textA likelihood ratio test for completed sampling in population size estimation studies
No full textWe propose a likelihood ratio test to assess that sampling has been completed in closed population size estimation studies. More precisely, we assess if the expected number of subjects that have never been sampled is below a user-specified threshold. The likelihood ratio test statistic has a nonstandard distribution under the null hypothesis. Critical values can be easily approximated and tabulated, and they do not depend on model specification. We illustrate in a simulation study and three real data examples, one of which involves ascertainment bias of amyotrophic lateral sclerosis in Gulf War veterans
A two component Weibull mixture to model early and late mortality in a Bayesian framework
No full textA two-component parametric mixture is proposed to model survival after an invasive
treatment, when patients may experience different hazards regimes: a risk of early
mortality directly related to the treatment and/or the treated condition, and a risk of late
death influenced by several exogenous factors. The parametric mixture is based on Weibull
distributions for both components. Different sets of covariates can affect the Weibull scale
parameters and the probability of belonging to one of the two latent classes. A logarithmic
function is used to link explanatory variables to scale parameters while a logistic link is
assumed for the probability of the latent classes. Inference about unknown parameters is
developed in a Bayesian framework: point and interval estimates are based on posterior
distributions, whereas the Schwarz criterion is used for testing hypotheses. The advantages
of the approach are illustrated by analyzing data from an aorta aneurysm study
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