Results 251 to 260 of about 566,338 (299)

Pooled Multinomial Logistic Regression for Parametric G-computation in the Presence of Competing Events. [PDF]

Epidemiology
Neuroth LM, Swilley-Martinez ME, Zivich PN, Edwards JK, Edwards JK.   +4 more
europepmc   +1 more source

Applying a hypothetical strategy to the intercurrent event of non-adherence with the parametric g-formula: a post hoc secondary analysis of the MET-PREVENT randomised controlled trial. [PDF]

Trials
Hiu S, Wilson N, Wilson K, Lin N, Witham MD, Wason JMS, M. E. T.-PREVENT Study Group.   +6 more
europepmc   +1 more source

The value of multi-parametric ultrasonography nomogram in predicting nipple-areolar complex involvement in breast cancer. [PDF]

Quant Imaging Med Surg
Ma Y, Tang S, Zhang J, Ma Y, Lian Q, Jin C, Lu J, Zhou P.   +7 more
europepmc   +1 more source

Translation, cross-cultural adaptation, and validation of the Turkish version of the Hospital for Special Surgery Anterior Cruciate Ligament Postoperative Satisfaction Survey. [PDF]

Medicine (Baltimore)
Sayer G, Pehlivan M, Akpinar Y, Golgelioglu F, Kazez M, Misir A.   +5 more
europepmc   +1 more source

A Parametric Bootstrap for the Mean Measure of Divergence [PDF]

International Journal of Biostatistics, 2020
Abstract For more than 50 years the Mean Measure of Divergence (MMD) has been one of the most prominent tools used in anthropology for the study of non-metric traits. However, one of the problems, in anthropology including palaeoanthropology (more often there), is the lack ...
Federico Zertuche
exaly   +4 more sources

Some of the next articles are maybe not open access.

Related searches:

On Parametric Bootstrapping and Bayesian Prediction

Scandinavian Journal of Statistics, 2004
Abstract.  We investigate bootstrapping and Bayesian methods for prediction. The observations and the variable being predicted are distributed according to different distributions. Many important problems can be formulated in this setting. This type of prediction problem appears when we deal with a Poisson process.
Fushiki, Tadayoshi, Komaki, Fumiyasu, Aihara, Kazuyuki   +2 more
openaire   +2 more sources

Parametric and nonparametric bootstrap methods for meta-analysis

Behavior Research Methods, 2005
In a meta-analysis, the unknown parameters are often estimated using maximum likelihood, and inferences are based on asymptotic theory. It is assumed that, conditional on study characteristics included in the model, the between-study distribution and the sampling distributions of the effect sizes are normal.
Patrick Onghena, Wim van den Noortgate
exaly   +3 more sources

Bootstrapping Parametric Models of Mortality

Scandinavian Actuarial Journal, 2004
We consider a general problem of modeling a mortality law of a population of failing units with some parametric function. In this setting we define a mortality table of crude rates as a statistical estimator with multinomial distribution and show its consistency as well as asymptotic normality.
Grzegorz A. Rempala, Konrad Szatzschneider   +1 more
openaire   +1 more source

Parametric bootstrapping with nuisance parameters

Statistics & Probability Letters, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Young, GA, Lee, SMS
openaire   +3 more sources

Non-parametric bootstrap recycling

Statistics and Computing, 2002
The double bootstrap provides diagnostics for bootstrap calculations and, if need be, appropriate adjustments. The amount of computation involved is usually considerable, and recycling provides a less computer intensive alternative. Recycling consists of using repeatedly the same samples drawn from a recycling distribution G for estimation under each ...
openaire   +2 more sources