Search results for "otanta"

Jyväskyläläisten kotitalouksien kaupan valinta ja otanta-asetelman vaikutus tuloksiin

2000

Bayesian Modeling of Sequential Discoveries

2022

We aim at modelling the appearance of distinct tags in a sequence of labelled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarised via accumulation curves, which count the number of distinct entities observed in an increasingly large set of objects. We propose a novel Bayesian method for species sampling modelling by directly specifying the probability of a new discovery, therefore allowing for flexible specifications. The asymptotic behavior and finite sample properties of such an approach are extensively studied. Interestingly, our enlarged class of sequential processes includes highly tr…

Assessing physical performance and physical activity in large population-based aging studies: home-based assessments or visits to the research center?

2019

Abstract Background The current study aims to compare correlations between a range of measures of physical performance and physical activity assessing the same underlying construct in different settings, that is, in a home versus a highly standardized setting of the research center or accelerometer recording. We also evaluated the selective attrition of participants related to these different settings and how selective attrition affects the associations between variables and indicators of health, functioning and overall activity. Methods Cross-sectional analyses comprising population-based samples of people aged 75, 80, and 85 years living independently in Jyväskylä, Finland. The AGNES stud…

Mikä virhemarginaali?

2015

Recommendations for design and analysis of health examination surveys under selective non-participation

2019

Background The decreasing participation rates and selective non-participation peril the representativeness of health examination surveys (HESs). Methods Finnish HESs conducted in 1972–2012 are used to demonstrate that survey participation rates can be enhanced with well-planned recruitment procedures and auxiliary information about survey non-participants can be used to reduce selection bias. Results Experiments incorporated to pilot surveys and experience from previously conducted surveys lead to practical improvements. For example, SMS reminders were taken as a routine procedure to the Finnish HESs after testing their effect on a pilot study and finding them as a cost-effective way to inc…

Optimal sample allocation conditioned on a small area model, estimator, and auxiliary data

2018

We have studied optimal sample allocation, associated with small area estimation, when the objective is to obtain as accurate estimates as possible, for the population and for the subpopulations, called as areas here. It is a question of a two-level optimization problem. The basic premise is composed of planned areas, stratified sampling, and small overall sample size predetermined by restricted time and budget resources. Low sample sizes are common in market surveys. During this thesis, we have developed new allocation methods, based on a small area model, estimator, and auxiliary data. The final method, the three-term Pareto allocation, is based on the three terms of the mean-squared erro…

Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

2020

We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the MCMC typically operates on the hyperparameters, and the subsequent weighting may be based on IS or sequential Monte Carlo (SMC), but allows for multilevel techniques as well. The IS approach provides a natural alternative to delayed acceptance (DA) pseudo-marginal/particle MCMC, and has many advantages over DA, including a straightforward parallelisation and additional flexibility in MCMC implementation. We detail minimal conditions which ensure strong consistency of the sug…

Sensitivity of bipartite network analyses to incomplete sampling and taxonomic uncertainty

2023

Bipartite network analysis is a powerful tool to study the processes structuring interactions in ecological communities. In applying the method, it is assumed that the sampled interactions provide an accurate representation of the actual community. However, acquiring a representative sample may be difficult as not all species are equally abundant or easily identifiable. Two potential sampling issues can compromise the conclusions of bipartite network analyses: failure to capture the full range of interactions (sampling completeness) and use of a taxonomic level higher than species to evaluate the network (taxonomic resolution). We asked how commonly used descriptors of bipartite antagonisti…