Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "covariates" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Territorial variation in mortality from causes amenable to medical care in Poland
Autorzy:
Wróblewska, Wiktoria
Powiązania:
https://bibliotekanauki.pl/articles/990859.pdf
Data publikacji:
2017
Wydawca:
Instytut Medycyny Wsi
Tematy:
amenable mortality
spatial variations
socioeconomic covariates
health care resources
multilevel modelling
Opis:
Introduction and objective. This study examines the geographical variation of amenable mortality in Poland, focusing primarily on the role of health care resources at the level of administrative districts and regions, and selected area socioeconomic characteristics as explanatory factors. The concept was used of amenable mortality, based on the assumption that deaths from certain causes should not occur in the presence of timely and effective health care. Materials and method. Standardized death rates (SDR) from causes considered amenable to health care and, separately, for ischaemic heart disease (IHD), were calculated for each of 379 districts (NUTS 4 level) in Poland in 1991–1995 and 2006–2010, using unit mortality data from the National Causes of Death Register. The analytical procedure involved spatial analysis of the distribution of amenable mortality rates, selection of explanatory variables and fitting multilevel regression models using area-level and regional-level characteristics. Results. The results indicate that mortality from conditions which have become amenable to medical intervention has generally decreased in all districts of Poland in the past two decades. Considerable territorial variation in mortality can be observed. Since the 1990s, these differences have been reduced for IHD-related mortality and have increased for amenable mortality. Conclusions. The presented analysis only partly confirms the correlation between variables reflecting the infrastructure of health care resources and the territorial variation in mortality from these two categories of causes of death. Significant correlations with variation in mortality are revealed for the number of primary care physicians (at district level) and the number of specialist practitioners (at regional level). However, after controlling for socioeconomic variables, such as education and low income, the effect of the health care infrastructure-related variables was considerably reduced. The multi-level models also revealed a substantial variation at the regional level, which implies that there are other unobserved contextual influences on amenable mortality at this level.
Źródło:
Annals of Agricultural and Environmental Medicine; 2017, 24, 3
1232-1966
Pojawia się w:
Annals of Agricultural and Environmental Medicine
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analyzing randomized controlled interventions: Three notes for applied linguists
Autorzy:
Vanhove, Jan
Powiązania:
https://bibliotekanauki.pl/articles/780998.pdf
Data publikacji:
2015-03-01
Wydawca:
Uniwersytet im. Adama Mickiewicza w Poznaniu
Tematy:
randomized experiments
cluster randomization
pretest-postest designs
covariates
mixed-effects modeling
Opis:
I discuss three common practices that obfuscate or invalidate the statistical analysis of randomized controlled interventions in applied linguistics. These are (a) checking whether randomization produced groups that are balanced on a number of possibly relevant covariates, (b) using repeated measures ANOVA to analyze pretest-posttest designs, and (c) using traditional significance tests to analyze interventions in which whole groups were assigned to the conditions (cluster randomization). The first practice is labeled superfluous, and taking full advantage of important covariates regardless of balance is recommended. The second is needlessly complicated, and analysis of covariance is recommended as a more powerful alternative. The third produces dramatic inferential errors, which are largely, though not entirely, avoided when mixed-effects modeling is used. This discussion is geared towards applied linguists who need to design, analyze, or assess intervention studies or other randomized controlled trials. Statistical formalism is kept to a minimum throughout.
Źródło:
Studies in Second Language Learning and Teaching; 2015, 5, 1; 135-152
2083-5205
2084-1965
Pojawia się w:
Studies in Second Language Learning and Teaching
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies