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Adjusted for complex sampling design.
Standard statistical regression methods often fail to account for complex sampling designs, which may lead to severely biased estimators of model coefficients.
Regression analyses adjust for complex sampling design and compare easy firearm access at home among conservative Protestant adolescents to adolescent firearm access in other religious traditions.
Commonly used statistical methods and software packages typically assume that observations are independent and identically distributed and fail to account for complex sampling designs when present.
We first review general approaches that account for complex sampling designs, e.g. methods using probability weighting, and stress the need to explore the effects of the sampling design when applying logistic regression models.
Analyses for rates and proportions and logistic regression for complex sampling design is carried out examining the associations between mental health problems and substance use controlling for socio-demographic and behavioral variables.
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While Shotgun Protein Sequencing was shown to work well for low-complexity samples it remains unclear how it will scale up for complex samples.
We use multilevel logit models for complex samples to disentangle industry from firm-specific effects.
Miniaturized sample preparation technique for complex sample matrices has been developed with a polymer-coated fibrous extraction medium.
A multiplexed dual-secondary column comprehensive two-dimensional gas chromatography approach (GC × 2GC) designed for complex sample analysis is introduced.
These phenomena are expected from theory, but only rarely observed for complex samples such as semi-crystalline polymers.
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