General Multi-Level Modeling with Sampling Weights
By T. Asparouhov. 2006
295 citations recorded by the source corpus.
Subfields: Analytical Chemistry, Control and Systems Engineering, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/8df0ee40f53a78bf1d2ddc322b6b72541d2c9fcb
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In Analytical Chemistry
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Citations in the corpus
- lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models (2014, methodology): “…literature: adjustment of the weights or sample size to an effective sample size (Stapleton 2002), pseudo-maximum likelihood (Muth´en and Satorra 1995; Asparouhov 2005, 2006), and weighted least squares estimation (Skinner et al. 1989, p. 86); see Stapleton (2006) for an overview of these…”
- Observations on the Use of Growth Mixture Models in Psychological Research (2007, methodology): “Those samples that could be described as probability samples, were complex probability samples, but in no case were probability weights used in the analysis (nor was the complex design tested for informativeness to justify omitting the weights; Asparouhov, 2006).”
- Classroom Assessment Practices, Teacher Judgments, and Student Achievement in Mathematics: Evidence from the ECLS (2009, background): “…and thus the properties of the variance parameter estimates for cross-level interactions obtained from weighted multilevel models were thus unknown (Asparouhov, 2006). taking more than 2.5 mathematics teaching methods courses in their college training, spending about 8 hr in mathematics-related…”
- Testing Factorial Invariance in Multilevel Data: A Monte Carlo Study (2012, background): “Instead, only one single model is specified and the standard errors of the parameter estimates are adjusted for the complexity of sampling ( Asparouhov, 2005 , 2006 ).”
- “Mom, dad, look at me”: The development of the Parental Phubbing Scale (2020, methodology): “Thus, we opted for a design-based approach (Kim et al., 2012; “complex” analysis type), which allows for invariance testing, adjusting the chi-square statistic and standard errors (Asparouhov, 2006).”
- Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd Edition) (2013, methodology): “Finally, the chapter concludes with a series of empirical examples demonstrating differences (and ways to compare such differences; e.g., Asparouhov, 2006) in parameter estimation based on design-based (weighted) and model-based (unweighted) analyses of data, and general considerations of creating…”