Applying the Hájek Approach in Formula-Based Variance Estimation. Research Report. ETS RR-17-24

Autor/in	Qian, Jiahe
Titel	Applying the Hájek Approach in Formula-Based Variance Estimation. Research Report. ETS RR-17-24
Quelle	In: ETS Research Report Series, (2017), (16 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2330-8516
Schlagwörter	Mathematical Formulas; Computation; Sampling; Research Design; Probability; Monte Carlo Methods; Comparative Analysis; National Competency Tests; National Assessment of Educational Progress + Suchen Sie Ihr Suchwort? Mathematische Formel; Forschungsdesign; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Monte-Carlo-Methode
Abstract	The variance formula derived for a two-stage sampling design without replacement employs the joint inclusion probabilities in the first-stage selection of clusters. One of the difficulties encountered in data analysis is the lack of information about such joint inclusion probabilities. One way to solve this issue is by applying Hájek's approximation of the joint probabilities in variance estimation. To assess the Hájek approach, several estimators of Hájek's "c" and "d" are proposed. The application is illustrated with simulation and real data. A Monte Carlo simulation is employed to compare the results of joint inclusion probabilities yielded from the probability-proportional-to-size sampling methods with the results from Hájek's approximation. Empirically estimated variances from the jackknife procedure are also compared with the formula-based variances with incorporated Hájek's approximation. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01