scholarly journals Effects of Cluster Sizes on Variance Components in Two-Stage Sampling

2015 ◽  
Vol 31 (4) ◽  
pp. 763-782
Author(s):  
Richard Valliant ◽  
Jill A. Dever ◽  
Frauke Kreuter
Keyword(s):  
Sample Size ◽  
Random Effects ◽  
Variance Components ◽  
Sample Size Calculation ◽  
Household Surveys ◽  
Sample Design ◽  
Two Stage ◽  
Random Effects Models ◽  
Standard Software ◽  
The U.S

Abstract Determining sample sizes in multistage samples requires variance components for each stage of selection. The relative sizes of the variance components in a cluster sample are dramatically affected by how much the clusters vary in size, by the type of sample design, and by the form of estimator used. Measures of the homogeneity of survey variables within clusters are related to the variance components and affect the numbers of sample units that should be selected at each stage to achieve the desired precision levels. Measures of homogeneity can be estimated using standard software for random-effects models but the model-based intracluster correlations may need to be transformed to be appropriate for use with the sample design. We illustrate these points and implications for sample size calculation for two-stage sample designs using a realistic population derived from household surveys and the decennial census in the U.S.

Dealing with Inaccurate Measures of Size in Two-Stage Probability Proportional to Size Sample Designs: Applications in African Household Surveys

2020 ◽  
Author(s):  
Graham Kalton ◽  
Ismael Flores Cervantes ◽  
Carlos Arieira ◽  
Mike Kwanisai ◽  
Elizabeth Radin ◽  
...  
Keyword(s):  
Final Stage ◽  
Population Based ◽  
Equal Probability ◽  
Household Surveys ◽  
Sample Design ◽  
African Countries ◽  
Two Stage ◽  
Fixed Sample ◽  
Multi Stage ◽  
Weighting Adjustments

Abstract The units at the early stages of multi-stage area samples are generally sampled with probabilities proportional to their estimated sizes (PPES). With such a design, an overall equal probability (EP) sample design would yield a constant number of final stage units from each final stage cluster if the measures of size used in the PPES selection at each sampling stage were directly proportional to the number of final stage units. However, there are often sizable relative differences between the measures of size used in the PPES selections and the number of final stage units. Two common approaches for dealing with these differences are: (1) to retain a self-weighting sample design, allowing the sample sizes to vary across the sampled primary sampling units (PSUs) and (2) to retain the fixed sample size in each PSU and to compensate for the unequal selection probabilities by weighting adjustments in the analyses. This article examines these alternative designs in the context of two-stage sampling in which PSUs are sampled with PPES at the first stage, and an equal probability sample of final stage units is selected from each sampled PSU at the second stage. Two-stage sample designs of this type are used for household surveys in many countries. The discussion is illustrated with data from the Population-based HIV Impact Assessment surveys that were conducted using this design in several African countries.

Improved $U$-tests for variance components in one-way random effects models

2020 ◽  
Vol 34 (3) ◽  
pp. 464-477
Author(s):  
Juvêncio Santos Nobre ◽  
Julio M. Singer ◽  
Maria J. Batista
Keyword(s):  
Random Effects ◽  
Variance Components ◽  
Random Effects Models

Sample Size Estimation for Random-effects Models

Epidemiology ◽  
2017 ◽  
Vol 28 (6) ◽  
pp. 817-826 ◽  
Author(s):  
Scott Weichenthal ◽  
Jill Baumgartner ◽  
James A. Hanley
Keyword(s):  
Sample Size ◽  
Random Effects ◽  
Sample Size Estimation ◽  
Size Estimation ◽  
Random Effects Models

scholarly journals CONSIDERING VARIANCES OF QUASI-RANDOM EFFECTS IN RELATIVE GPS POSITIONING PERFORMED DURING DAYTIME AND NIGHTTIME PERIODS – A NOVEL TWO-STAGE APPROACH

2021 ◽  
Vol 47 (1) ◽  
pp. 27-33
Author(s):  
Darko Anđić
Keyword(s):  
Random Effects ◽  
Joint Action ◽  
Variance Components ◽  
Near Field ◽  
Two Stage ◽  
Factor B ◽  
Gps Positioning ◽  
Antenna Phase ◽  
Antenna Phase Center ◽  
Relative Gps Positioning

In this paper, a new two-stage approach, involving an integral treatement of all quasi-random effects limiting the accuracy of relative GPS positioning and the method of moments to obtain final variance components regarding the effects of short-term (“far-field”) multipath (factor b), joint action of long-term (“near-field”) multipath and receiver antenna phase center offset and variations (factor a1), as well as joint action of tropospheric and ionospheric refraction (factor a2), is presented. In the study, GPS data collected on five baselines were used. Variance components of the quasirandom effects were obtained for the three relative GPS coordinates (e, n and u) using individually monthly datsets including daytime- and those including nighttime-wise ambiguity-fixed baseline solutions. The related results show that statistically significant inequality exists when comparing corresponding variances obtained for daytime and nighttime periods. It turned out that the following standard deviation estimates intervals are present (by the coordinates e, n and u, respectively): (a) daytime period: 3.3–6.9, 4.6–9.0 and 9.1–20.3 mm (factor b); 1.5–4.7, 1.9–7.0 and 3.4–21.9 mm (factor 1a ); 0.0116– 0.3282, 0.0103–0.2365 and 0.1222–0.7818 mm/km (factor a2); (b) nighttime period: 3.2–4.9, 4.7–7.3 and 8.4–15.4 mm (factor b); 0.8–3.8, 2.1–5.0 and 3.1–15.8 mm (factor a1); 0.0118–0.2734, 0.0097–0.2289 and 0.0752–0.6315 mm/km (factor a2).

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