scholarly journals Simulation Studies for Complex Sampling Designs

2016 ◽  
Vol 35 (4) ◽  
Author(s):  
Helga Wagner ◽  
Doris Eckmair
Keyword(s):  
Simulation Study ◽  
Variance Estimation ◽  
Sampling Error ◽  
Estimation Method ◽  
Sampling Plan ◽  
Simulation Studies ◽  
Complex Surveys ◽  
Variance Estimators ◽  
Complex Sampling ◽  
Complex Sampling Designs

Choosing the appropriate variance estimation method in complex surveys is a difficult task since there exist a variety of techniques which usually cannot be compared mathematically. A relatively easy way to accomplish such a comparison is on the basis of simulation studies. Though simulation studies are widely used in statistics, they are not a standard tool for investigating properties of estimators in complex survey sampling designs. In this paper we describe the setup for a simulation study according to the sampling plan of the Austrian Microcensus (AMC), used 1994–2003 which is an example for a very complex sampling plan. To illustrate the proceeding we conducted a simulation study comparing basic variance estimators. Results of the study reveal the extent to which simple variance estimators may underestimate the true sampling error in close to reality situations.

Variance Estimation by Linearisation for the At Risk of Poverty or Social Exclusion (AROPE) Rate

2020 ◽  
Vol 49 (1) ◽  
pp. 33-44
Author(s):  
Stefan Zins
Keyword(s):  
At Risk ◽  
Social Exclusion ◽  
Variance Estimation ◽  
Simulation Studies ◽  
Important Indicator ◽  
Variance Estimators ◽  
Complex Sampling ◽  
Key Indicator ◽  
Complex Sampling Design ◽  
Data Source

The At Risk of Poverty or Social Exclusion (AROPE) Rate is the key indicator for monitoring the European Commissions 2020 Strategy poverty target. But the variance of the AROPE Rate is not straightforward to estimate. Re-sampling methods can be used, but they are difficult to adapt to complex sampling design, that are often used for the surveys that provide the data source for estimating the AROPER. The presented work fills a methodological gap by providing a linearisation of the AROPE Rate estimator that can be used with well known variance estimators and therefore facilitate the reporting of appropriate inference for this important indicator. The precision of the developed variance estimators based on linearisation is assessed via simulation studies and compared with a bootstrap variance estimator, as an alternative.

scholarly journals Analytical Modeling in Complex Surveys of Work Practices

ILR Review ◽  
2005 ◽  
Vol 59 (1) ◽  
pp. 82-100 ◽  
Author(s):  
Jerome P. Reiter ◽  
Elaine L. Zanutto ◽  
Larry W. Hunter
Keyword(s):  
Analytical Modeling ◽  
Industrial Relations ◽  
Complex Surveys ◽  
Independent Variables ◽  
Complex Sampling ◽  
Model Based ◽  
Unequal Probability ◽  
Indicator Variables ◽  
National Organizations ◽  
Complex Sampling Designs

Quantitative industrial relations research frequently relies on data collected from large surveys of establishments that use complex sampling designs, such as stratified and unequal probability sampling. The authors analyze two complex surveys of establishments, the National Organizations Survey and the National Survey of Establishments. They discuss design-based (survey-weighted) and model-based (unweighted) strategies for analyzing these data. They show that the choice of strategy can affect inferences about parameters, and hence conclusions drawn from analyses. They discuss the advantages of model-based approaches that include independent variables corresponding to design features, such as functions of size measures or indicator variables for strata or clusters, relative to purely design-based approaches.

scholarly journals L-Moments and Calibration-Based Estimators for Variance Parameter

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Malik Muhammad Anas ◽  
Muhammad Ali ◽  
Ambreen Shafqat ◽  
Faisal Shahzad ◽  
Kashif Abbass ◽  
...  
Keyword(s):  
Simulation Study ◽  
Random Sampling ◽  
Variance Estimation ◽  
Extreme Values ◽  
Natural Sciences ◽  
Stratified Random Sampling ◽  
Variance Estimators ◽  
Highly Efficient ◽  
L Moments ◽  
The Subject

The subject of variance estimation is one of the most important topics in statistics. It has been clarified by many different research studies due to its various applications in the human and natural sciences. Different variance estimators are built based on traditional moments that are especially influenced by the existence of extreme values. In this paper, with the presence of extreme values, we proposed some new calibration estimators for variance based on L-moments under double-stratified random sampling. A simulation study with COVID-19 data is performed to evaluate the efficiency of the proposed estimators. All results indicate that the proposed estimators are often superior and highly efficient compared to the existing traditional estimator.

scholarly journals An Approximate Point-based Alternative for the Estimation of Variance under Big BAF Sampling

2020 ◽  
Author(s):  
Thomas B. Lynch ◽  
Jeffrey H Gove ◽  
Timothy G Gregoire ◽  
Mark J Ducey
Keyword(s):  
Forest Inventory ◽  
Variance Estimation ◽  
Basal Area ◽  
Simulation Studies ◽  
Variance Estimator ◽  
Forest Types ◽  
Variance Estimators ◽  
Computer Simulation Studies ◽  
New Formula ◽  
Estimation Of Variance

Abstract BackgroundA new variance estimator is derived and tested for big BAF (Basal Area Factor) sampling which is a forest inventory system that utilizes two BAF sizes, a small BAF for tree counts and a larger BAF on which tree measurements are made usually including \dbh s and heights needed for volume estimation.MethodsThe new estimator is derived using the \Dm\ from an existing formulation of the big BAF estimator as consisting of three sample means. The new formula is compared to existing big BAF estimators including a popular estimator based on Bruce's formula.ResultsSeveral computer simulation studies were conducted comparing the new variance estimator to all known variance estimators for big BAF currently in the forest inventory literature. In simulations the new estimator performed well and comparably to existing variance formulas.ConclusionsA possible advantage of the new estimator is that it does not require the assumption of negligible correlation between basal area counts on the small BAF factor and volume-basal area ratios based on the large BAF factor selection trees, an assumption required by all previous big BAF variance estimation formulas. Although this correlation was negligible on the simulation stands used in this study, it is conceivable that the correlation could be significant in some forest types, such as those in which the \dbh-height relationship can be affected substantially by density perhaps through competition. We also mathematically derived expressions for bias in the big BAF estimator that can be used to show the bias approaches zero in large samples on the order of 1/n where n is the number of sample points.

scholarly journals Joint adjustment by CPIII precision trigonometric elevation control network assisted with precision levelling observation

2020 ◽  
Vol 165 ◽  
pp. 03005
Author(s):  
Li Jianzhang
Keyword(s):  
Variance Estimation ◽  
Estimation Method ◽  
Parameter Method ◽  
Control Network ◽  
Network Construction

Using the precision trigonometric elevation instead of the precision levelling to build a CPⅢ elevation control network will greatly increase the speed of CPⅢ control network construction. However, the accuracy of CPIII precision trigonometric elevation control network is still difficult to reach the level of CPⅢ precision levelling network. Based on the existing parameter method, this paper introduces some precision levelling for joint adjustment, and uses Helmert’s variance estimation method to perform strict weight determination. Our experiments show that when the number of precision levelling participating in the joint adjustment exceeds 1/3 of the total number of CPⅢ precision levelling network observations, the accuracy of the CPIII precision trigonometric elevation control network can be effectively improved.

scholarly journals Sleep Duration and Waking Activities in Relation to the National Sleep Foundation’s Recommendations: An Analysis of US Population Sleep Patterns from 2015 to 2017

2021 ◽  
Vol 18 (11) ◽  
pp. 6154
Author(s):  
Michael Osei Mireku ◽  
Alina Rodriguez
Keyword(s):  
Sleep Duration ◽  
Time Use ◽  
Variance Estimation ◽  
Estimation Method ◽  
Short Sleep Duration ◽  
Weighted Estimates ◽  
American Time Use Survey ◽  
Increased Risk ◽  
The Us ◽  
Time Use Survey

The objective was to investigate the association between time spent on waking activities and nonaligned sleep duration in a representative sample of the US population. We analysed time use data from the American Time Use Survey (ATUS), 2015–2017 (N = 31,621). National Sleep Foundation (NSF) age-specific sleep recommendations were used to define recommended (aligned) sleep duration. The balanced, repeated, replicate variance estimation method was applied to the ATUS data to calculate weighted estimates. Less than half of the US population had a sleep duration that mapped onto the NSF recommendations, and alignment was higher on weekdays (45%) than at weekends (33%). The proportion sleeping longer than the recommended duration was higher than those sleeping shorter on both weekdays and weekends (p < 0.001). Time spent on work, personal care, socialising, travel, TV watching, education, and total screen time was associated with nonalignment to the sleep recommendations. In comparison to the appropriate recommended sleep group, those with a too-short sleep duration spent more time on work, travel, socialising, relaxing, and leisure. By contrast, those who slept too long spent relatively less time on each of these activities. The findings indicate that sleep duration among the US population does not map onto the NSF sleep recommendations, mostly because of a higher proportion of long sleepers compared to short sleepers. More time spent on work, travel, and socialising and relaxing activities is strongly associated with an increased risk of nonalignment to NSF sleep duration recommendations.

scholarly journals An Alternative Promotion Time Cure Model with Overdispersed Number of Competing Causes: An Application to Melanoma Data

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1815
Author(s):  
Diego I. Gallardo ◽  
Mário de Castro ◽  
Héctor W. Gómez
Keyword(s):  
Estimation Method ◽  
Selection Criterion ◽  
Likelihood Method ◽  
Simulation Studies ◽  
Cure Rate ◽  
Nested Models ◽  
Proposed Model ◽  
The Em Algorithm ◽  
Competing Causes ◽  
The One

A cure rate model under the competing risks setup is proposed. For the number of competing causes related to the occurrence of the event of interest, we posit the one-parameter Bell distribution, which accommodates overdispersed counts. The model is parameterized in the cure rate, which is linked to covariates. Parameter estimation is based on the maximum likelihood method. Estimates are computed via the EM algorithm. In order to compare different models, a selection criterion for non-nested models is implemented. Results from simulation studies indicate that the estimation method and the model selection criterion have a good performance. A dataset on melanoma is analyzed using the proposed model as well as some models from the literature.

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