INCORPORATION OF THE JACKKNIFING PROCEDURE INTO THE THREE-STAGE CLUSTER SAMPLING DESIGN IN THE ESTIMATION OF FINITE POPULATION TOTALS

2018 ◽  
Vol 54 (4) ◽  
pp. 369-379
Author(s):  
Imboga Orang’o Herbert ◽  
George Otieno Orwa ◽  
Romanus Odhiambo Otieno
Keyword(s):  
Sampling Design ◽  
Finite Population ◽  
Cluster Sampling

scholarly journals Estimation of the Number of Unemployed and Employed For Lithuanian Counties and Municipalities Using Models

2015 ◽  
Vol 54 (1) ◽  
pp. 33-44
Author(s):  
Linas Naujanis ◽  
Danutė Krapavickaitė
Keyword(s):  
Standard Deviation ◽  
Sampling Design ◽  
Finite Population ◽  
Labour Force ◽  
Parameters Estimation ◽  
Population Parameters ◽  
Model Based ◽  
Stein Estimator ◽  
Role Of Information

Problems of finite population parameters estimation are analyzed in this paper. Four methods have been used for parameterestimation: sampling design-based unbiased estimator, multiple regression and logistic regression model-based estimators and James–Stein estimator. The design-based estimator is unbiased, but its standard deviation is usually high. Model-based estimators are notunbiased, but their standard deviations are low. In order to minimize the standard deviation and the bias, the James–Stein estimator isapplied. Labour force survey data of Statistics Lithuania are used for simulation to study model-based estimators for the number ofunemployed and employed persons in districts and counties, and the role of information on registered unemployment in these models.

An optimal multivariate cluster sampling design

2019 ◽  
Vol 49 (24) ◽  
pp. 6121-6128
Author(s):  
M. G. M. Khan ◽  
Mahmood A. Rashid ◽  
Sushita Sharma
Keyword(s):  
Sampling Design ◽  
Cluster Sampling ◽  
Multivariate Cluster

Cessation of E-Cigarette Use Among Adolescents and Its Associated Factors

2019 ◽  
Vol 31 (7_suppl) ◽  
pp. 53S-60S ◽  
Author(s):  
Thamil Arasu Saminathan ◽  
Wan Shakira Rodzlan Hasani ◽  
Tania Gayle Robert Lourdes ◽  
Muhammad Fadhli Mohd Yusoff ◽  
Hasimah Ismail ◽  
...  
Keyword(s):  
Associated Factors ◽  
Sampling Design ◽  
Multiple Logistic Regression Analysis ◽  
Cross Sectional Study ◽  
Cluster Sampling ◽  
Cigarette Use ◽  
Sectional Study ◽  
Cross Sectional ◽  
Complex Sampling ◽  
Complex Sampling Design

We assessed the prevalence of cessation of e-cigarette and its associated factors among adolescents in Malaysia. This study analyzed data from the Tobacco and E-Cigarette Survey among Malaysian Adolescent (TECMA) in 2016, a cross-sectional study with 2-stage stratification cluster sampling. A total of 14 832 school-going adolescents aged 10 to 19 years participated in this survey. A complex sampling design and multiple logistic regression analysis were applied. Nearly half of the adolescents (49.9%; 95% confidence interval [CI] = 44.9-55.0) who had ever used e-cigarette ceased the usage. Based on multivariate analysis, adolescents were more likely to quit e-cigarette because they could not afford the e-cigarette (adjusted odds ratio [aOR] = 2.39, 95% CI = 1.78-3.20), if they are aged 13 year and older (aOR = 1.80, 95% CI = 1.25-2.61), and those who claimed their e-cigarette does not contain nicotine (aOR = 1.35, 95% CI = 1.03-1.78). E-cigarette prevention efforts among adolescents could consider the cessation factors described in this study.

scholarly journals A National Baseline Prevalence Survey of Schistosomiasis in the Philippines Using Stratified Two-Step Systematic Cluster Sampling Design

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Lydia Leonardo ◽  
Pilarita Rivera ◽  
Ofelia Saniel ◽  
Elena Villacorte ◽  
May Antonnette Lebanan ◽  
...  
Keyword(s):  
Intervention Program ◽  
Sampling Design ◽  
National Level ◽  
The Philippines ◽  
Cluster Sampling ◽  
Prevalence Survey ◽  
Food Borne ◽  
Two Phases ◽  
Low Prevalence ◽  
Systematic Cluster

For the first time in the country, a national baseline prevalence survey using a well-defined sampling design such as a stratified two-step systematic cluster sampling was conducted in 2005 to 2008. The purpose of the survey was to stratify the provinces according to prevalence of schistosomiasis such as high, moderate, and low prevalence which in turn would be used as basis for the intervention program to be implemented. The national survey was divided into four phases. Results of the first two phases conducted in Mindanao and the Visayas were published in 2008. Data from the last two phases showed three provinces with prevalence rates higher than endemic provinces surveyed in the first two phases thus changing the overall ranking of endemic provinces at the national level. Age and sex distribution of schistosomiasis remained the same in Luzon and Maguindanao. Soil-transmitted and food-borne helminthes were also recorded in these surveys. This paper deals with the results of the last 2 phases done in Luzon and Maguindanao and integrates all four phases in the discussion.

A Test of Cluster Sampling in Forest Inventories

1975 ◽  
Vol 5 (2) ◽  
pp. 269-272 ◽  
Author(s):  
G. M. Bonnor
Keyword(s):  
Random Sampling ◽  
Sampling Design ◽  
Simple Random Sampling ◽  
Cluster Sampling ◽  
Field Sampling ◽  
Forest Inventories ◽  
Straight Line ◽  
Time Required ◽  
Variance Estimates ◽  
The Given

During a recent pilot survey in Newfoundland, forest data were collected using a stratified, one-stage cluster-sampling design. The data were analyzed to determine if, within the stratified framework, cluster sampling would be more efficient than simple random sampling. Each cluster consisted of five point-samples located in a straight line. For the analysis, volume and variance estimates were determined from clusters of 1,2,3,4 and 5 points. During the survey, records were kept of the time required to complete various field-sampling tasks. These were used in lieu of cost data in the analysis. Results indicated that, for the given conditions, simple random sampling was more efficient than cluster sampling. However, relatively small changes in the conditions would make cluster sampling more efficient.

scholarly journals On Using Adaptive Cluster Sampling Design in Forest Inventory: It's Implication to Forest Biodiversity Status Reporting

2009 ◽  
Vol 9 (1) ◽  
pp. 56-66
Author(s):  
Dennis Peque ◽  
Keyword(s):  
Sampling Design ◽  
Systematic Sampling ◽  
Cluster Sampling ◽  
Forest Biodiversity ◽  
Adaptive Cluster Sampling ◽  
State University ◽  
Statistical Efficiency ◽  
Forest Reserve ◽  
Sparse Population ◽  
Combined Data

This paper presents adaptive cluster sampling (ACS) as a method of assessing forest biodiversity. In this study, ACS was used to estimate the abundance of ecologically sparse population of Diospyros philippinensis (Desrousseaux) within the Visayas State University Forest Reserve. Its statistical efficiency were analyzed by comparing them to the conventional systematic sampling (Syst) estimator. Results indicated that adaptive cluster sampling (ACS) plots captured more trees into the sample compared to systematic sampling (Syst) plots. In addition, ACS estimates for mean and total numbers of individuals per ha was higher than systematic sampling estimates and in terms of variance ACS gave substantially lower variance than systematic sampling. However, the ratio of the adjusted SE of ACS to the adjusted SE of systematic sampling for each species and the combined data of the two species was generally lesser than 1 which means that ACS was not a better design than systematic sampling.

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