• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.7-15
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• 2006

A large sample can Provide more information about the Population. As the sample size Increases, analysts will be more confident about the survey results. On the other hand, the costs for survey will increase in time and manpower. Therefore, determination of the sample size is a trade-off between the required accuracy and the cost. In addition, permitted error and significance level should be considered. Sample size determination in surveys for O/D estimation is also connected with confidence of survey result. However, the past methods were usually too simple to consider confidence. Therefore, a new method for O/D surveys was Proposed and it was accurate enough, but it has too large sample size when we have current budget constraint. In this research, several minimum sample size determination methods for origin-destination survey under budget constraint were proposed. Each method decreased sample size, but has its own advantages. Selection of the sample size will depend on the study Purpose and budget constraint.

• Survey Research
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• v.6 no.1
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• pp.39-62
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• 2005

In this paper we investigate some concepts frequently called in sample surveys such as 'representative of sample' as well as 'consistency', 'unbiasedness', and 'efficiency' in estimation. The first is strongly related with sampling procedure including coverage rate of survey population, response rate in establishment survey, and recruit rate of final samples. The others, however, are concerned with both sampling design and corresponding estimators simultaneously. Whereas both consistency and unbiasedness are based on the representative sample, efficiency does not depend on the representative sample. The representative of sample can be increased by raising the rate of coverage, response and recruit as well. Consistency may be investigated according to variables of interest and auxiliary variables. The well-known raing-ratio weighting method is a method to increase consistency of auxiliary variables by means of matching population size in each cell. Efficiency is not directly related with the representative of sample, and allocation methods such as proportional and Neyman allocation in stratified sampling and post-stratification are all methods to increase the efficiency of estimation under the condition of satisfying the representative of sample.

• Journal of Nutrition and Health
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• v.17 no.3
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• pp.236-241
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• 1984

In order to make clear the relationship between sample design and sample survey in community, it was conducted research on sample design for National Nutrition Survey in 1983. In this paper it was tried to analize the data based on The Report of a Settled Population, 1981 conducted by National Bureau of Statistics Economic Planning Board. The sample was basically using stratified two-stage sampling with systematic sampling of Ban or Li as administrative unit. The population represents the whole nation excluding Jeju-do because of budget. The selection of sampling unit and sampling procedure was as follows. 1) Stratify the nation-wide area in 20 sections according to administrative districts. 2) Determine the sample size in each section according to equal proportional rate (1 / 8040) and to about 1,000 households in the sample. 3) Select the 25 sampling units by section according to households proportion. 4) Select the 10 households at random from each Ban or Li according to equal probability proportion as the final sampling unit. Using the procedure, it was sampled 1,000 households for National Nutrition Survey in 1983.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.27-41
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• 2005

We made a new sample design for intestinal parasitic infection survey in 2004. We used the 10% sample survey data of 2000 population and housing census as a survey population. Since the infection rates of intestinal parasitics are very low, we applied the relative risk and odds ratio instead of ordinary method such as t-test to study the characteristics from the 1997 survey data. In order to allocate samples to stratum, we used the compromise of Neyman allocation which is the average of three Neyman allocations. And also, we derive estimators and variance estimators of the estimators.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.375-382
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• 2001

The agricultural machine estimated sales survey is a survey to estimate annual sales quantities of eight major agricultural machines such as tracter, combine, etc. The purpose of this study is to design a multipurpose sample for the agricultural machine estimated sales survey. Main achievements of this study are to present an efficient stratification criterion and to suggest a reasonable estimation method by using the concept of post-stratification.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.587-597
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• 2018

Procedures, such as sampling technique, survey method, and questionnaire preparation, are required in order to obtain sample data in accordance with the purpose of a survey. An important procedure is the decision of the sample size formula. The sample size formula is determined by setting the target error and total cost according to the sampling method. In this paper, we propose a sample size formula using population changes over time, estimation error of the previous time and response rate of past data when the target error and the expected response rate are given in the simple random sampling. In actual research, we use estimators that apply complex weights in addition to design-based weights. Therefore, we induce a sample size formula for estimators using design-based weights and nonresponse adjustment coefficients, that can be a formula that reflects differences in response rates when survey methods are changed over time. In addition, we use simulations to compare the proposed formula with the existing sample size formula.

• Survey Research
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• v.5 no.2
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• pp.31-48
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• 2004

We collected and analyzed 18 social surveys to assess the quality of samples with respect to region, gender, age-band, education level and occupation. We found in our samples that highly educated people and house wives are over-represented whereas low educated people, self-employed/blue collars and white collars are under-represented. To correct such sample distortions, we applied the iterative proportional weighting or the raking to our samples. We observed sizable changes in survey results. Also, the effective sample sizes were shrunken up to 20%-40%, that could be interpreted as the necessity of larger samples to meet the claimed sampling error limits.

• Journal of Korean Society on Water Environment
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• v.31 no.6
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• pp.610-618
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• 2015

This study was conducted to find out the influence of sample size (accumulated survey areas) on the seven biological indices of benthic macroinvertebrates. BMI, the index similar to Zeilika-Marvan’s saprobic index, tended to be independent on the variations of sample size. The other indices (Shannon-Weaver’s diversity, Margalef’s richness, Menhinick’s richness, Pielou’s evenness, and Lenat’s EPT index) showed the considerable variations along with the increase of sample size and environmental conditions. To get the appropriate index values, it should be sampled at least 6 replicates more based on 30×30cm Surber sampler. In addition, the habitat heterogeneity index of benthic macroinvertebrates suggested in this study, it will be able to be used for evaluating the heterogeneity of habitats.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1021-1029
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• 2010

In 2009 the former three surveys on small and medium enterprises were combined into one survey to reduce the response burden of enterprises. In this report, we study a sample design for 2009 survey on actual state of small and medium enterprises (SMEs). However, the differences between the manufacturing industries and knowledge-based service industries are so large that we need to consider separate populations in the survey. The total sample size is decided as 10,000 in new survey design for integration. We allocate the sample sizes for the first stratum based on CV and then allocate the sample sizes for the second stratum using root proportional formula. Also we calculate survey weights and propose the formula for the estimators as well as standard errors using weights for each characteristic.

• Survey Research
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• v.11 no.1
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• pp.19-41
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• 2010

Although it is possible to provide statistically reliable estimators of the entire population parameters based on each independent rolling sample, estimators of the small areas may not have the required statistical efficiency. Thus, in general, small area estimators are calculated based on the combined rolling sample after entire rolling sample survey is finished. In this study, we considered the construction of weights that is necessary in the analysis of the combined rolling sample. Unlike the past studies that provided the empirical results for the corresponding specific rolling sample survey, we considered linear models that depends only on design variables and rolling period and provided the corresponding Best Linear Unbiased Predictor(BLUP). Through a simulation study, we proposed the estimators for the population parameters that are robust to model failure and the BLUP under the assumed model. The results are applied to the 4th Korea National Health and Nutrition Examination Survey.