• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.23-32
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• 2012

This paper deals with the bias and variance of regression coefficient estimators in a finite population. We derive approximate formulas for the bias, variance and mean square error of two estimators when we select a fixed-size inclusion probability proportional to the size sample and then estimate regression coefficients by the ordinary least square estimator as well as the weighted least square estimator based on the selected sample data. Necessary and sufficient conditions for the comparison of the two estimators in terms of variance and mean square error are suggested. In addition, a simple example is introduced to numerically compare the variance and mean square error of the two estimators.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.349-363
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• 2020

Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.

• Communications for Statistical Applications and Methods
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• v.20 no.6
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• pp.455-466
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• 2013

In nested case-control studies, the most common way to make inference under a proportional hazards model is the conditional logistic approach of Thomas (1977). Inclusion probability methods are more efficient than the conditional logistic approach of Thomas; however, the epidemiology research community has not accepted the methods as a replacement of the Thomas' method. This paper promotes the inverse probability weighting method originally proposed by Samuelsen (1997) in combination with an approximate jackknife standard error that can be easily computed using existing software. Simulation studies demonstrate that this approach yields valid type 1 errors and greater powers than the conditional logistic approach in nested case-control designs across various sample sizes and magnitudes of the hazard ratios. A generalization of the method is also made to incorporate additional matching and the stratified Cox model. The proposed method is illustrated with data from a cohort of children with Wilm's tumor to study the association between histological signatures and relapses.

• International Journal of Contents
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• v.13 no.3
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• pp.49-58
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• 2017

This is a descriptive research study that classified Korean adults with obesity into those with Metabolically Healthy Obesity and those with Metabolically Unhealthy Obesity based on the data from the fifth and sixth South Korea's National Health and Nutrition Examination Surveys, designed due to the development of information and communication technology, to examine the impacts of obese adults' health behavior factors and mental health factors on their metabolic state. With respect to data analysis, the collected data were analyzed by complex sample statistics. The results of this study can be summarized as follows: Men who were smoking at the time of the survey had a 1.29 times higher probability of inclusion in the MUO group than in the MHO group. Women who had a high stress cognition rate had a 1.02 times higher probability of inclusion in the MUO group than in the MHO group. This study is significant as it provides the basic data for establishing strategies of nursing intervention for the promotion of obese adults' health, and it suggests that it is necessary to develop a program for the promotion of obese adults' health based on these results.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.993-1004
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• 2017

A stratified sampling method is generally used with a sample selected using the same sample weight in each stratum in order to improve the accuracy of the sampling survey estimation. However, the weight should be adjusted to reflect the response rate if the response rate is affected by the value of the variable of interest. It may be also more effective to adjust the weights by subdividing the stratum rather than using the same weight if the variable of interest has a linear relationship with the continuous auxiliary variables. In this study, we propose a method to increase the accuracy of estimation using an informative sampling design technique when the response rate is an exponential function of the variable of interest and the variable of interest has a linear relationship with the auxiliary variable. Simulation results show the superiority of the proposed method.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.631-642
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• 2019

Many methods have been developed to solve problems found in sample surveys involving a large number of item non-responses that cause inaccuracies in estimation. However, the non-response adjustment method used under the assumption of random non-response generates a bias in cases where the response rate is affected by the variable of interest. Chung and Shin (2017) and Min and Shin (2018) proposed a method to improve the accuracy of estimation by appropriately adjusting a bias generated when the response rate is a function of the variables of interest. In this study, we studied a case where the response rate function is linear and the error of the super population model follows normal distribution. We also examined the effect of the number of stratum population on bias adjustment. The performance of the proposed estimator was examined through simulation studies and confirmed through actual data analysis.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.621-636
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• 2018

Research on the application of informative sampling technique has been conducted in order to reduce the influence of non-response. Chung and Shin (Korean Journal of Applied Statistics, 30, 993-1004, 2017) showed that the estimation accuracy improved when using exponential response rate information for the parameter estimation if the distribution of errors included in the super population model follows normal distribution. However this method divides the stratum into equally spaced substrata to obtain the sample weight of the informative sampling technique and shows that the accuracy of the estimation improves as the number of substrata increases. In this study, with the given number of total sample size, the optimal substratum boundary points are calculated using equal space, quantile, and LH algorithm; consequently, the results using those methods are compared through simulation. We also studied the criteria to determine the number of substrata and substratum boundaries that can be used in practice with various types of auxiliary variable distributions.

• Agribusiness and Information Management
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• v.9 no.2
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• pp.1-11
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• 2017

Introduction: To analyze the impact of marketing losses on efficiency in transacting banana in Kurnool district of SRZ in Andhra Pradesh and to assess the opinions of the farmers on the constraints in transacting banana. Research back ground, Materials and Methods: The study relies exclusively on primary information obtained from the banana farmers of Kurnool District. Purposive sampling procedure was followed for the selection of the study area. Top two mandals in the district and top two villages in each mandal are selected in accordance with the area under cultivation of banana. Probability proportion to size was followed regarding the selection of sample farmers and accordingly 60 marginal, 37 small and 23 other farmers were selected and thereby, the total sample size was 120. Result and Discussion: Three marketing channels were identified in the marketing of banana in Kurnool district viz., Producer ${\rightarrow}$ Local-exporter ${\rightarrow}$ Wholesaler ${\rightarrow}$ Retailer ${\rightarrow}$ Consumer (Channel-I), Producer ${\rightarrow}$ Wholesaler ${\rightarrow}$ Cart-vendor ${\rightarrow}$ Consumer (Channel-II) and Producer ${\rightarrow}$ Juice-holder ${\rightarrow}$ Consumer (Channel-III). With the inclusion of marketing losses in the price spread analysis of banana in all the three channels, the marketing costs of all the intermediaries were increased and thereby, the farmer's share in consumer's rupee and Net Marketing Margins of the agencies are on the decline. So, without inclusion of marketing losses, the farmer's share in consumer's rupee and Net Marketing Margins of all the agencies are overvalued. The higher the marketing losses, the more is the negative impact on farmer's net selling price, net marketing margins of the intermediaries and marketing efficiency. The sample farmers are facing major problems in marketing of banana like frequent price fluctuations, unorganized marketing and lack of transportation facilities on priority basis. Suggestions: It is suggested to educate the farmers regarding the optimum maturity index for harvest, use of mechanical harvesters, proper placement of fruits during storage and ripening, better packaging and cushioning technologies to absorb shocks during transportation, strengthening of storage facilities and transport facilities, encourage co-operative marketing etc., to promote marketing efficiency of banana in the study area.

• Journal of Korea Trade
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• v.26 no.5
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• pp.39-55
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• 2022

Purpose - This study empirically examines the effect of the Korean government export promotion program (EPP) on small and medium-sized enterprise (SMEs) export performance using firm-level data. Unlike most previous studies that investigated some specific samples of firms, this study analyzes a vast amount of SME data of the Korean Small and Medium Business Administration over the period 2005 to 2008. Design/methodology - An endogeneity problem arises when a firm's probability of being selected is correlated with the likelihood of successfully implementing EPPs. To control for the endogeneity of the EPPs in a relatively short-period sample, we employ 2-Stage Residual Inclusion (2SRI) RE-Tobit and bivariate Tobit procedure. Findings - Analyses show that Korean government EPPs have positive significant effects on SME exports. Empirical results also show that SME export activities are significantly encouraged by R&D investment and capital intensity, but not obviously by labor productivity. Originality/value - This study provides evidence that SME capital intensity, R&D investment, and the number of workers are significant determinants to SME exporting activities, whereas per worker labor cost and employee education are not. These results imply that even for SMEs, firm size is a major factor in promoting exporting activities.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.281-290
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• 2007

Linear estimator, a weighted sum of the sample observation, is commonly adopted to estimate the finite population parameters such as population totals in survey sampling. The weight for a sampled unit is often constructed by multiplying the base weight, which is the inverse of the first-order inclusion probability, by an adjustment term that takes into account of the auxiliary information obtained throughout the population. The linear estimator using the weight adjustment is often more efficient than the one using only the bare weight, but its valiance estimation is more complicated. We discuss variance estimation for a general class of weight-adjusted estimator. By identifying that the weight-adjusted estimator can be viewed as a function of estimated nuisance parameters, where the nuisance parameters were used to incorporate the auxiliary information, we derive a linearization of the weight-adjusted estimator using a Taylor expansion. The method proposed here is quite general and can be applied to wide class of the weight-adjusted estimators. Some examples and results from a simulation study are presented.