• Title/Summary/Keyword: Statistical surveys

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Analysis of categorical data with nonresponses (무응답을 포함하는 범주형 자료의 분석)

  • 박태성;이승연
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.83-95
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    • 1998
  • Statistical models are proposed for analyzing categorical data in the presence of missing observations or nonresponses which might occur in the sampling surveys and polls. As an illustration, we analyzed real polling data of the pre-presidential election in the USA, 1948, It had been predicted that Dewey would win the election. However, Truman won in the actual election.

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Contribution of Ecological Surveys to Coastal Conservation: A Case in Soft Shore Study

  • Tai, K. K;Cheung, S.-G;Shin, P.-K.-S.
    • The Korean Journal of Ecology
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    • v.27 no.3
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    • pp.127-131
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    • 2004
  • Soft shores are particularly vulnerable to human exploitation; however, they exhibit a variety of habitats which provide refuge for a diversity of flora and fauna. This study describes a survey of 13 soft shores in Hong Kong with information on species diversity, sediment characteristics, shore extent, pollution threat, degree of naturalness, linkage with other ecological habitats, and degree of social/economic importance. Data collected were subjected to multivariate statistical analyses, so as to identify shores that have significant ecological status and conservation value for management purposes.

The Controlled Selection: Do Algorithms for Optimal Sampling Plan Exist?

  • Kim, Sun-Woong;Ryu, Jae-Bok;Yum, Joon-Keun
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.11a
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    • pp.175-178
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    • 2002
  • A number of controlled selection methods, which have some advantages for practical surveys in considering controls beyond stratification, have developed throughout the last half-century. With respect to the optimization of sampling plan, it is obvious that we may use optimal controlled selection in preference to satisfactory controlled selection. However, there are currently certain restrictions on the employment of optimal controlled selection. We present further research to improve an algorithm for optimal controlled selection and to develop standard software.

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Implementation of Randomized Response Technique at Internet Survey

  • Park, Hee-Chang;Nam, Ki-Seong;Lee, Gi-Sung
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.731-737
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    • 2001
  • In this paper, we suggest and implement an internet survey system cooperating the randomized response technique(RRT). We compare it with the direct survey. RRT is an indirect survey method to get true information from the respondent who is conceived to have sensitive character without revealing his/her status. We implement our system(method) based a data-base system, so it common all kind of data obtained through internet surveys. This system also can be used in spot survey independently.

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Time Use and Time Famine in Single-Parent Families: A Comparison of Single-Mothers and Fathers (한부모가족의 시간사용과 시간부족감의 성차 분석)

  • Kim, Oi-Sook;Park, Eun Jung
    • Journal of Family Resource Management and Policy Review
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    • v.22 no.3
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    • pp.1-19
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    • 2018
  • This study was aimed at exploring gender differences in time use and time famine between single-parent families. Data were obtained from the time use surveys, that were conducted by the Korea National Statistical Office in 2014. A total of 500 time diaries (168 from fathers, 332 from mothers) from single-parents aged between 20 and 59 were analyzed. Descriptive statistics, chi-square test, and t-test were used for the statistical analyses. Results indicated that the single-parent families exhibit gender differences in time use and subjective time famine. The single-mothers spend a significantly longer amount of time on housework and less time on leisure than do the single-fathers. The single fathers and mothers also differ in time use and time famine according to employment status and working days on/off.

Language Modeling Approaches to Information Retrieval

  • Banerjee, Protima;Han, Hyo-Il
    • Journal of Computing Science and Engineering
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    • v.3 no.3
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    • pp.143-164
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    • 2009
  • This article surveys recent research in the area of language modeling (sometimes called statistical language modeling) approaches to information retrieval. Language modeling is a formal probabilistic retrieval framework with roots in speech recognition and natural language processing. The underlying assumption of language modeling is that human language generation is a random process; the goal is to model that process via a generative statistical model. In this article, we discuss current research in the application of language modeling to information retrieval, the role of semantics in the language modeling framework, cluster-based language models, use of language modeling for XML retrieval and future trends.

Estimation of Hard-to-Measure Measurements in Anthropometric Surveys

  • Choi, Jong-Hoo;Kim, Ryu-Jin
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.213-220
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    • 2002
  • Anthropometric survey is important as a basis for human engineering fields. According to our experiences, there are difficulties in obtaining the measurements of some body parts because respondents are reluctant to expose. In order to overcome these difficulties, we propose a method for estimating such hard-to-measure measurements by using easy-to-measure measurements those are closely related to them. Multiple Regression Model, Feedforward Neural Network(FNN) Model and Projection Pursuit Regression(PPR) Model will be used as analytical tools for this purpose. The method we propose will be illustrated with real data from the 1992 Korea national anthropometric survey.

Measuring economic sentiment using ordinary response options

  • Park, Inho;Kim, Tae Yoon
    • Communications for Statistical Applications and Methods
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    • v.24 no.2
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    • pp.163-172
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    • 2017
  • Economic sentiment is typically measured using ordinary response options. The University of Michigan and the United States Conference Board are two widely used major indexes that have separately established independent consumer sentiment indexes based on three-level ordinary response options: positive, neutral, and negative. Notwithstanding, limited attention has been paid to the structural differences in their built-in formulas, which are referred to the disparate micro scoring schemes applied to an individual question. This paper examines the structural difference of the two indexes and then addresses situations where one is more reliable than the other. Real data from business tendency surveys of the Organization for Economic Cooperation and Development are used to illustrate our points empirically. As a conclusion, it is stressed that the two indexes should be handled with care when applied to economic sentiment comparison studies.

Allocation in Multi-way Stratification by Linear Programing

  • NamKung, Pyong;Choi, Jae-Hyuk
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.327-341
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    • 2006
  • Winkler (1990, 2001), Sitter and Skinner (1994), Wilson and Sitter (2002) present a method which applies linear programing to designing surveys with multi-way stratification, primarily in situation where the desired sample size is less than or only slightly larger than the total number of stratification cells. A comparison is made with existing methods both by illustrating the sampling schemes generated for specific examples, by evaluating sample mean, variance estimation, and mean squared errors, and by simulating sample mean for all methods. The computations required can, however, increase rapidly as the number of cells in the multi-way classification increase. In this article their approach is applied to multi-way stratification using real data.

Variance Estimation for Imputed Survey Data using Balanced Repeated Replication Method

  • Lee, Jun-Suk;Hong, Tae-Kyong;Namkung, Pyong
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.365-379
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    • 2005
  • Balanced Repeated Replication(BRR) is widely used to estimate the variance of linear or nonlinear estimators from complex sampling surveys. Most of survey data sets include imputed missing values and treat the imputed values as observed data. But applying the standard BRR variance estimation formula for imputed data does not produce valid variance estimators. Shao, Chen and Chen(1998) proposed an adjusted BRR method by adjusting the imputed data to produce more accurate variance estimators. In this paper, another adjusted BRR method is proposed with examples of real data.