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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Korean Journal of Applied Statistics
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Journal DOI :
The Korean Statistical Society
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Volume & Issues
Volume 6, Issue 2 - Sep 1993
Volume 6, Issue 1 - Mar 1993
Selecting the target year
의학 연구자료 분석과 통계적 기법
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 183~189
Statistical methods for evaluating the tracking phenomenon of blood pressure
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 191~200
This study introduced speical characteristics of an epidemiologic study on blood pressure and compared several statistical methods for evaluating the tracking phenomenon of blood pressure for Korean children. While correlation coefficients adjusted for measurement error are commonly used for the evaluation of tracking, it is hard to interpretate the results when correlation functions for lag-difference are not monotonous. McMahan defined a tracking as maintenance of relative rank over time and calculated tracking index usng growth curve model. The tracking index in McMahan's model is complicate to calculate, and it is hard to determine the degree of growth curve parameter. Blomqvist showed the relationship between the rate of change and the initial value. This concept could be extended for the evaluation of tracking. However, it is not so easy to interpretate the estimates in his model when those are non-positive.
Statistical analyses in an occupational health study
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 201~215
The health status of workers in a foundry was analyzed in a study which consisted of evaluations of respiratory health together with environmental measurements. The results from environmental measurements showed values exceeding permissible exposure limits. A t-test was done with log transformed and untransformed data to examine the statistical significance for the noncompliance with exposure standards. For the analysis of categorical health outcomes,
-square test with 2
2 tables and logistic regression analysis were employed. For continuous variables, multiple linear regression was done against assessed risk factors. Pros and cons of different parameters in the compliance (or noncompliance) testing were presented. Respiratory function did not show any relation with occupational exposures, which may be due to the healthy worker effects. Strategies for controlling time dependent covariates were discussed in relation to the healthy worker effect. The scope of statistical analysis in occupational health studies is still limited in Korea without a suitable external comparison group such as credible vital statistics for the whole nation. Internal comparisons between different exposure status often result in unstable estimates of effect, and proportional morbidity study is discussed as an alternative potential research tool.
"의학 연구자료 분석과 통계적 기법"에 대하여
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 217~226
Nonparametric kernel calibration and interval estimation
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 227~235
Calibration relates the estimation of independent variable which rquires more effort or expense than dependent variable does. It would be provided with high accuracy because a little change of the result of independent variable cn cause a serious effect to the human being. Usual statistical analysis assumes the normality of error distribution or linearity of data. It is desirable to analyze the data without those assumptions for the accuracy of the calibration. In this paper, we calibrated the data nonparametrically without those assumptions and derived confidence interval estimate for the independent variable. As a method, we used kernel method which is popular in modern statistical branch. We derived bootstrap confidence interval estimate from the bootstrap confidence band.
A study on a nonparametric test for ordered alternatives in regreesion problem
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 237~245
A nonparametric test for the parallelisim of k regression lines against ordered alternatives is proposed. The test statistic is weighted Jonckheere-type statistic applied to slope estimators obtained from each lines. The distribution of the proposed test statistic is asymptotically distribution-free. From the viewpoint of efficiencies, the proposed test desirable properties and is more efficient than the other nonparametric tests.
On L1 regression coefficients
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 247~252
Consider minimizing the sum of absolute deviations for multiple regression models. If a regression line is assumed to pass a given point, then we can find that the
regression coefficient can be defined in terms of the weighted medians of the slopes from each data point to the given point. Therefore,
method could be regarded to find the optimal point which regression line passes over.
Generalized linear models versus data transformation for the analysis of taguchi experiment
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 253~263
Recent interest in Taguchi's methods have led to developments of joint modelling of the mean and dispersion in generalized linear models. Since a single data transformation cannot produce all the necessary conditions for an analysis, for the analysis of the Taguchi data, the use of the generalized linear models is preferred to a commonly used data transformation method. In this paper, we will illustrate this point and provide GLIM macros to implement the joint modelling of the mean and dispersion in generalized linear models.
Consistency of M-estimators in nonlinear regression model
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 265~275
This paper deals with the M-estimators in regression model. The class of M-estimators is defined on nonlinear regression model and the conditions to hold the consistency of the considered estimators are suggested when the parameter space of the model is compact.
Multi-level skip-lot sampling plan
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 277~287
This paper is a generalization of single- and two-level skip-lot sampling plans to n-level, which can considerably reduce inspection cost when the level of submitted quality is high. In every skipping inspection of the generalized sampling plan, not only skipping parameters but also inspection fractions can be freely choosed. The general formula of the operating characteristic function for the n-level skip-lot sampling plan is derived. Also the operating characteristic curves of a reference plan, two-level and three-level skip-lot sampling plans are compared.
A goodness-of-fit test for exponentiality with censored samples
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 289~302
A goodness-of-fit test for the two-parameter exponential distribution, for use with the singly Type I and Type II right censored samples, is proposed. The test statistic is based on the
-norm of discrepancy between the cumulative distribution function and the empirical distribution function. To deal with the unknown parameters problem, the K- transformation is considered and modified to be applied to the censored samples. Rosenblatt's transformation is extended to the cases of Type I and Type II censored samples, in order to transform the censored samples into the complete ones. The critial values of the test statistic are obtained by Monte Carlo simulations for some finite sample sizes. The power studies are conducted to compare the proposed test with the Pettitt(1977) test for exponentiality with censored samples. It appears that the proposed test has relatively good power properties for moderate and large sample sizes.
Error-robust experimental designs: D- and heteroscedastic G-optimalities
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 303~309
In this paper we have defined two approaches to be error-robust when the precise form of error-structure is unknown. An experiment is optimal by the first criterion if it maximizes the minimum effciency over all candidates of error structure and is optimal by the second if it maximizes the minimum average of the efficiency over all candidates of error structure. In order to appreciate the basic implications of each design criterion, these approaches are applied to two different experimental situations, D- and heteroscedastic G-optimalities.
An alternative randomized response technique
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 311~318
In this paper, we consider the test based on using Forced question model instead of Warner model and compare the power of two randomized respose models. The estimator for the prportion of the individuals belonging to the sensitive group is obtained by using Forced question model and the conditions that the estimator by Forced question model will be more efficient than the estimators by Warner model are found when the respondents are truthrul in their answers.
Convergence Rate of Newton-Raphson Method
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 319~328
The actual convergence rate of Newton-Raphson iteration method at each step is studied under the regularity conditions for the limiting distribution: The convergence rate of it is accelerated with good starting values. Hence we can decide a number of iterations according to our purposes.
Modification of boundary bias in nonparametric regression
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 329~339
Kernel regression is a nonparametric regression technique which requires only differentiability of the true function. If one wants to use the kernel regression technique to produce smooth estimates of a curve over a finite interval, one can realize that there exist distinct boundary problems that detract from the global performance of the estimator. This paper develops a kernel to handle boundary problem. In order to develop the boundary kernel, a generalized jacknife method by Gray and Schucany (1972) is adapted. Also, it will be shown that the boundary kernel has the same order of convergence rate as non-boundary.
On asymptotics for a bias-corrected version of the NPMLE of the probability of discovering a new species
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 341~353
As an estimator of the conditional probability of discovering a new species at the next observation after a sample of certain size is taken, the one proposed by Good(1953) has been most widely used. Recently, Clayton and Frees(1987) showed via simulation that their nonparametric maximum likelihood estimator(NPMLE) has smaller MSE than Good's estimator when the population is relatively nonuniform. Lee(1989) proved that their conjecture is asymptotically true for truncated geometric population distributions. One shortcoming of the NPMLE, however, is that it has a considerable amount of negative bias. In this study we proposed a bias-corrected version of the NPMLE for virtually all realistic population distributions. We also showed that it has a smaller asymptotic MSE than Good's extimator except when the population is very uniform. A Monte Carlo simulation was performed for small sample sizes, and the result supports the asymptotic results.
Efficiency of MINQE for arbitrary underlying distribution under one way random effects model
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 355~370
The estimations of variance components for the unbalanced one way random effects model when the underlying distributions are not necessarily normal are considered. ANOVA, REML, ML, MIVQUE, and MINQE estimators are compared with respect to their mean squared errors and biases through a simulation study. Explicit, computable expressions with no matrix inversion necessary are given for these estimators. An efficient rule to provide a prior guess of MINQE is given. Our results indicate that the efficiency of MINQE is excellent for arbitrary underlying distribution in the sense of MSE even in the presence of nontrivial bias. Also, MINQE is a worthwhile improvement over other estimators when kurtosis of underlying distributions become large 1.
Robust selection rules of k in ridge regression
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 371~381
When the multicollinearity presents in the standard linear regression model, ridge regression might be used to mitigate the effects of collinearity. As the prediction-oriented criterion, the integrated mean sqare error criterion
was introduced by Lim, Choi & Park(1980). By noting the equivalent relationship between the
with a special choice of weight function
, we propose a more reasonable selection rule of k w.r.t. the
criterion than that given in Myers(1986). Next, to find the
which behaves reasonably well w.r.t. competing criteria, we adopt the minimax principle in the sense of maximizing the worst relative efficiency of k among competing criteria.
Statistical method for testing synergism among several compounds
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 383~391
Interaction between anti-cancer agents and various modulators of multidrug resistance in producing their joint effects are of fundamental interest in the chemtherapeutic treatment of cancer. We generate a dose-response curve for each combination of several anti-cancer agents and modulators based on an in-vitro experiment on each of several human cancer cell lines. We employ a log-linear model developed by Wahrendorf et al (1981) and Piegorsch et al (1988) to detect synergism among several compounds. We show two examples of the data analysis and their results. We believe that these results encourage further experiment in-vivo studies.
Assessing the accuracy of the maximum likelihood estimator in logistic regression models
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 393~399
When we compute the maximum likelihood estimators of the parameters for the logistic regression models, which are useful in studying the relationship between the binary response variable and the explanatory variable, the standard error calculations are usually based on the second derivative of log-likelihood function. On the other hand, an estimator of the Fisher information motivated from the fact that the expectation of the cross-product of the first derivative of the log-likelihood function gives the Fisher information is expected to have similar asymptotic properties. These estimators of Fisher information are closely related with the iterative algorithm to get the maximum likelihood estimator. The average numbers of iterations to achieve the maximum likelihood estimator are compared to find out which method is more efficient, and the estimators of the variance from each method are compared as estimators of the asymptotic variance.
A nonparametric test for parallelism of regression lines against ordered alternatives
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 401~408
This paper suggests a nonparametric test for the parallelism of several regression lines against ordered alternatives. The test statistic is an extension of the Potthoff statistic. The asymptotic variance of the proposed statistic is estimated by Bootstrap method. The proposed test are compared with the Adichie's parametric and nonparametric tests.
A graphical method for discriminant analysis when covariance matrices are unequal
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 409~419
This paper concerns graphical methods for discriminant analysis. We discuss Sammon's graph, MV graph and possibility of an alternative. The properties of the three graphs are investigated using real data and simulation studies. Dimensionality reduction for an alternative and robust procedure are discussed.
Influential observations on variable selection in linear regression model
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 421~433
Few ovservation can influence in model building procedure and can dominate the least squares fit of a selected model. An observation, however, may not have the same impact on all aspects of regression analysis. We introduce a statistic which measures the impact of individual cases on the overall goodness-of-fit statistics. We also propose an influence measure for variable selection problem. The property of uncorrelatedness between fitted values and residuals has been used to develop the influence measure. The performance of the measures are used to develop the influence measure. The performance of the measures are compared with other widely used influence measures by the analysis of real data.
Approximate confidence intervals about quantiles in the generalized gamma distribution
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 435~442
For the generalized gamma distribution, exact inferences about quantiles need many computations involving complicated numerical integrations. This paper suggests approximate confidence intervals which are easily obtained by considering the alternative location-scale model. Also, these intervals are very accurate even for small sample size. Approximate confidence intervals about quantiles in the lognormal distribution are also considered. With type 2 censoring data, approximate confidence intervals can also be obtained directly by the suggested methods.
A Study on the Validity of the Statistical Collection and Analysis in Gwangju and Chonnam
Korean Journal of Applied Statistics, volume 6, issue 2, 1993, Pages 443~452
A check list which includes the items that are to be considered in the process of the statistical data collection and analysis by non-scientific organizations is proposed. Based on the suggested check list, the output resulting from the statistical survey conducted by private organizations, banks, organs of expression and enterprises in Gwangju and Chonnam are examined about the validity of data collection and statistical analysis.