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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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The Korean Statistical Society
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Volume & Issues
Volume 11, Issue 2 - Sep 1998
Volume 11, Issue 1 - Mar 1998
Selecting the target year
Analysis of Repeated Measures Data: Chronic Renal Allograft Dysfunction Data from the Renal Transplanted Patients
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 205~219
Statistical analyses have been perf7rm7d to find factors affecting chronic renal allograft dysfunction for 114 renal transplanted patients. Renal function was evaluated using serum creatinine values every three months during 1 year to 5 years after transplantation. Statistical models for the repeated measures were considered to evaluate factors affecting the reciprocal of serum creatinine values. This paper focuses on some common problems on the choice of correlation matrices occurred in the analysis of repeated measures.
Measuring the changes in the trend of urban and rural migration in Korea
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 221~232
There was a large reform in administrative districts during 1990-95, which might influence the estimates of migration according to the definition of migration. An indirect method has been worked out in this paper to measure the influence of the district reforms on migration estimation and to provide more accurate recent trend of migration. The district reform during 1950-95 tended to decrease the estimate of total migrants and influenced substantially the estimates of migrants between urban and rural. When the influences of district rewarm were removed, it was found that total migrations increased by 8.5%, between two periods 1985-'90 and 1990-'95, and the net migrants in the rural areas reduced drastically. It was also found that the change in migration trend between urban and rural was no more a local but a nation wide phenomenon.
A Sampling Design for the livestock (Korean Native Beef Cattle, Milk Cow, Pig, Chicken) Statistics
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 233~246
We made a sample design for next 5 years, based on the population as of 1995, for livestock statistics. In the sample design, we used the stratified one stage sampling method where the sample size depends on the prefixed coefficient of variation. In stratifying the population, we considered the complete linkage method, and decided the number of strata to be the one which yields the minimum sample size. We listed here some difficulties we had for the better sample design in the future.
Subset Selection in the Poisson Models - A Normal Predictors case -
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 247~255
In this paper, a new subset selection problem in the Poisson model is considered under the normal predictors. It turns out that the subset model has bigger valiance than that of the Poisson model with random predictors and this has been used to derive new subset selection method similar to Mallows'
A Study on Mante1-Haenszel Test of Conditional Independence
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 257~268
Many epidemiological studies investigate whether an association exists between a binary risk factor X and a binary response variable Y. They analyse whether an observed association between X and Y persists when the level of another factor Z that might influence the association is controlled. This involves testing conditional independence of X and Y controlling for Z. The Mantel-Haenszel test is most widely used to test conditional independence for sparse tables. But if the association between X and Y varies along the levels of Z, Mantel-Haenszel test has a low power problem. In this study, we propose an alternative test procedure which overcomes the low power problem in that case. We find out the null distribution of the alternative test statistic and compare its performance with the Mantel-Haenszel test by simulation.
Sample Size Determination in survival Studies
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 269~285
One of the most important issues in the area of clinical trial research is the determination of the sample size required to insure a specified power in detecting a real or clinically relevant difference of a stated magnitude. Increasingly, medical journals are requiring authors to provide information on the sample size needed to detect a given difference. We restrict our attention to the designs far comparirng two survival distributions. These are concerned with the survival time which is defined as the interval from a baseline(e.g. randomization) to failure (e.g. death, recurrence of disease). Survival times axe right censored when patients have not foiled by the time of analysis or have been loss to follow-up during the trial. For different types of clinical trials for comparing survival distributions, there have been marry research in sample size determination. We review the existing literature concerning commonly used sample size formulae in the design of randomized clinical trials, and compare the assumption, the power and the sample size calculation of these methods. We also compare by simulation the expected power and observed power of each method under various circumstances. As a result, guidelines in terms of practical usage are provided.
Saddlepoint Approximation to the Distribution of General Statistic
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 287~302
Saddlepoint approximation to the distribution function of sample mean(Daniels, 1987) is extended to the case of general statistic in this paper. The suggested approximation methods are applied to derive the approximations to the distributions of some statistics, including sample valiance and studentized mean. Some comparisons with other methods show that the suggested approximations are very accurate for moderate or small sample sizes. Even in extreme tail the accuracies are also maintained.
Fractional Factorial Desig Excluded A Debarred Combination
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 303~315
In a factorial experiment, certain combinations of factor levels clay not be ruled out for operational or economical reason. A fractional factorial design that contains such infeasible combinations, called debarred combinations, becomes too unbalanced to estimate the required effects. This thesis presents a method of selecting defining contrasts for constructing regular
fractional factorial design which does not contain a debarred combination. Consequently, the construction of the design is accomplished by choosing the defining contrasts so that one of defining contrasts is compatible with a debarred combination.
The Analysis of the Stock Price Time Series using the Geometric Brownian Motion Model
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 317~333
In this study, I employed the autoregressive model and the geometric Brownian motion model to analyze the recent stock prices of Korea. For all 7 series of stock prices(or index) the geometric Brownian motion model gives better predicted values compared with the autoregressive model when we use smaller number of observations.
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 335~350
X11ARIMA is established on the basis of X11 which is one of smoothing approach in time series area and this procedure was introduced by Bureau of Census of United States and developed by Dagum(1975). This procedure had been updated and adjusted by Dagum(1988) with 174 economic index of North America and has been used until nowadays. Recently, X12ARIMA procedure has been studied by William Bell et.al. (1995) and Chen. & Findly(1995) whose approaches adapt adjusting outliers, Trend-change effects, seasonal effect, arid Calender effect. However, both of these procedures were implemented for correct adjusting the economic index of North America. This article starts with providing some appropriate and effective ARIMA model for 102 indexes produced by national statistical office in Korea; which consists of production(21), shipping(27), stock(27), and operating rate index(21). And a reasonable smoothing method will be proposed to reflect the specificity of Korean economy using several moving average model. In addition, Sulnal(lunar happy new year) and Chusuk effects will be extracted from the indexes above and both of effects reflect contribution of lunar calender effect. Finally, we will discuss an alternative way to estimate holiday effect which is similar to X12ARIMA procedure in concept of using both of ARIMA model and Regression model for the best fitness.
A Test for Weibull Distribution and Extreme Value Distribution Based on Kullback-Leibler Information
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 351~362
In this paper, a test of fit for Weibull distribution on the estimated Kullback-Leibler information is proposed. The test uses the Vasicek entropy estimates, so to compute it a window size m must first be fried, and then is obtained critical values computed by Monte Carlo simulations. The power of the proposed test under various alternatives is compares with that of ocher famous tests. The use of the test is shown in an illustrative example.
A Second Order Smoother
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 363~376
The linear smoothing spline estimator is modified to remove boundary bias effects. The resulting estimator can be calculated efficiently using an O(n) algorithm that is developed for the computation of fitted values and associated smoothing parameter selection criteria. The asymptotic properties of the estimator are studied for the case of a uniform design. In this case the mean squared error properties of boundary corrected linear smoothing splines are seen to be asymptotically competitive with those for standard second order kernel smoothers.
Bayesian Computation for Superposition of MUSA-OKUMOTO and ERLANG(2) processes
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 377~387
A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced latent variables that indicates with component of the Superposition model. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Metropolis algorithms along with Gibbs steps are proposed to preform the Bayesian inference of such models. for model determination, we explored the Pre-quential conditional predictive Ordinate(PCPO) criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions, we consider in this paper Superposition of Musa-Okumoto and Erlang(2) models. A numerical example with simulated dataset is given.
Learning system for Regression Analysis using Multimedia and Statistical Software
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 389~401
This paper introduces CybeRClass(Cyber Regression Class). CybeRClass uses the technique of animation arid voice to teach regression analysis. The structure of this system make it possible to extend to multivariate analysis methods such as discriminant analysis and cluster analysis. Tools for multimedia is Multimedia ToolBook, and Xlisp-Stat is used for statistical computation and statistical graphics.
Assessment for Sample Size Determination using Two-Stage Sampling Scheme
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 403~413
Sample size determination is a crucial part of sampling design. This paper gives a assessment for sample size determination using two-stage sampling scheme for estimating the population mean with a given precision.
Improved Unrelated Question Model
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 415~421
In this paper, we proposed improved unrelated question model which has the benefit of simplicity the Kim et al.'s two-stage unrelated question model(1992). conditions are obtained under which the proposed model is more efficient than the Greenberg et al. model(1971) and Kim et al's two-stage unrelated question model.
Modelling Heterogeneity in Fertility for Analysis of Variety Trials
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 423~433
In agricultural field experiments, the completely randomized block design is often used for the analysis of variety trials. An important assumption is that every experimental unit in each block has the some fertility. But, in most agricultural field experiments there often exists a systematic heterogeneity in fertility among the experimental units. To account for the heterogeneity, we propose to use the hierarchical generalized linear models. We compare our analysis of the data from Scottish Agricultural colleges list with that using Markov chain Monte Carlo method.
A Bayes Criterion for Selecting Variables in MDA
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 435~449
In this article we have introduced a Bayes criterion for the variable selection in multiple discriminant analysis (MDA). The criterion is a default Bayes factor for the comparision of homo/heteroscadasticity of the multivariate normal means. The default Bayes factor is obtained from a development of the imaginary training sample method introduced by Spiegelhalter and Smith (1982). Based an the criterion, we also provided a test for additional discrimination in MDA. The advantage of the criterion is that it is not only applicable for the optimal subset selection method but for the stepwise method. More over, the criterion can be reduced to that for two-group discriminant analysis. Thus the criterion can be regarded as an unified alternative to variable selection criteria suggested by various sampling theory approaches. To illustrate the performance of the criterion, a numerical study has bean done via Monte Carlo experiment.
A Study of Applications of Sequential Biplots in Multiresponse Data
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 451~459
The analysis of data from a multiresponse experiment requires careful consideration of the multivariate nature of the data. In a multiresponse sitation, the optimization problem is more complex than in the single response case. The biplot is a graphical tool which make the analyst to understand the correlation of the response variables, the relation of the response variables arid the explanatory variables and the relative importance of the explanatory variables. In case of good fitting of the first order model, we can draw the biplot with the first order experimental design. Otherwise, we can make the biplot with the second order experimental design by adding other experimental points.
An Estimation Procedure Using Updated Stratification Sample in Panel Survery
Korean Journal of Applied Statistics, volume 11, issue 2, 1998, Pages 461~475
In panel survey in which the sample is selected by stratified random sampling, if the sampling units shift from a stratum to others in time, then the movement should be incorporated in the estimation procedures. Dealing with the problem caused by the movement of units across stratum in the updated stratification sample, the bias of the conventional estimator neglecting the movement is investigated, arid the bias-adjusted estimators are proposed. The variance estimator of the suggested estimators is also derived. It is illustrated via a simulation study that the proposed estimators beat the conventional estimator in the sense of bias and mean squared error In particular, when the Neyman allocation is applied in stratified sampling, the proposed estimator is shown much more effective to this end.