• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.71-82
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• 2001

There are several ways to test the equality of two survival distributions under a variety of situations. Tests for equality of two distributions with life-table model for univariate independent response times are reviewed and introduced. It is developed that the methodology to test it for correlated response times where treatments are applied to different independent sets of cohorts. Data, which can be separated into two independent sets, from an angioplasty study where more than one procedure is performed on some patients are used to illustrate this methodology.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.423-434
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• 2012

A two-sample test for equality of survival distribution is one of the important issues in survival analysis, especially for clinical and epidemiological research. With interval censored data, some testing methods have been developed. This study introduces some testing methods and compares them under various situations through simulation study. Based on simulation result, it provides some useful information on choosing the most appropriate testing method in a given situation.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.521-529
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• 2005

In this paper, we consider a bootstrap method to the 'row and column effects model' (RC model) to analyze a contingency table with ordered variables. We propose a bootstrap procedure for testing of independence, equality of intervals, and goodness of fit in the RC model. A real data example is included.

• Journal of Integrative Natural Science
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• v.12 no.3
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• pp.91-99
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• 2019

Many researchers in various study fields use the two sample t-test to confirm their treatment effects. The two sample t-test is generally used for small samples, and assumes that two independent random samples are selected from normal populations, and the population variances are unknown. Researchers often conduct F-test, the test of equality of variances, before testing the treatment effects, and the test statistic or confidence interval for the two sample t-test has two formats according to whether the variances are equal or not. Researchers using the two sample t-test often want to know how large sample sizes they need to get reliable test results. This research gives some guidelines for sample sizes to them through simulation works. The simulation had run for normal populations with the different ratios of two variances for different sample sizes (${\leq}30$). The simulation results are as follows. First, if one has no idea equality of variances but he/she can assume the difference is moderate, it is safe to use sample size at least 20 in terms of the nominal level of significance. Second, the power of F-test for the equality of variances is very low when the sample sizes are small (<30) even though the ratio of two variances is equal to 2. Third, the sample sizes at least 10 for the two sample t-test are recommendable in terms of the nominal level of significance and the error limit.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.691-699
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• 2017

Data analysts sometimes test the equality of two normal population means by the inspection of the overlapping of two confidence intervals. This method seems simple to use; however, it is a common statistical misconception to suppose that two normal means are not significantly different because of no overlapping. This article will present transforming the confidence interval of the mean difference to individual confidence intervals that are visualized to inspect overlapping. It will also be shown that this technique can be extended when comparing the k normal population means with equal variances.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.4
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• pp.587-596
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• 2017

In this study, multi-chambered single autoinjector(2in1) and KMARK-1 containing atropine and 2-PAM(pyridine-2-aldoxime methylchloride) were administered to the beagle's muscle, and blood samples were taken for a certain period of time to compare and evaluate the pharmacokinetic profiles of the two drugs. Male beagles were used and classified into two test groups(G1, G2), and crossover pharmacokinetic studies were performed in two test groups. Blood samples were collected from the jugular vein for analysis after administration. The 90 % confidence interval(CI) for log transformed data indicated that the Cmax for both atropine(log 0.9683 ~ log 1.113) and 2-PAM(log 0.9453 ~ log 1.214) was within the limits of bioequivalence criteria, but the AUC for atropine(log 1.1786 ~ log 1.3238) failed to meet this criteria. This is expected as the amount of atropine dose is 25 % higher for the test as compared to the reference formulation. In summary, in view of the ATNAA(antidote for nerve agent of US) authorization, the Cmax equivalence was more important than AUC equivalence, so in this study, we also focused on verifying the equality of Cmax between the two autoinjectors.

• Journal of Animal Environmental Science
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• v.14 no.3
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• pp.159-166
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• 2008

This research was carried out to test and analyze capacity of the long distance sprayer fan in large livestock farmhouses. Long distance sprayer was manufactured to be able to spray a lot of water, which was a solvent for agricultural chemicals and black dye with the maximum spraying distance of 140 m and the effective spraying distance of 100 m. The spraying quantity and the distance were measured the intensity values of images within A4 papers, which absorbed the agricultural chemicals by spraying by binary image processing. These A4 papers were fixed upon the height of 1 m from soil ground at regular 10 m interval. After the A4 papers were collected and analyzed the intensity values of gray level. Gray level was ranged from 0 to 255, where 0 was black and 255 was white. A4 paper was fallen down from the stick at 10 m distance, because there were too large amount of sprayed water with black dye. Also, the paper showed low gray level at distance 30 m because of dropping lots of black water. The intensity value of gray level was showed almost less than 200 on the A4 papers between the distance 20 m and 100 m, which meant equality of spraying quantity. Additionally, it was possible to spay agricultural chemicals of until 180 m. Throughout this research, long distance sprayer could apply for preventing hoof-and-mouth disease in large livestock farmhouses.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.47-59
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• 2000

The purpose of this study is to develop travel-time estimation model using neural networks and prediction model using neural networks and kalman-filtering technique. The data used in this study are travel speed collected from inductive loop vehicle detection systems(VDS) and travel time collected from the toll collection system (TCS) between Seoul and Osan toll Plaza on the Seoul-Pusan Expressway. Two models, one for travel-time estimation and the other for travel-time Prediction were developed. Application cases of each model were divided into two cases, so-called, a single-region and a multiple-region. because of the different characteristics of travel behavior shown on each region. For the evaluation of the travel time estimation and Prediction models, two Parameters. i.e. mode and mean were compared using five-minute interval data sets. The test results show that mode was superior to mean in representing the relationship between speed and travel time. It is, however shown that mean value gives better results in case of insufficient data. It should be noted that the estimation and the Prediction of travel times based on the VDS data have been improved by using neural networks, because the waiting time at exit toll gates can be included for the estimation of travel time based on the VDS data by considering differences between VDS and TCS travel time Patterns in the models. In conclusion, the results show that the developed models decrease estimation and prediction errors. As a result of comparing the developed model with the existing model using the observed data, the equality coefficients of the developed model was average 88% and the existing model was average 68%. Thus, the developed model was improved minimum 17% and maximum 23% rather then existing model .