• Title/Summary/Keyword: Statistical errors

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Trends in statistical methods in articles published in Archives of Plastic Surgery between 2012 and 2017

  • Han, Kyunghwa;Jung, Inkyung
    • Archives of Plastic Surgery
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    • v.45 no.3
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    • pp.207-213
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    • 2018
  • This review article presents an assessment of trends in statistical methods and an evaluation of their appropriateness in articles published in the Archives of Plastic Surgery (APS) from 2012 to 2017. We reviewed 388 original articles published in APS between 2012 and 2017. We categorized the articles that used statistical methods according to the type of statistical method, the number of statistical methods, and the type of statistical software used. We checked whether there were errors in the description of statistical methods and results. A total of 230 articles (59.3%) published in APS between 2012 and 2017 used one or more statistical method. Within these articles, there were 261 applications of statistical methods with continuous or ordinal outcomes, and 139 applications of statistical methods with categorical outcome. The Pearson chi-square test (17.4%) and the Mann-Whitney U test (14.4%) were the most frequently used methods. Errors in describing statistical methods and results were found in 133 of the 230 articles (57.8%). Inadequate description of P-values was the most common error (39.1%). Among the 230 articles that used statistical methods, 71.7% provided details about the statistical software programs used for the analyses. SPSS was predominantly used in the articles that presented statistical analyses. We found that the use of statistical methods in APS has increased over the last 6 years. It seems that researchers have been paying more attention to the proper use of statistics in recent years. It is expected that these positive trends will continue in APS.

DIMENSIONAL ACCURACY OF DENTURE BASE USING LASER SCANNER OF REVERSE ENGINEERING TECHNIC (Reverse Engineering 기법의 레이저 스캐너를 이용한 의치상의 정확도에 관한 연구)

  • Lee, Si-Hyuk;Chang, Ik-Tae;Yim, Soon-Ho
    • The Journal of Korean Academy of Prosthodontics
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    • v.37 no.2
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    • pp.167-184
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    • 1999
  • The purpose of this study was to evaluate and compare the at of denture bases processed by injection pressing technic using laser scanner of reverse engineering technic. The auther duplicated 20 maxillary edentulous models and 20 mandibular edentulous models, which were scanned on HYSCAN 45C 3D BCANNER(Hymarc Co., Canada). The scanned data were stored in the personal computer using SURFACER (Imageware Co. U.S.A.) software program. After 40 dentures were cured by PERform Inkovac system, SR-Ivocap system, Palajet system, and Sulfon system, they were stored in water at room temperature fir 24 hours. The dentures were scanned on HYSCAN 45C 3D SCANNER(Hymarc Co., Canada). The scanned data were stored in the personal computer using SURFACER (Imageware Co., U.S.A.) software program. By overlapping two images using the same program, the fit between two surfaces was scaled by positive and negative errors. The obtained results were as follows 1. In the upper denture, most of the positive errors occurred on the lingual side of anterior alveolar ridge and the negative errors were on the flange of denture bases. 2. In the lower denture, most of the positive errors occurred on the inner side of lingual flange and the negative errors were on the border of anterior labial flange areas, 3. There were no statistical differences among the positive errors of the four types of injection denture curing methods and also no statistical differences between negative errors except only in negative maximum errors. 4. In PERform system and SR-Ivocap system, they have the tendency of inaccurate at of lower denture bases comparing to that of upper denture bases. 5. The negative error scales were greater than the positive error scales in all types of injection denture curing methods.

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Evaluation of Statistical Analysis of Radiologist's Journal: Focus on Journal of Korean Society of Computer Tomographic Technology (방사선사 학술지에 게재된 통계방법 분석: 대한전산화단층기술학회지 중심으로)

  • Kim, Sang-Hyun;Lee, Mi-Hwa
    • Journal of Digital Convergence
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    • v.12 no.9
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    • pp.275-282
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    • 2014
  • The aim of this study was to investigate the statistical trend and errors of articles in the journal of Korean society of computed tomographic technology for contribution to the academic development of the professional society. Preliminary findings indicate that there are various statistical errors in the papers in the journal of Korean society of computed tomographic technology. Results suggest that the statistical education needs to be strengthened from university education to instructional course lecture of academic society. The improvement of the quality of the paper by improving awareness of the statistical error.

Analysis on Reports of Statistical Testings for Mean Differences (차이검정을 이용한 논문의 통계활용 분석)

  • Chung, Chae-Weon;Kim, Jeung-Im;Park, Hye-Sook;Ahn, Suk-Hee;Cho, Dong-Sook;Park, So-Mi
    • Women's Health Nursing
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    • v.13 no.3
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    • pp.211-218
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    • 2007
  • Purpose: This study aimed to evaluate the accuracy and adequacy of research papers reporting statistical testings for mean differences. Methods: Original research articles utilized t-test, Chi-square test, and ANOVA were reviewed from Korean Journal of Women Health Nursing published from the year 2004 to 2006. Seventy-six papers were evaluated in accordance with formatted criteria in respect to an inclusiveness of research title, accuracy of statistical methods and presentation styles, and errors in reporting statistical outcomes. Results: Research titles were quite comprehensive, however overall accuracy of statistical values and basic formats reached only 60 to 80% by items. Details of the presentation in the reporting of outcomes were not complied with the guidelines, which need careful concerns of the writers. Errors of English in table presentation were found in more than 30% of the papers. Conclusion: The outcome would be reflected in the submission guidelines for future writers. To reach the level comparable with internationally recognized nursing journals, concrete knowledge to apply statistical methods should be ensured in the processes of submission, reviews, and editing.

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Monotone Likelihood Ratio Property of the Poisson Signal with Three Sources of Errors in the Parameter

  • Kim, Joo-Hwan
    • Communications for Statistical Applications and Methods
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    • v.5 no.2
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    • pp.503-515
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    • 1998
  • When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector, it follows approximately Poisson distribution. Under the four assumptions in the presence of errors and uncertainties for the Poisson parameters, an exact probability distribution of neutral particles have been derived. The probability distribution for the neutron signals received by a detector averaged over the three sources of errors is expressed as a four-dimensional integral of certain data. Two of the four integrals can be evaluated analytically and thereby the integral is reduced to a two-dimensional integral. The monotone likelihood ratio(MLR) property of the distribution is proved by using the Cauchy mean value theorem for the univariate distribution and multivariate distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem related to the distribution.

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PRELIMINARY DETECTION FOR ARCH-TYPE HETEROSCEDASTICITY IN A NONPARAMETRIC TIME SERIES REGRESSION MODEL

  • HWANG S. Y.;PARK CHEOLYONG;KIM TAE YOON;PARK BYEONG U.;LEE Y. K.
    • Journal of the Korean Statistical Society
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    • v.34 no.2
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    • pp.161-172
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    • 2005
  • In this paper a nonparametric method is proposed for detecting conditionally heteroscedastic errors in a nonparametric time series regression model where the observation points are equally spaced on [0,1]. It turns out that the first-order sample autocorrelation of the squared residuals from the kernel regression estimates provides essential information. Illustrative simulation study is presented for diverse errors such as ARCH(1), GARCH(1,1) and threshold-ARCH(1) models.

DEFAULT BAYESIAN INFERENCE OF REGRESSION MODELS WITH ARMA ERRORS UNDER EXACT FULL LIKELIHOODS

  • Son, Young-Sook
    • Journal of the Korean Statistical Society
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    • v.33 no.2
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    • pp.169-189
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    • 2004
  • Under the assumption of default priors, such as noninformative priors, Bayesian model determination and parameter estimation of regression models with stationary and invertible ARMA errors are developed under exact full likelihoods. The default Bayes factors, the fractional Bayes factor (FBF) of O'Hagan (1995) and the arithmetic intrinsic Bayes factors (AIBF) of Berger and Pericchi (1996a), are used as tools for the selection of the Bayesian model. Bayesian estimates are obtained by running the Metropolis-Hastings subchain in the Gibbs sampler. Finally, the results of numerical studies, designed to check the performance of the theoretical results discussed here, are presented.

A General Procedure for Estimating the General Parameter Using Auxiliary Information in Presence of Measurement Errors

  • Singh, Housila P.;Karpe, Namrata
    • Communications for Statistical Applications and Methods
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    • v.16 no.5
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    • pp.821-840
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    • 2009
  • This article addresses the problem of estimating a family of general population parameter ${\theta}_{({\alpha},{\beta})}$ using auxiliary information in the presence of measurement errors. The general results are then applied to estimate the coefficient of variation $C_Y$ of the study variable Y using the knowledge of the error variance ${\sigma}^2{_U}$ associated with the study variable Y, Based on large sample approximation, the optimal conditions are obtained and the situations are identified under which the proposed class of estimators would be better than conventional estimator. Application of the main result to bivariate normal population is illustrated.

Partially linear multivariate regression in the presence of measurement error

  • Yalaz, Secil;Tez, Mujgan
    • Communications for Statistical Applications and Methods
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    • v.27 no.5
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    • pp.511-521
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    • 2020
  • In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors.

Wavelet Estimation of Regression Functions with Errors in Variables

  • Kim, Woo-Chul;Koo, Ja-Yong
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.849-860
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    • 1999
  • This paper addresses the issue of estimating regression function with errors in variables using wavelets. We adopt a nonparametric approach in assuming that the regression function has no specific parametric form, To account for errors in covariates deconvolution is involved in the construction of a new class of linear wavelet estimators. using the wavelet characterization of Besov spaces the question of regression estimation with Besov constraint can be reduced to a problem in a space of sequences. Rates of convergence are studied over Besov function classes $B_{spq}$ using $L_2$ error measure. It is shown that the rates of convergence depend on the smoothness s of the regression function and the decay rate of characteristic function of the contaminating error.

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