• The Journal of the Korean dental association
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• v.54 no.11
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• pp.880-896
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• 2016

The comparison of the repeated measurements is often needed to see whether they agree sufficiently, when a measurement is repeated under identical conditions by different raters. Such investigations are often analyzed inappropriately, by using correlation coefficient. The purpose of this study is to introduce statistical methods for accessing the agreement of the repeated measurements, which include Bland-Altman plot, intra class correlation, Passing-Bablok regression and Cohen's kappa coefficient, and to show how to execute them using examples.

• The Korean Journal of Pain
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• v.30 no.4
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• pp.243-249
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• 2017

Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.297-310
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• 2002

Liang and Zeger proposed generalized estimating equations(GEE) for analyzing repeated data which is discrete or continuous. GEE model can be extended to model for repeated categorical data and its estimator has asymptotic multivariate normal distribution in large sample sizes. But GEE is based on large sample asymptotic theory. In this paper, we study the properties of GEE estimators for repeated ordinal data in small sample sizes. We generate ordinal repeated measurements for two groups using two methods. Through Monte Carlo simulation studies we investigate the empirical type 1 error rates, powers, relative efficiencies of the GEE estimators, the effect of unequal sample size of two groups, and the performance of variance estimators for polytomous ordinal response variables, especially in small sample sizes.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.201-210
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• 2015

Repeated measurements on each variables of interest often arise in bioscience or medical research. We need to account for correlations among repeated measurements to assess the correlation between two variables in the presence of replication. This paper reviews methods to estimate a correlation coefficient between two variables in repeated measurements using the variance-covariance matrix of linear mixed effect models. We analyze acoustic radiation force impulse imaging (ARFI) data to assess correlation between three shear wave velocity (SWV) measurements in liver or spleen and spleen length by ultrasonography. We present how to obtain parameter estimates for the variance-covariance matrix and correlations in mixed effects models using PROC MIXED in SAS.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.331-334
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• 2004

A new measurement scheme is proposed to generate an optimized boost table for video rate LCD response time compensation. This method, which closely follows basic theory, enables up to a 90% reduction in the lookup table creation time compared to conventional methods. Furthermore, while conventional approaches require all measurements to be repeated in order to load the entire LUT whenever key parameters such as refresh rate or boost intensity are modified, the method proposed in this paper allows the new table to be calculated by utilizing saved waveform data without the need for any repeated measurements.

• International Journal of Advanced Culture Technology
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• v.11 no.3
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• pp.182-189
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• 2023

This study investigates the psychological effects of positive/negative valence order in repeated exposure to a suspenseful text. Specifically, the study seeks to understand how the order in which positive and negative elements are presented in a narrative impacts the experience of suspense, arousal, and enjoyment in readers or listeners. Using a suspenseful short story, participants were exposed to narratives with varying valence orders in a repeated-measures design. The study employed self-report questionnaires and psychophysiological measurements to capture participants' psychological responses. The results supported the hypothesis that repeated exposure impacts suspense, with negative valence enhancing suspense and arousal. Moreover, the order of valence influenced participants' psychological responses, indicating that positive valence can mitigate the impact of repeated exposure. However, the influence on enjoyment was not significant. Psychophysiological measures, specifically skin conductance level (SCL), revealed trends of habituation over repeated exposure. The findings underscore the significance of negative valence in heightening suspense and suggest directions for future research in exploring diverse factors that contribute to suspense in both fictional and real-life contexts.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.187-191
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• 2000

In the analysis of repeated measurements, multivariate regression models that account for the correlations among the observations from the same subject are widely used. Like the usual univariate regression models, these multivariate regression models also need some model diagnostic procedures. In this paper, we propose a simple graphical method to detect outliers and to investigate the goodness of model fit in repeated measures data. The graphical method is based on the quantile-quantile(Q-Q) plots of the $X^2$ distribution and the standard normal distribution. We also propose diagnostic measures to detect influential observations. The proposed method is illustrated using two examples.

• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.321-328
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• 2018

In clinical trials with repeated measurements, the time-averaged difference (TAD) may provide a more powerful evaluation of treatment efficacy than the rate of changes over time when the treatment effect has rapid onset and repeated measurements continue across an extended period after a maximum effect is achieved (Overall and Doyle, Controlled Clinical Trials, 15, 100-123, 1994). The sample size formula has been investigated by many researchers for the evaluation of TAD in two treatment groups. For the evaluation of TAD in multi-arm trials, Zhang and Ahn (Computational Statistics & Data Analysis, 58, 283-291, 2013) and Lou et al. (Communications in Statistics-Theory and Methods, 46, 11204-11213, 2017b) developed the sample size formulas for continuous outcomes and count outcomes, respectively. In this paper, we derive a sample size formula to evaluate the TAD of the repeated binary outcomes in multi-arm trials using the generalized estimating equation approach. This proposed sample size formula accounts for various correlation structures and missing patterns (including a mixture of independent missing and monotone missing patterns) that are frequently encountered by practitioners in clinical trials. We conduct simulation studies to assess the performance of the proposed sample size formula under a wide range of design parameters. The results show that the empirical powers and the empirical Type I errors are close to nominal levels. We illustrate our proposed method using a clinical trial example.

• The Journal of Advanced Prosthodontics
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• v.6 no.4
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• pp.309-316
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• 2014

PURPOSE. The color of the ceramic restorations is affected by various factors such as brand, thickness of the layered the ceramic, condensation techniques, smoothness of surface, number of firings, firing temperature and thickness of dentin. The aim of this study was to evaluate the color change and surface roughness in dental porcelain with different thicknesses during repeated firings. MATERIALS AND METHODS. Disc-shaped (N=21) metal-ceramic samples (IPS Classic; Ivoclar Vivadent; Shaar, Liechtenstein) with different thickness were exposed to repeated firings. Color measurement of the samples was made using a colorimeter and profilometer was used to determine surface roughness. ANOVA and Tukey tests with repeated measurements were used for statistical analysis. RESULTS. The total thickness of the ceramics which is less than 2 mm significantly have detrimental effect on the surface properties and color of porcelains during firings (P<.05). CONCLUSION. Repeated firings have effects on the color change and surface roughness of the dental ceramics and should be avoided.

• The Journal of Korean Medicine
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• v.38 no.4
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• pp.55-61
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• 2017

Objectives: In order to accurately measure skin moisture and accumulate normal skin moisture data, analyzing the uncertainty of the skin moisture measurement and establishing standard reference data is essential. It helps to evaluate the skin's condition and has great significance in diagnosis and treatment. In this study, the traceability of the equipment and the uncertainty of the results were analyzed for their potential use in the field of Korean medicine. The data was collected measuring skin moisture on the sole of the foot. Methods: One professional measured the moisture of the adult male's foot 10 times following a determined protocol. The standard uncertainty of repeated measurements was calculated from the mean value of 10 repeated measurements. Ten trainee participants also measured the adult male's foot following a determined protocol. The standard uncertainty by tester was calculated from the value of repeated measurements. Results: As a result of analyzing the difference between the mean and standard uncertainties in both the expert and trainees, it was confirmed that the variance in this study did not satisfy the normal distribution. In addition, the Mann-Whitney U-test was carried out, and it was found that there was no significant difference in the measured values of the two groups. The authorized uncertainty of measurements and traceability of all the equipment was not confirmed. Conclusions: This paper establishes the basis for later measurement-equipment research to provide the objective indicators to approach the dryness of plantar skin from dehydration, the Korean medicine perspective.