• Proceedings of the Safety Management and Science Conference
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• 2010.04a
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• pp.519-524
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• 2010

The research presents implementation strategy and features for experimental design of quality. The MINITAB models of experimental design classfies by the kinds of factors, orthogonality, blocking, confounding and rotationability. The results discussed in this paper can be easily used for practictioners.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.849-858
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• 2016

It is important to control confounding bias when estimating the causal effect of treatment in an observational study. We illustrated that the covariate selection in the causal inference is different from the variable selection in the ANCOVA model. We then investigated the three criteria of covariate selection for controlling confounding bias, which can be used when we have inadequate information to draw a complete causal graph. VanderWeele and Shpitser (2011) proposed one of them and claimed it was better than the other two. We show by example that their criterion also has limitations and some disadvantages. There is no clear winner; however, their criterion is better (if some correction is made on its condition) than the other two because it can remove the confounding bias.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.353-359
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• 1998

Factorial designs with two-level factors represent the smallest factorial experiments. The system of notation and confounding and fractional factorial schemes developed for the $2^N$system are found in standard textbooks of experimental designs. Just as in the $2^N$ system, the general confounding and fractional factorial schemes are possible in $3^N,5^N$, .... , and $\rho^N$ where $\rho$ is a prime number. Hence, we have the $\rho^N$ system. In this article, the author proposes a new algorithm for constructing fractional factorial plans in the $\rho^N$ system.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.519-527
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• 2004

Relationship between the partial likelihood ratio statistics for logisitic models and the partial goodness-of-fit statistics for corresponding log-linear models is discussed. This paper shows how definitions of suppression in logistic model can be adapted for log-linear model and how they are related to confounding in terms of collapsibility for categorical data. Several $2{times}2{times}2$ contingency tables are illustrated.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.44 no.1
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• pp.25-28
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• 2018

Objectives: This study aimed to describe recent patterns in the types of statistical test used in original articles that were published in Journal of the Korean Association of Oral and Maxillofacial Surgeons. Materials and Methods: Thirty-six original articles published in the Journal in 2015 and 2016 were ascertained. The type of statistical test was identified by one researcher. Descriptive statistics, such as frequency, rank, and proportion, were calculated. Graphical statistics, such as a histogram, were constructed to reveal the overall utilization pattern of statistical test types. Results: Twenty-two types of statistical test were used. Statistical test type was not reported in four original articles and classified as unclear in 5%. The four most frequently used statistical tests constituted 47% of the total tests and these were the chi-square test, Student's t-test, Fisher's exact test, and Mann-Whitney test in descending order. Regression models, such as the Cox proportional hazard model and multiple logistic regression to adjust for potential confounding variables, were used in only 6% of the studies. Normality tests, including the Kolmogorov-Smirnov test, Levene test, Shapiro-Wilk test, and $Scheff{\acute{e}}^{\prime}s$ test, were used diversely but in only 10% of the studies. Conclusion: A total of 22 statistical tests were identified, with four tests occupying almost half of the results. Adoption of a nonparametric test is recommended when the status of normality is vague. Adjustment for confounding variables should be pursued using a multiple regression model when the number of potential confounding variables is numerous.

• Health Policy and Management
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• v.20 no.1
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• pp.87-102
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• 2010

The objective of this study were to examine the impact of medicaid coverage expansion policy aimed at improving access to primary care. The case-control study was conducted to compare preventable hospitalization(PH) rate in new medicaid recipients versus national health insurance(NHI) enrollees form 1996 to 2001. Rates of preventable hospitalization associated with ambulatory care sensitive conditions(ACSC) were calculated and standardized by age and sex. Multinomial logit regression model was used to control the confounding factors such as age, gender and charlson comorbidity index Annual PH rates in the new medicaid increased 1.64 times after medicaid expansion, with controling confounding factors. Meanwhile, annual PH rate in the NHI increased 1.68 times during the same period, with adjusting confounding factors. Current findings suggest that the new medicaid PH rate was less likely to rise than NHI PH rate after implementing medicaid expansion. This study is expected to provide policy-relevant evidence of medicaid expansion to include population with low income.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.703-713
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• 2002

In longitudinal studies, outcomes are repeatedly measured over time for each subject. It is common to have missing values or dropouts for longitudinal data. In this study time trend in longitudinal data with dropouts is of concern. The confounding of time trend with dropout process is investigated through simulation studies. Some simulation results are reported for binary responses as well as continuous responses with patterns of dropouts varying. It has been found that time trend is not confounded with random dropout process for binary responses when it is estimated using GEE.

• Journal of Preventive Medicine and Public Health
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• v.15 no.1
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• pp.179-186
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• 1982

The methods controlling the confounding factors were discussed using the data of secondary infertility with induced abortion. Mantel-Haenszel method and logistic model were applied in the analysis to find out which factors were confounding and/or effect modification variables. In the logistic analysis, the main effect of induced abortion, spontaneous abortion, age and interaction effect between induced abortion and spontaneous abortion were chosen as independent variables being regressed into logistic functions. Spontaneons abortion was interpreted as a potential confounder and at the same time potential effect modifier and age was interpreted as potential confounder. Spontaneous abortion was shown to be more important influencing factor than age to the secondary infertility. In the course of logistic analysis, the problem of parameter estimation and hypothesis testing, assessing the fitness of a model, and selection of the best model were briefly explained. For the program of logistic model, FUNCAT Procedure of SAS package was chosen.

• Journal of dental hygiene science
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• v.17 no.5
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• pp.454-461
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• 2017

The purpose of this study was to confirm the relevance of dental health capacity and pulmonary function status. The subjects of this study were adults aged 40 years and older, who participated in pulmonary function and oral examinations. The data used for this study were raw data from the sixth Korea National Health and Nutrition Examination Survey (2013~2015). Statistical analysis was performed by analysis of complex sample survey data. The results were as follows: First, restrictive and obstructive patterns were more prevalent among males than females. They were even worse in older subjects. Approximately 67% of smokers had obstructive pattern. Second, there was a relevance between dental health capacity and pulmonary function status. The functioning teeth index, number of present teeth, and number of sound teeth (ST), which are indicators of dental health, declined with decreased pulmonary function. The number of missing teeth (MT) increased as the pulmonary function deteriorated (p<0.05). Third, the relevance between dental health capacity and pulmonary function status after stratifying the life-long smoking experience was statistically significant in the tissue health (T-health) index and ST among non-smokers. The relevance between dental health capacity and pulmonary function status after stratifying the life-long smoking experience was statistically significant (p<0.05) for the T-health index, ST, and MT among smokers. However, there was no relevance between dental health capacity and pulmonary function status after stratifying the life-long smoking experience and adjusting confounding variables. In conclusion, there was a relevance between dental health capacity and pulmonary function status after confounding variables were adjusted. However, there was no relevance between dental health capacity and pulmonary function status after stratifying the life-long smoking experience and adjusting confounding variables.

• Korean Journal of Health Education and Promotion
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• v.21 no.3
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• pp.1-17
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• 2004

The purpose of this study is to evaluate the roles of expected self-control and expected self-control results in explaining adolescents' Internet addiction. In the study model, expectations of self-control and self-control results directly determine Internet addiction and Internet use time meditates the impacts of expectations of self-control and self-control results on Internet addiction. The study subjects are 1,080 middle and high school students in Busan. Stratified cluster sampling is applied by school type and school year. The response rate is 96%(l,037cases). This study develops the scales of expected self-control and expected self-control results. The scales of Internet addiction are devised by using the concept of functional dependency such as salience, withdrawal symptoms, mood modification, tolerance, relapse, and conflict. For verifying the study model, path analysis and multiple regression models are applied for identifying path significants and evaluating confounding effects of control variables, respectively. Moreover, multi partial F-test is performed for selecting the best regression model. Expected self-control is a significant determinant of Internet addiction and Internet use time that also significantly explains Internet addiction. The total effect of expected self-control towards Internet addiction is -.95. The total effect is comprised with the direct effect (-.71) and the indirect effect(-.24). In this result, the direct effect refers a curative effect since expected self-control directly reduces the level of Internet addiction, and the indirect effect refers a preventive effect because self-control can reduce time of Internet use that is a direct determinant of Internet addiction. In the test of the confounding effects of control variables, there are no confounding effects in the models of multiple regression. It implies a robustness of the study model as regards control variables. In conclusion, improving adolescents' expected self-control can control Internet addiction level. This finding implies that a health promotion program for improving expected self-control can be a cost effective method compared to other approaches.