• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.415-445
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• 2023

Oftentimes, the time dependent treatment covariate and the time dependent confounders exist in observation studies. It is an important problem to correctly adjust for the time dependent confounders in the propensity score analysis. Recently, In the survival data, Hade et al. (2020) used a propensity score matching method to correctly estimate the treatment delay effect when the time dependent confounder affects time to the treatment time, where the treatment delay effects is defined to the delay in treatment reception. In this paper, we proposed the Cox model based marginal structural model (Cox-MSM) framework to estimate the treatment delay effect and conducted extensive simulation studies to compare our proposed Cox-MSM with the propensity score matching method proposed by Hade et al. (2020). Our simulation results showed that the Cox-MSM leads to more exact estimate for the treatment delay effect compared with two sequential matching schemes based on propensity scores. Example from study in treatment discontinuation in conjunction with simulated data illustrates the practical advantages of the proposed Cox-MSM.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.469-487
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• 2007

Grain-Size Trend Analysis is the methodology to identify net sediment transport pathways, based on the assumption that the movement of sediment from the source to deposit leaves the identifiable spatial pattern of mean, sorting, and skewness of grain size. It can easily be implemented with low cost, so it has great potentials to contribute to geomorphological research, whereas it can also be used inadequately without recognition of its limitations. This research aims to compare three established methods of grain-size trend analysis to search for the adequate way of application, and also suggest the research tasks needed in improving this methodology 1D pathway method can corporate the field experience into analyzing the pathway, provide the useful information of depositional environments through X-distribution, and identify the long-term trend effectively. However, it has disadvantage of the dependence on subjective interpretation, and a relatively coarse temporal scale. Gao-Collins's 2D transport vector method has the objective procedure, has the capability to visualize the transport pattern in 2D format, and to identify the pattern at a finer temporal scale, whereas characteristic distance and semiquantitative filtering are controversial. Le Roux's alternative 2D transport vector method has two improvement of Gao-Collins's in that it expands the empirical rules, considers the gradient of each parameters as well as the order, and has the ability to identify the pattern at a finer temporal scale, while the basic concepts are arbitrary and complicated. The application of grain sire trend analysis requires the selection of adequate method and the design of proper sampling scheme, based on the field knowledge of researcher, the temporal scale of sediment transport pattern targeted, and information needed. Besides, the relationship between the depth of sample and representative temporal scale should be systematically investigated in improving this methodology.

• Journal of agricultural medicine and community health
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• v.47 no.4
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• pp.229-241
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• 2022

Purpose: This study was attempted to identify the demographic characteristics, depression, and dietary quality of elderly patients with type 2 diabetes, and to identify the difference in food quality according to these variables. Methods: The subjects of the study were 216 elderly patients with type 2 diabetes over the age of 65 visiting elderly welfare centers and senior citizens' centers in G city and H districts. Data were collected from December 2020 to July 2021. The collected data were analyzed by descriptive statistics, t-test and one-way ANOVA using IBM SPSS Statistics 21 program. Results: There were significant differences in dietary quality according to the subject's gender, education level, residential area, spouse or not, family living together or not, subject of meal preparation, calorie requirement recognition or not, exercise practice for diabetes management or not, and depression. Depression and Fasting Blood Sugar management were important influencing factors on dietary quality, and Residence and Gender were also verified as influencing factors. Conclusions: The results of this study can be provided as basic data to establish a program to improve the quality of meals for diabetic elderly patients.