• Survey Research
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• v.11 no.2
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• pp.1-28
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• 2010

This paper reports the results of the 2009 Internet volunteer panel version of the social survey conducted by Statistics Korea (Korea National Statistical Office). Authors identify socio-psychological characteristics of Internet survey volunteers and present quantitative evaluation of the propensity adjustment weighting method intended to remove Internet sample bias. The nine criteria used for propensity adjustment were regions, urban/rural, gender, age, education, consumer satisfaction, views on income distribution, newspaper access and Internet news access. Propensity adjustment weighting based on the logit model and rim weights were applied to the online survey of 2,903 respondents using the face-to-face area sample data of 37,049 respondents as reference. A total of 106 items were used for evaluating the propensity adjustment weighting methods. The results showed that in 80% of survey items the propensity adjustment weighting yielded better estimates compared to simple demographic weighting. This suggests that Internet surveys by volunteer panels are useful for conducting the general social study in Korea. The reference survey data for this study contains several items on social-psychological behaviors and attitudes, is large in size and obtained by probability sampling. Thus it may be utilized in propensity adjustment of other Internet surveys.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.103-113
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• 2009

Weighting is a common form of unit nonresponse adjustment in sample surveys where entire questionnaires are missing due to noncontact or refusal to participate. A common approach computes the response weight as the inverse of the response rate within adjustment cells based on covariate information. In this paper, we consider the efficiency and robustness of nonresponse weight adjustment bated on the response propensity and predictive mean. In the simulation study based on 2000 Fishry Census in Korea, the root mean squared errors for assessing the various ways of forming nonresponse adjustment cell s are investigated. The simulation result suggest that the most important feature of variables for inclusion in weighting adjustment is that they are predictive of survey outcomes. Though useful, prediction of the propensity to response is a secondary. Also the result suggest that adjustment cells based on joint classification by the response propensity and predictor of the outcomes is productive.

• Survey Research
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• v.10 no.3
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• pp.21-36
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• 2009

This study suggests the applicability of web surveys regarding elections in order to contact a great number of young people. The propensity weighting model was estimated using the demographic variables and the covariate variables collected during the 2007 presidential election surveys. In order to adjust the internet survey to the telephone survey, we used the propensity score method. Propensity score weighting made the internet survey results closer to the telephone survey results. This shows that an internet survey with propensity weighting model is a potential alternative survey method in the prediction of elections.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.217-227
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• 2015

In observational study, handling confounders is a primary issue in measuring treatment effect of interest. Historically, a regression with covariate adjustment (covariate-adjusted regression) has been the typical approach to estimate treatment effect incorporating potential confounders into model. However, ever since the introduction of the propensity score, covariate-adjusted regression has been gradually replaced in medical literatures with various balancing methods based on propensity score. On the other hand, there is only a paucity of researches assessing propensity score methods compared with the covariate-adjusted regression. This paper examined the performance of propensity score methods in estimating risk difference and compare their performance with the covariate-adjusted regression by a Monte Carlo study. The study demonstrated in general the covariate-adjusted regression with variable selection procedure outperformed propensity-score-based methods in terms both of bias and MSE, suggesting that the classical regression method needs to be considered, rather than the propensity score methods, if a performance is a primary concern.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.55-66
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• 2010

Propensity score adjustment(PSA) has been suggested as approach to adjustment for volunteer internet survey. PSA attempts to decrease the biases arising from noncoverage and nonprobability sampling in volunteer panel internet surveys. Although PSA is an appealing method, its application for internet survey regarding Korea presidential election and its effectiveness is not well investigated. In this study, we compare the Ni Korea internet survey with the telephone survey conducted by MBMR and KBS for 2007 Korean presidential election. The result of study show that the accuracy of internet survey can be improved by using PSA. And it is critical to include covariates that highly related to the voting tendency and the role of nondemographic variables seems important to improving PSA for Korea presidential election prediction.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.655-664
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• 2015

A nonresponse adjusted raking ratio estimator that consists of weighting adjustment using estimated response probability and raking procedure is often used to reduce the nonresponse bias and keep the calibration property of the estimator. We investigated asymptotic properties of nonresponse adjusted raking ratio estimator and proposed a variance estimator. A simulation study is used to examine the performance of suggested estimators.

• Korean Journal of Radiology
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• v.24 no.12
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• pp.1284-1292
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• 2023

Objective: We investigated the impacts of computed tomography (CT) added to ultrasound (US) for preoperative evaluation of patients with papillary thyroid carcinoma (PTC) on staging, surgical extent, and postsurgical survival. Materials and Methods: Consecutive patients who underwent surgery for PTC between January 2015 and December 2015 were retrospectively identified. Of them, 584 had undergone preoperative additional thyroid CT imaging (CT + US group), and 859 had not (US group). Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were used to adjust for 14 variables and balance the two groups. Changes in nodal staging and surgical extent caused by CT were recorded. The recurrence-free survival and distant metastasis-free survival after surgery were compared between the two groups. Results: In the CT + US group, discordant nodal staging results between CT and US were observed in 94 of 584 patients (16.1%). Of them, CT accurately diagnosed nodal staging in 54 patients (57.4%), while the US provided incorrect nodal staging. Ten patients (1.7%) had a change in the extent of surgery based on CT findings. Postsurgical recurrence developed in 3.6% (31 of 859) of the CT + US group and 2.9% (17 of 584) of the US group during the median follow-up of 59 months. After adjustment using IPTW (580 vs. 861 patients), the CT + US group showed significantly higher recurrence-free survival rates than the US group (hazard ratio [HR], 0.52 [95% confidence interval {CI}, 0.29-0.96]; P = 0.037). PSM analysis (535 patients in each group) showed similar HR without statistical significance (HR, 0.60 [95% CI, 0.31-1.17]; P = 0.134). For distant metastasis-free survival, HRs after IPTW and PSM were 0.75 (95% CI, 0.17-3.36; P = 0.71) and 0.87 (95% CI, 0.20-3.80; P = 0.851), respectively. Conclusion: The addition of CT imaging for preoperative evaluation changed nodal staging and surgical extent and might improve recurrence-free survival in patients with PTC.

• Journal of Chest Surgery
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• v.57 no.3
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• pp.242-251
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• 2024

Background: This study compared the outcomes of surgical aortic valve replacement (AVR) in patients aged 50 to 70 years based on the type of prosthetic valve used. Methods: We compared patients who underwent mechanical AVR to those who underwent bioprosthetic AVR at our institution between January 2000 and March 2019. Competing risk analysis and the inverse probability of treatment weighting (IPTW) method based on propensity score were employed for comparisons. Results: A total of 1,580 patients (984 patients with mechanical AVR; 596 patients with bioprosthetic AVR) were enrolled. There was no significant difference in early mortality between the mechanical AVR and bioprosthetic AVR groups (0.9% vs. 1.7%, p=0.177). After IPTW adjustment, the risk of all-cause mortality was significantly higher in the bioprosthetic AVR group than in the mechanical AVR group (hazard ratio [HR], 1.39; 95% confidence interval [CI], 1.07-1.80; p=0.014). Competing risk analysis revealed lower risks of stroke (sub-distributional hazard ratio [sHR], 0.44; 95% CI, 0.28-0.67; p<0.001) and anticoagulation-related bleeding (sHR, 0.35; 95% CI, 0.23-0.53; p<0.001) in the bioprosthetic AVR group. Conversely, the risk of aortic valve (AV) reintervention was higher in the bioprosthetic AVR group (sHR, 6.14; 95% CI, 3.17-11.93; p<0.001). Conclusion: Among patients aged 50 to 70 years who underwent surgical AVR, those receiving mechanical valves showed better survival than those with bioprosthetic valves. The mechanical AVR group exhibited a higher risk of stroke and anticoagulation-related bleeding, while the bioprosthetic AVR group showed a higher risk of AV reintervention.