1.The directionality of measurement bias: a directed acyclic graph-based structural perspective.
Yi Jie LI ; Yan Min CAO ; Wei FAN ; Miao ZHANG ; Li Li LIU ; Ying Jie ZHENG
Chinese Journal of Epidemiology 2023;44(4):643-649
Measurement bias (MB) has been described in causal structures but is still not entirely clear. In practice, the correctness of substitution estimate (SE) of effect is a prerequisite for causal inference, usually based on a bidirectionally non-differential misclassification between the measured exposure and the measured outcome. Based on a directed acyclic graph (DAG), this paper proposes a structure for the single-variable measure, where its MB is derived from the choice of an imperfect, "input/output device-like" measurement system. The MB of the SE is influenced both by the measurement system itself and by factors outside the measurement system: while the independence or dependence mechanism of the measurement system still ensures that the MB of the SE is bidirectionally non-differential; however, the misclassification can be bidirectionally non-differential, unidirectionally differential, or bidirectionally differential resulted from the factors outside the measurement system. In addition, reverse causality should be defined at the level of measurement, where measured exposures can influence measured outcomes and vice versa. Combined with temporal relationships, DAGs help elucidate MB's structures, mechanisms, and directionality.
Humans
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Confounding Factors, Epidemiologic
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Data Interpretation, Statistical
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Bias
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Causality
2.Statistical notes for clinical researchers: the independent samples t-test
Restorative Dentistry & Endodontics 2019;44(3):e26-
No abstract available.
Statistics as Topic
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Models, Statistical
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Data Interpretation, Statistical
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Sampling Studies
;
Biometry
3.Endovascular Treatments Performed Collaboratively by the Society of Korean Endovascular Neurosurgeons Members: A Nationwide Multicenter Survey
Tae Gon KIM ; Oki KWON ; Yong Sam SHIN ; Jae Hoon SUNG ; Jun Seok KOH ; Bum Tae KIM
Journal of Korean Neurosurgical Society 2019;62(5):502-518
OBJECTIVE: Since less invasive endovascular treatment was introduced to South Korea in 1994, a considerable proportion of endovascular treatments have been performed by neuroradiology doctors, and endovascular treatments by vascular neurosurgeons have recently increased. However, few specific statistics are known regarding how many endovascular treatments are performed by neurosurgeons. Thus, authors compared endovascular treatments collaboratively performed by vascular neurosurgeons with all cases throughout South Korea from 2013 to 2017 to elucidate the role of neurosurgeons in the field of endovascular treatment in South Korea.METHODS: The Society of Korean Endovascular Neurosurgeons (SKEN) has issued annual reports every year since 2014. These reports cover statistics on endovascular treatments collaboratively or individually performed by SKEN members from 2013 to 2017. The data was requested and collected from vascular neurosurgeons in various hospitals. The study involved 77 hospitals in its first year, and 100 in its last. National statistics on endovascular treatment from all over South Korea were obtained from the Healthcare Bigdata Hub website of the Health Insurance Review & Assessment Service based on the Electronic Data Interchange (EDI) codes (in the case of intra-arterial (IA) thrombolysis, however, statistics were based on a combination of the EDI and I63 codes, a cerebral infarction disease code) from 2013 to 2017. These two data sets were directly compared and the ratios were obtained.RESULTS: Regionally, during the entire study period, endovascular treatments by SKEN members were most common in Gyeonggi-do, followed by Seoul and Busan. Among the endovascular treatments, conventional cerebral angiography was the most common, followed by cerebral aneurysmal coiling, endovascular treatments for ischemic stroke, and finally endovascular treatments for vascular malformation and tumor embolization. The number of endovascular treatments performed by SKEN members increased every year.CONCLUSION: The SKEN members have been responsible for the major role of endovascular treatments in South Korea for the recent 5 years. This was achieved through the perseverance of senior members who started out in the midst of hardship, the establishment of standards for the training/certification of endovascular neurosurgery, and the enthusiasm of current SKEN members who followed. To provide better treatment to patients, we will have to make further progress in SKEN.
Busan
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Cerebral Angiography
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Cerebral Infarction
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Data Interpretation, Statistical
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Dataset
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Delivery of Health Care
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Endovascular Procedures
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Gyeonggi-do
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Humans
;
Insurance, Health
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Intracranial Aneurysm
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Korea
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Neurosurgeons
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Neurosurgery
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Seoul
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Stroke
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Vascular Malformations
4.Incidence of Colon Cancer Related to Cigarette Smoking and Alcohol Consumption in Adults with Metabolic Syndrome: Prospective Cohort Study
Journal of Korean Academy of Nursing 2019;49(6):713-723
PURPOSE: The purpose of this study was to identify the impact of cigarette smoking and alcohol consumption on the incidence of colon cancer in adults with metabolic syndrome.METHODS: This study employed a longitudinal study design and utilized secondary data drawn from the Korean Genome and Epidemiology Study (KoGES). The data of a sample of 2,327 adults with metabolic syndrome tracked every two years from 2001 to 2014 were used in this study. Statistical data analyses of the frequency, number of cases per 100,000 person-years, log-rank test, Kaplan-Meier curve, and Cox's proportional hazards regression were performed using IBM SPSS statistics version 24.RESULTS: During the observation period, the number of colon cancer cases was 46, and the total person-years were 252,444. The incidence of colon cancer was higher in current, over 10 pack-year smokers when compared to non-smokers (hazard ratio=3.38, 95% confidence interval=1.09~8.42).CONCLUSION: Excessive and long-term smoking should be avoided to prevent colon cancer, especially in adults with metabolic syndrome, since it might exacerbate the risk factors of colon cancer. Particularly, health professionals need to provide individualized smoking cessation interventions to those at high risk of colon cancer.
Adult
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Alcohol Drinking
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Cohort Studies
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Colon
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Colonic Neoplasms
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Data Interpretation, Statistical
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Epidemiology
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Genome
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Health Occupations
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Humans
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Incidence
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Kaplan-Meier Estimate
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Longitudinal Studies
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Prospective Studies
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Risk Factors
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Smoke
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Smoking Cessation
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Smoking
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Tobacco Products
5.Multicollinearity and misleading statistical results
Korean Journal of Anesthesiology 2019;72(6):558-569
Multicollinearity represents a high degree of linear intercorrelation between explanatory variables in a multiple regression model and leads to incorrect results of regression analyses. Diagnostic tools of multicollinearity include the variance inflation factor (VIF), condition index and condition number, and variance decomposition proportion (VDP). The multicollinearity can be expressed by the coefficient of determination (R(h)²) of a multiple regression model with one explanatory variable (X(h)) as the model’s response variable and the others (X(i) [i≠h] as its explanatory variables. The variance (σ(h)²) of the regression coefficients constituting the final regression model are proportional to the VIF(1/1−R(h)²). Hence, an increase in R(h)² (strong multicollinearity) increases σ(h)². The larger σ(h)² produces unreliable probability values and confidence intervals of the regression coefficients. The square root of the ratio of the maximum eigenvalue to each eigenvalue from the correlation matrix of standardized explanatory variables is referred to as the condition index. The condition number is the maximum condition index. Multicollinearity is present when the VIF is higher than 5 to 10 or the condition indices are higher than 10 to 30. However, they cannot indicate multicollinear explanatory variables. VDPs obtained from the eigenvectors can identify the multicollinear variables by showing the extent of the inflation of σ(h)² according to each condition index. When two or more VDPs, which correspond to a common condition index higher than 10 to 30, are higher than 0.8 to 0.9, their associated explanatory variables are multicollinear. Excluding multicollinear explanatory variables leads to statistically stable multiple regression models.
Bias (Epidemiology)
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Biostatistics
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Data Interpretation, Statistical
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Inflation, Economic
6.How to Increase Your “Power”
Hip & Pelvis 2018;30(1):1-4
No abstract available.
Data Accuracy
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Data Interpretation, Statistical
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Statistics as Topic
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Biomedical Research
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Analysis of Variance
7.A Statistical Analysis on Forensic Autopsies Performed in Korea in 2016
Ji Hye PARK ; Joo Young NA ; Bong Woo LEE ; Young Shik CHOI
Korean Journal of Legal Medicine 2018;42(1):8-21
A statistical analysis was performed on national forensic autopsy data collected in the Republic of Korea during 2016 to overcome regional limitations and limitations from the number of unusual deaths as reported in the literature over the previous year. A total of 8,335 cases were categorized based on the region, based on requests by the Police Agency and the Coast Guard, gender, age, manner of death, and cause of death. Analysis of the manner of death revealed that 4,028 cases (48.3%) were of unnatural death, 3,447 cases (41.4%) were of natural death, and 860 cases (10.3%) were of unknown death. Among the unnatural deaths, the majority of the manner of deaths (1,584 cases, 39.3%) was accidents, 1,378 cases (34.2%) were suicides, 428 cases (10.6%) were homicides, and 638 cases (15.8%) were undetermined deaths. Among the unnatural deaths, the majority of the cause of deaths (1,518 cases, 37.7%) was due to trauma, followed by 827 cases (20.5%) of poisoning and 732 cases (18.2%) of asphyxia. Falling was the major cause of death by trauma (668 cases, 44.0%). Based on a previous study about asphyxia, strangulation was the major cause, with 569 cases (77.7%). Among the natural deaths, heart disease was the major cause (1,727 cases, 50.1%), followed by vascular disease (587 cases, 17.0%).
Accidental Falls
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Asphyxia
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Autopsy
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Cause of Death
;
Data Interpretation, Statistical
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Heart Diseases
;
Homicide
;
Humans
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Korea
;
Military Personnel
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Poisoning
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Police
;
Republic of Korea
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Suicide
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Vascular Diseases
8.Study for Lists of Forensic Autopsy Request: Quantitative Analysis about Documents Relating to Autopsy Request
Ji Hye PARK ; Joo Young NA ; Bo Young LEE ; Song Hee SONG
Korean Journal of Legal Medicine 2018;42(2):39-43
In the Republic of Korea, relevant documents are submitted to forensic doctors or agencies when courts grant confiscation warrants for autopsy. If the essential data on unusual death are not submitted at the time of the autopsy, it may be difficult to properly understand the situation relating to an unusual death prior to the autopsy, thus reducing the accuracy of the autopsy. As many as 6,133 out of 6,610 autopsy data (92.8%) in the Republic of Korea in 2015 were analyzed. Most autopsy appraisal requests (99.8%) were submitted. Unusual death occurrence reports (86.0%) and command recommendations of unusual death (70.3%) were submitted in many cases. However, prosecutor commands on unusual death were submitted only in 27.8% cases, and confiscation warrants were not submitted in 7.4% cases. As for postmortem inspection and death scene investigation reports, 29.3% and 34.1% cases were submitted, respectively. In addition to the above two documents, death certificates and records of statement of a relative had significant regional variations (0.3%–80.1%, 3.1%–64.7%, 27.8%–81.3%, and 40.8%–96.8%, respectively). For postmortem inspection and death scene photos, 2.7% and 3.2% were submitted in black-and-white photographs, respectively. The authors propose a list of forensic autopsy requests including autopsy appraisal requests, unusual death occurrence reports, command recommendations of unusual deaths, prosecutor commands on unusual death, and confiscation warrants unconditionally, as an essential document reflecting the progress of investigations. We suggest that postmortem inspection reports and photos, death scene investigation reports and photos, and death certificates should be included as part of postmortem investigation data.
Autopsy
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Data Interpretation, Statistical
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Death Certificates
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Financing, Organized
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Korea
;
Republic of Korea
9.A Statistical Analysis on Forensic Autopsies Performed in Korea in 2017
Ji Hye PARK ; Joo Young NA ; Bong Woo LEE ; Kyung Moo YANG ; Young Shik CHOI
Korean Journal of Legal Medicine 2018;42(4):111-125
Statistical analysis was performed on national forensic autopsy data collected in the Republic of Korea, with the exception of Ulsan, during 2017. A total of 8,777 cases were categorized based on the region; information was provided by the Police Agency and the Coast Guard regarding sex, age, manner of death, and cause of death. Analysis of the manner of death revealed that 3,971 cases (45.2%) were unnatural deaths, 3,679 cases (41.9%) were natural deaths, and 1,127 cases (12.8%) were unknown deaths. Among the unnatural deaths, the majority of the cases (1,740 cases, 43.8%) were accidents, 1,316 cases (33.1%) were suicide, 385 cases (9.7%) were homicide, and 530 cases (13.3%) were undetermined deaths. Among the unnatural deaths, the majority of the cases (1,575 cases, 39.7%) were trauma, followed by 793 cases (20.0%) of poisoning and 689 cases (17.4%) of asphyxia. Falling down was the major cause of death by trauma (737 cases, 46.8%). As a result of the classification of asphyxia based on previous study, strangulation was the major cause, with 538 cases (78.1%). Among the natural deaths, heart disease was the major cause (1,790 cases, 48.7%), followed by vascular disease (697 cases, 18.9%).
Accidental Falls
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Asphyxia
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Autopsy
;
Cause of Death
;
Classification
;
Data Interpretation, Statistical
;
Heart Diseases
;
Homicide
;
Humans
;
Korea
;
Military Personnel
;
Poisoning
;
Police
;
Republic of Korea
;
Suicide
;
Ulsan
;
Vascular Diseases
10.Statistical notes for clinical researchers: covariance and correlation
Restorative Dentistry & Endodontics 2018;43(1):e4-
No abstract available.
Data Interpretation, Statistical
;
Biometry
;
Factor Analysis, Statistical
;
Models, Statistical
;
Regression Analysis

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