Semiparametric Imputation Using Conditional Gaussian Mixture Models under Item Nonresponse

Imputation is a popular technique for handling item nonresponse in survey sampling. Parametric imputation is based on a parametric model for imputation and is less robust against the failure of the imputation model. Nonparametric imputation is fully robust but is not applicable when the dimension of covariates is large due to the curse of dimensionality. Semiparametric imputation is another robust imputation based on a flexible model where the number of model parameters can increase with the sample size. In this paper, we propose another semiparametric imputation based on a more flexible model assumption than the Gaussian mixture model. In the proposed mixture model, we assume a conditional Gaussian model for the study variable given the auxiliary variables, but the marginal distribution of the auxiliary variables is not necessarily Gaussian. We show that the proposed mixture model achieves a lower approximation error bound to any unknown target density than the Gaussian mixture model in terms of the Kullback-Leibler divergence. The proposed method is applicable to high dimensional covariate problem by including a penalty function in the conditional log-likelihood function. The proposed method is applied to 2017 Korean Household Income and Expenditure Survey conducted by Statistics Korea. Supplementary material is available online

Semiparametric fractional imputation using Gaussian mixture models for handling multivariate missing data

Item nonresponse is frequently encountered in practice. Ignoring missing data can lose efficiency and lead to misleading inference. Fractional imputation is a frequentist approach of imputation for handling missing data. However, the parametric fractional imputation of Kim (2011) may be subject to bias under model misspecification. In this paper, we propose a novel semiparametric fractional imputation method using Gaussian mixture models. The proposed method is computationally efficient and leads to robust estimation. The proposed method is further extended to incorporate the categorical auxiliary information. The asymptotic model consistency and √n- consistency of the semiparametric fractional imputation estimator are also established. Some simulation studies are presented to check the finite sample performance of the proposed method

Effects of emotional labor on musculoskeletal disorders among physical therapists in Seoul

Introduction: Health care workers, including physical therapists, have some of the most important roles in the health care system as shown during the COVID-19 pandemic. Physical therapists encounter emotionally and physically vulnerable patients, experience emotional labor, and are exposed to conditions that can lead to job stress and musculoskeletal disorders. We aimed to examine the relationship between physical therapists’ emotional labor and its effect on perceived job stress and risk of musculoskeletal disorders. Methods: We conducted a 30-day survey among 230 physical therapists working in various settings from October 2 to November 1, 2019. Questionnaires, including questions on musculoskeletal symptoms, perceived job stress, and emotional labor, were administered to the participants. Results: The physical therapist's surface behavior affected the body burden. Job burnout experienced by physical therapists had an effect on their interpersonal relationships. The physical therapist's emotional law affects the degree of compensation. Conclusion: To prevent the long-term consequences of work-related strain, physical therapists should receive support in terms of maintaining a healthy lifestyle and developing effective methods of communication with patients. Encouragement of activities for psychological rejuvenation with colleagues with whom they can share emotional difficulties is also desirable. It is also necessary to establish a communication channel that can directly convey the grievances of physical therapists to hospitals

Pharmacologic Agents for Chronic Diarrhea

Chronic diarrhea is usually associated with a number of non-infectious causes. When definitive treatment is unavailable, symptomatic drug therapy is indicated. Pharmacologic agents for chronic diarrhea include loperamide, 5-hydroxytryptamine type 3 (5-HT3) receptor antagonists, diosmectite, cholestyramine, probiotics, antispasmodics, rifaximin, and anti-inflammatory agents. Loperamide, a synthetic opiate agonist, decreases peristaltic activity and inhibits secretion, resulting in the reduction of fluid and electrolyte loss and an increase in stool consistency. Cholestyramine is a bile acid sequestrant that is generally considered as the first-line treatment for bile acid diarrhea. 5-HT3 receptor antagonists have significant benefits in patients with irritable bowel syndrome (IBS) with diarrhea. Ramosetron improves stool consistency as well as global IBS symptoms. Probiotics may have a role in the prevention of antibiotic-associated diarrhea. However, data on the role of probiotics in the treatment of chronic diarrhea are lacking. Diosmectite, an absorbent, can be used for the treatment of chronic functional diarrhea, radiation-induced diarrhea, and chemotherapy-induced diarrhea. Antispasmodics including alverine citrate, mebeverine, otilonium bromide, and pinaverium bromide are used for relieving diarrheal symptoms and abdominal pain. Rifaximin can be effective for chronic diarrhea associated with IBS and small intestinal bacterial overgrowth. Budesonide is effective in both lymphocytic colitis and collagenous colitis. The efficacy of mesalazine in microscopic colitis is weak or remains uncertain. Considering their mechanisms of action, these agents should be prescribed properly

An Empirical Study of Spam and Spam Vulnerable email Accounts

Spam messages muddle up users inbox, consume network resources, and build up DDoS attacks, spread malware. Our goal is to present a definite figure about the characteristics of spam and spam vulnerable email accounts. These evaluations help us to enhance the existing technology to combat spam effectively. We collected 400 thousand spam mails from a spam trap set up in a corporate mail server for a period of 14 months form January 2006 to February 2007. Spammers use common techniques to spam end users regardless of corporate server and public mail server. So we believe that our spam collection is a sample of world wide spam traffic. Studying the characteristics of this sample helps us to better understand the features of spam and spam vulnerable e-mail accounts. We believe that this analysis is highly useful to develop more efficient anti spam techniques. In our analysis we classified spam based on attachment and contents. According to our study the four years old heavy users email accounts attract more spam than four years oldlight users mail accounts. The 14 months old relatively new email accounts don't receive spam. In some special cases like DDoS attacks, the new email accounts receive spam. During DDoS attack 14 months old heavy users email accounts have attracted more number of spam than 14 months old light users mail accounts.Comment: 6 pages, 5 Figures, FGCN 2007, IEEE C