Bias is the main problem that should be considered in epidemiologic research. Information bias caused by measurement error and confounding caused by total energy intake are listed as the main biases in nutritional epidemiology and the concept, fact and the methods for adjusting effects of these biases are discussed. The biases which can be caused during the nutritional epidemiologic research process are listed and discussed. The pros and cons of the continuous data and categorical data of the nutrients and the ways how to categorize the data are reviewed. During the analysis of food and nutrient data, multiple comparison and publication bias are prone to be encountered, and these should be considered in interpretation of the results. Understanding of the biases will lead us to make valuable nutritional epidemiologic research and these lead the application of the research results to control the prevalent noncommunicable diseases.
Bias (Epidemiology)* ; Energy Intake ; Epidemiology* ; Publication Bias

PURPOSE: This study was conducted to meta-analyze the effects of hardiness on health-related variables. METHOD: After review of 19 studies performed by Korean nurses, research variables, statistical data(r or F), and other methodological data were extracted and coded. Research variables were categorized under 5 groups such as health-related behavior, well-being, adaptation, stress, and support according to conceptual similarity. Using SAS program, 20 research variables and 34 effect sizes were calculated after eliminating heterogeneous data by Q-test, RESULTS: Effects of hardiness on whole research variables was .512 and ranged from .322 to .643 by categories. The greatest effect was obtained from well-being category, whereas the smallest effect from stress category. All effect sizes were statistically significant. But fail-safe numbers were small and failed to achieve reasonable tolerance level. CONCLUSION: Results of meta-analysis indicated that hardiness has a moderate effect on health-related variables. But for improving the reliability of the results by minimizing publication bias, the more hardiness studies should be done.
Nursing Research* ; Nursing* ; Publication Bias

China ; Duplicate Publication as Topic ; Periodicals as Topic ; Publication Bias

To make updated and unbiased answers to a clinical question, it is essential to effectively and efficiently search the medical literature. The goal of medical literature searching is comprehensive and transparent and is a replicable procedure to get correct conclusions to the question. To do this, each user should make well formulated clinical questions, and have knowledge on what specific characteristics each database has. There are several readily accessible English databases that provide literature information including PubMed, EMBASE, and CINAHL. The Korean medical literature database including Koreamed and KMBase are also available. Users can search information through formulated search terms such as in MeSH in Pubmed. Skills in finding and using search terms are essential in effective searching. Also knowledge on using filters is frequently needed to search database quickly for articles on several study designs. After running a search in the database, one needs to retrieve search results effectively. In comprehensive literature search, especially for writing a systematic review, one needs to include literature to overcome and minimize publication bias. This process often requires searching in gray literature, and the common types and sources of publication bias are described. Finally, we need to constantly validate search results, and revise the search through a continuous process. In this article, the basic concepts and procedures of searching medical literature are described.
Literature Based Discovery ; Publication Bias ; Running ; Writing

OBJECTIVES: This study was designed to integrate the results of community based studies which assessed a relationship between depression and alcoholism by meta-analysis. METHODS: We identified the previons studies and included in meta-analysis by searching MEDLINE. Overall, 21 results of the studies for relationship between depression and alcoholism were selected for quantitative meta-analysis. Before the integration of the each effect size of the relationship between depression and alcoholism, a homogeneity test was conducted. For the publication bias, we also conducted the analyses of funnel plot, normal quantile plot, rank correlation test and the fail-safe n. RESULTS: We used the random effect model to estimate the overall effect size, because the homogeneity of studies was rejected in a fixed effect model. Our quantitative meta-analysis yielded that integrated odds ratio between depression and alcoholism was 2.42 (95% C.I. 1.98-2.97). From the results of analyses of the publication bias, the probability of publication bias is considered low. CONCLUSION: The published evidences suggested that there may be a significant positive relationship between depression and alcoholism.
Alcoholism* ; Depression* ; Odds Ratio ; Publication Bias

OBJECTIVES: This study was designed to integrate the results of community based studies which assessed a relationship between depression and alcoholism by meta-analysis. METHODS: We identified the previons studies and included in meta-analysis by searching MEDLINE. Overall, 21 results of the studies for relationship between depression and alcoholism were selected for quantitative meta-analysis. Before the integration of the each effect size of the relationship between depression and alcoholism, a homogeneity test was conducted. For the publication bias, we also conducted the analyses of funnel plot, normal quantile plot, rank correlation test and the fail-safe n. RESULTS: We used the random effect model to estimate the overall effect size, because the homogeneity of studies was rejected in a fixed effect model. Our quantitative meta-analysis yielded that integrated odds ratio between depression and alcoholism was 2.42 (95% C.I. 1.98-2.97). From the results of analyses of the publication bias, the probability of publication bias is considered low. CONCLUSION: The published evidences suggested that there may be a significant positive relationship between depression and alcoholism.
Alcoholism* ; Depression* ; Odds Ratio ; Publication Bias

BACKGROUND/AIMS: To evaluate the therapeutic outcomes of the endoscopic submucosal dissection (ESD) technique for the treatment of gastric subepithelial tumors (SETs). METHODS: A systematic literature review was conducted using the core databases. Data on the complete resection rates and the procedure-related perforation rates were extracted and analyzed. A random effects model was then applied for this meta-analysis. RESULTS: In all, 288 patients with 290 SETs were enrolled from nine studies (44 SETs originated from the submucosal layer; 246 SETs originated from the muscularis propria layer). The mean diameter of the lesions ranged from 17.99 to 38 mm. Overall, the pooled complete resection rate was estimated to be 86.2% (95% confidence interval [CI], 78.9 to 91.3). If the analysis was limited to the lesions that originated from the submucosal layer, the pooled complete resection rate was 91.4% (95% CI, 77.9 to 97). If the analysis was limited to the lesions that originated from the muscularis propria, the pooled complete resection rate was 84.4% (95% CI, 78.7 to 88.8). The pooled procedure-related gastric perforation rate was 13% (95% CI, 9.4 to 17.6). Sensitivity analyses showed consistent results. Finally, publication bias was not detected. CONCLUSIONS: ESD, including endoscopic muscularis dissection, is a technically feasible procedure for the treatment of SETs. However, selection bias is suspected from the enrolled studies. For the development of a proper indication of ESD for SETs, further studies are needed.
Gastrointestinal Stromal Tumors ; Humans ; Publication Bias ; Selection Bias

A systematic review (SR) provides the best and most objective analysis of the existing evidence in a particular field. SRs and derived conclusions are essential for evidence-based strategies in medicine and evidence-based guidelines in clinical practice. The popularity of SRs has also increased markedly in the field of hepatology. However, although SRs are considered to provide a higher level of evidence with greater confidence than original articles, there have been no reports on the quality of SRs and meta-analyses (MAs) in the field of hepatology. Therefore, we performed a quality assessment of 225 SRs and MAs that were recently published in the field of hepatology (January 2011 to September 2014) using A MeaSurement Tool to Assess systematic Reviews (AMSTAR). Using AMSTAR, we revealed both a shortage of assessments of the scientific quality of individual studies and a publication bias in many SRs and MAs. This review addresses the concern that SRs and MAs need to be conducted in a stricter and more objective manner to minimize bias and random errors. Thus, SRs and MAs should be supported by a multi-disciplinary approach that includes clinical experts, methodologists, and statisticians.
*Gastroenterology ; Humans ; *Meta-Analysis as Topic ; *Publication Bias ; *Review Literature as Topic

The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were “gemtc” for the Bayesian approach and “netmeta” for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the “rjags” package is a common tool. “rjags” implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.
Bayes Theorem ; Hope ; Markov Chains ; Population Characteristics ; Publication Bias

The objective of this study was to describe general approaches for intervention meta-analysis available for quantitative data synthesis using the R software. We conducted an intervention meta-analysis using two types of data, continuous and binary, characterized by mean difference and odds ratio, respectively. The package commands for the R software were “metacont”, “metabin”, and “metagen” for the overall effect size, “forest” for forest plot, “metareg” for meta-regression analysis, and “funnel” and “metabias” for the publication bias. The estimated overall effect sizes, test for heterogeneity and moderator effect, and the publication bias were reported using the R software. In particular, the authors indicated methods for calculating the effect sizes of the target studies in intervention meta-analysis. This study focused on the practical methods of intervention meta-analysis, rather than the theoretical concepts, for researchers with no major in statistics. Through this study, the authors hope that many researchers will use the R software to more readily perform the intervention meta-analysis and that this will in turn generate further related research.
Forests ; Hope ; Odds Ratio ; Population Characteristics ; Publication Bias