PURPOSE: To do nursing research effectively requires an understanding of fundamental principles of statistical methods. In this article, some key statistical methods which are commonly used in nursing research are identified and summarized. METHODS: Ninety-two original articles from the Journal of Korean Academy of Nursing Administration were reviewed. Statistical methods were classified and summarized for usage in research and occurrence of common errors. RESULTS: Among the original articles reviewed, 58 statistical usages contained errors. Most errors were found in linear regression analysis, Pearson correlation analysis, and chi-square test. From the detection of statistical errors in usage, suggestions for appropriate statistical methods were made. CONCLUSION: In order to improve validity of original articles in the Journal of Korean Academy of Nursing Administration, clearly stated statistical usage and close editorial attention to statistical methods are needed. Understanding statistical methods is part of the process that researchers must use to determine both quality and usefulness of the research. Research findings will be used to guide nursing practice and reduce uncertainty in decision making. However, to understand how to interpret research results, it is important to be able to understand basic statistical concepts. Researchers should also choose statistical methods that match their purposes.
Decision Making ; Linear Models ; Nursing Research ; Uncertainty

PURPOSE: The aim of the present study was to investigate associations between the renin gene (REN) and the risk of essential hypertension and blood pressure (BP) levels in Koreans. MATERIALS AND METHODS: To outline the functional role of a single nucleotide polymorphism in the transcription of the REN gene, we conducted a case-control study of 1975 individuals: 646 hypertension (HT) patients and 1329 ethnically and age-matched normotensive subjects. RESULTS: Logistic regression analysis indicated that the genotypes AA/AG were strongly associated with risk of HT (odds ratio, 1.493; 95% confidence interval, 1.069-2.086, p=0.018) in female subjects. The genotypes AA/AG also showed significant association with higher blood pressure levels, both systolic and diastolic, in postmenopausal HT women (p=0.003 and p=0.017, respectively). Analysis of the promoter containing rs6682082 revealed a 2.4+/-0.01-fold higher activity in the A variant promoter than the G variant promoter, suggesting that rs6682082 is itself a functional variant. CONCLUSION: We suggest that the A allele of rs6682082 is a positive genetic marker for predisposition to essential hypertension and high BP in Korean women and may be mediated through the transcriptional activation of REN.
Alleles ; Asian Continental Ancestry Group/*genetics ; Blood Pressure/*genetics ; Case-Control Studies ; Diastole/genetics ; Female ; Gene Frequency ; *Genetic Association Studies ; *Genetic Predisposition to Disease ; Humans ; Hypertension/*genetics/*physiopathology ; Luciferases/metabolism ; Middle Aged ; Polymorphism, Single Nucleotide/*genetics ; Promoter Regions, Genetic/genetics ; Renin/*genetics ; Republic of Korea ; Risk Factors ; Systole/genetics ; Transfection

OBJECTIVE: We wanted to assess the role of the popliteal lymph nodes for differentiating rheumatoid arthritis (RA) from osteoarthritis (OA), and we also wanted to investigate the relationship between the popliteal lymph nodes and the inflamed synovial volume (ISV) by using contrast enhanced (CE), fat suppressed, three dimensional-fast spoiled gradient echo (3D-FSPGR) MR imaging. MATERIALS AND METHODS: Contrast enhanced 3D-FSGPR MR imaging of 94 knees (21 with RA and 73 with OA) was analyzed. A lymph node was defined as being 'observed' if it could be seen in at least two planes of the three orthogonal reformatted planes. The number of observed lymph nodes, the mean of the smallest dimension of each lymph node and the existence of central fatty change were recorded. The OA group was graded according to the ISV calculated by a segmentation method: grade I was < 20 cm3; grade II ranged from 20 cm3 to 40 cm3; and grade III was > 40 cm3. Statistical analysis of the number and the mean size of the popliteal lymph nodes among the four groups (the RA group and the grade I-III OA groups) was performed. RESULTS: The prevalence of the observed popliteal lymph nodes was significantly different between all the OA groups or between the grade III OA group and the RA group (p < 0.0001, 0.0001, respectively). The popliteal lymph node was observed in 32 out of 73 OA cases, whereas it was visible in all of the 21 RA cases. The number (mean+/-standard deviation) of lymph nodes in the grade I OA group, the grade II OA group, the grade III OA group and the RA group was 1.2+/-0.4, 1.2+/-0.4, 1.3+/-0.5, and 2.7+/-1.1, respectively. The mean size (mean+/-standard deviation) of the lymph nodes was 3.8+/-1.0 mm, 3.6+/-1.1 mm, 4.1+/-0.8 mm, and 5.4+/-1.3 mm, respectively. The incidence of central fatty changes was significantly lower in the RA group than in all the OA groups and the grade III OA group. When differentiating RA from OA, and when the differentiation was confined to the RA group and grade III OA group, respectively, the criteria of the number of lymph nodes, their size, their central fatty change and a combination of all these three criteria showed statistical significance (Az values for the former were 0.869, 0.847, 0.776, and 0.942; Az values for the latter were 0.855, 0.799, 0.712, and 0.916). The number and mean size of the lymph nodes correlated with the ISVs (r = 0.49, p < 0.001; 0.50, 0.001, respectively). CONCLUSION: The number, size and central fatty changes in the popliteal lymph nodes observed on the MR images might serve as simple and useful markers in differentiating RA disease from OA disease. These markers would be particular helpful in cases of severe synovial enhancement where the ISVs of both RA and OA overlap. The number and mean size of the lymph nodes also correlated well with the ISV.
Adult ; Aged ; Arthritis, Rheumatoid/*diagnosis ; Diagnosis, Differential ; Female ; Humans ; Inflammation ; Knee ; *Lymph Nodes ; Magnetic Resonance Imaging/*methods ; Male ; Middle Aged ; Osteoarthritis/*diagnosis ; Research Support, Non-U.S. Gov't ; Retrospective Studies ; Synovial Membrane/*pathology

BACKGROUND AND OBJECTIVES: Analyzing the association between multiple SNPs and the disease outcomes will provide new insight into the disease's etiology. However, this presents an analytic difficulty due to the large number of SNPs and the complex relationships among them. We proposed using the mixed model approach to identify the significant multi-locus genotypes and the high-order gene-to-gene interactions. SUBJECTS AND METHODS: We described the mixed effects model and applied this approach to real world data. For the purpose of these analyses, we examine the association of four types of SNPs (AGT5, APOB, CETP3 and ACE6) with the lipid profiles and the measures related with cardiovascular disease. We used data from 672 healthy individuals (283 males and 389 females) who were without cardiovascular diseases. RESULTS: The results of our analysis suggested that there were significant random genotype patterns and genotype groups according to the gender effect on the lipid profiles. In other words, there was significant variability across the genotype groups because of the effect of gender on the lipid profiles. CONCLUSION: The mixed model approach provided a flexible statistical framework for controlling potential confounding variables and for identifying a significant genetic contributions that may come about through the effects of multi-locus genotypes or through an interaction between the genotype and environmental variables (e.g. gender) with the variations in quantitative traits (e.g. lipid profiles). There were significant genetic contributions to the variability in the lipid profiles, and these were explained by the 4 SNPs described in our real data.
Apolipoproteins B ; Cardiovascular Diseases ; Confounding Factors (Epidemiology) ; Genotype ; Humans ; Male ; Polymorphism, Single Nucleotide

BACKGROUND AND OBJECTIVES : The common methods of genetic association analysis are sensitive to population stratification, which may easily lead to a spurious association result. We used a regression approach based for linkage disequilibrium to perform a high resolution genetic association analysis. SUBJECTS AND METHODS : We applied a regression approach that can increase the resolution of quantitative traits that are related with cardiovascular diseases. The population data was composed of 543 males and 876 females without cardiovascular diseases, and it was obtained from a cardiovascular genome center. We used information about linkage disequilibrium between the marker and trait locus, and we added the covariates to model their effects. RESULTS : We found that this regression approach has the merit of analyzing genetic association based on linkage disequilibrium. In the analysis of the male group, the total cholesterol was significantly in linkage disequilibrium with CETP3 (p=0.002), and triglyceride was significantly in linkage disequilibrium with ACE8 (p=0.037), APOA1-1 (p=0.031), APOA5-1 (p=0.001), APOA5-2 (p=0.001) and LIPC4 (p=0.022). HDL-cholesterol was significantly in linkage disequilibrium with ACE7 (p=0.002), ACE8 (p=0.008), ACE10 (p=0.003), APOA5-2 (p=0.022), and MTP1 (p=0.001). In the female group, total cholesterol was significantly associated with APOA5-1 (p=0.020), APOA5-2 (p=0.001), and LIPC1 (p=0.016), and triglyceride was significantly associated with APOA5-1 (p=0.009), APOA5-2 (p=0.001), and CETP5 (p=0.049). LDL-cholesterol was significantly associated with APOA5-2 (p=0.004), and HDL-cholesterol was significantly associated with LIPC1 (p=0.004). CONCLUSION : We used a regression-based method to perform high resolution linkage disequilibrium analysis of a quantitative trait locus that's associated with lipid profiles. This method of using a single marker, as applied in this paper, was well suited for analysis of genetic association. Because of the simplicity, the method can also be easily performed by routine statistical analysis software.
Cardiovascular Diseases ; Cholesterol ; Female ; Genome ; Humans ; Linkage Disequilibrium* ; Male ; Quantitative Trait Loci* ; Triglycerides

Purpose: To proceed effectively with clinical research requires an understanding of the fundamental principles of study design and biostatistical methods. In this article, we identified and summarized basic clinical research designs and some of the key biostatistical methods that have been commonly used in clinical research. Materials and Methods: In an observational study, cross-sectional, case- control and Cohort designs were illustrated and compared. In a clinical trial study, parallel group design and cross-over designs were described according to their characteristics. Also, the biostatistical methods for their usages classified and summarized. Results: Understanding and evaluating research design are part of the process researchers must use to determine both the quality and usefulness of their research. Adequate applications to biostatistical methods are need; i.e., descriptive statistics, Student's t-test, ANOVA, nonparametrics, categorical data analysis, correlation and regression, and survival analysis. Conclusions: Research findings are used by clinical researcher to guide their practice and reduce their uncertainty in clinical decision making. However, to understand how to interpret research results, it is important to be able to understand basic statistical concepts and types of study design. Clinicians should also appropriately choose the biostatistical methods to suit their purposes.
Biostatistics ; Cohort Studies ; Cross-Over Studies ; Decision Making ; Observational Study ; Research Design* ; Statistics as Topic ; Uncertainty

BACKGROUND AND OBJECTIVES: It is very important to distinguish between the primary and secondary genetic effects at different sites within a small genetic region. Therefore, we evaluated the relative effects of single nucleotide polymorphisms (SNPs) within a gene on the serum lipid profiles by using individual data. SUBJECTS AND METHODS: To evaluate the contributions of SNPs in a region to the serum lipid profiles (total cholesterol, triglyceride, low density lipoprotein, high density lipoprotein), we used data that consisted of 808 individuals (327 males and 481 females) who did not have cardiovascular disease. In this study, we used a stepwise regression procedure to analyze the relative effects of four single nucleotide polymorphisms (ACE6, ACE7, ACE8, ACE10) in a gene region on the development of the serum lipid profiles in each gender group. RESULTS: In the males, there were epistatic interaction effects between two loci (ACE6xACE7, ACE6xACE8, ACE6xACE10, ACE8xACE10 and ACE7xACE8) and among three loci (ACE6xACE7xACE8, ACE6xACE7xACE10 and ACE6xACE8xACE10). Also, there are interaction effects between two loci (ACE6xACE7, ACE6xACE8, ACE6xACE10, ACE7xACE10 and ACE8xACE10) and among three loci (ACE6xACE7xACE8, ACE6xACE7xACE10, ACE6xACE8xACE10 and ACE7xACE8xACE10) in the females. CONCLUSION: The results suggested that each of these loci is important in causing a relative change of the serum lipid profiles, even with simultaneously accounting for the effects at the other loci. In the results of the analysis, there existed the effects of individual loci and significant interaction between the loci on the serum lipid profiles in each gender group. It was confirmed that this stepwise regression method can be suitable for evaluating the relative effects of SNPs and it is easily performed.
Cardiovascular Diseases ; Cholesterol ; Female ; Genes, vif* ; Humans ; Linear Models* ; Lipoproteins ; Male ; Peptidyl-Dipeptidase A ; Polymorphism, Single Nucleotide* ; Triglycerides

OBJECTIVES: The mixture-of-experts (ME) network uses a modular type of neural network architecture optimized for supervised learning. This model has been applied to a variety of areas related to pattern classification and regression. In this research, we applied a ME model to classify hidden subgroups and test its significance by measuring the stiffness of the liver as associated with the development of liver cirrhosis. METHODS: The data used in this study was based on transient elastography (Fibroscan) by Kim et al. We enrolled 228 HBsAg-positive patients whose liver stiffness was measured by the Fibroscan system during six months. Statistical analysis was performed by R-2.13.0. RESULTS: A classical logistic regression model together with an expert model was used to describe and classify hidden subgroups. The performance of the proposed model was evaluated in terms of the classification accuracy, and the results confirmed that the proposed ME model has some potential in detecting liver cirrhosis. CONCLUSIONS: This method can be used as an important diagnostic decision support mechanism to assist physicians in the diagnosis of liver cirrhosis in patients.
Elasticity Imaging Techniques ; Humans ; Learning ; Liver ; Liver Cirrhosis ; Logistic Models

Clinical prediction models are developed to calculate estimates of the probability of the presence/occurrence or future course of a particular prognostic or diagnostic outcome from multiple clinical or non-clinical parameters. Radiologic imaging techniques are being developed for accurate detection and early diagnosis of disease, which will eventually affect patient outcomes. Hence, results obtained by radiological means, especially diagnostic imaging, are frequently incorporated into a clinical prediction model as important predictive parameters, and the performance of the prediction model may improve in both diagnostic and prognostic settings. This article explains in a conceptual manner the overall process of developing and validating a clinical prediction model involving radiological parameters in relation to the study design and statistical methods. Collection of a raw dataset; selection of an appropriate statistical model; predictor selection; evaluation of model performance using a calibration plot, Hosmer-Lemeshow test and c-index; internal and external validation; comparison of different models using c-index, net reclassification improvement, and integrated discrimination improvement; and a method to create an easy-to-use prediction score system will be addressed. This article may serve as a practical methodological reference for clinical researchers.
Calibration ; Dataset ; Diagnosis ; Diagnostic Imaging ; Discrimination (Psychology) ; Early Diagnosis ; Humans ; Methods* ; Models, Statistical ; Prognosis

BACKGROUND AND OBJECT: Phytosterols(Plant sterols) have been known to reduce serum cholesterol concentrations by inhibiting absorption of both dietary and biliary cholesterol from the small intestines. However, the hypocholesterolemic effect of plant sterols has not been evaluated in Korea. We investigated the effect of plant sterol containing beverage on blood lipid profiles in the hypercholesterolemic patients. MATERIALS AND METHODS: Forty-five hypercholesterolemic patients(fasting LDL-cholesterol>130 mg/dl) were fed either a placebo beverage for 4 weeks or a test beverage containing plant sterols or 8 weeks in a single-blind, randomized cross-over study. The subjects were instructed to maintain the same amount of dietary intake of fat and cholesterol during the study. After 4 week treatment of plant sterols, the dose of plant sterols was doubled (3.2 g/d) for subjects whose LDL-cholesterol reduction rate was not reached by 15%. RESULTS: 1. The total study population who completed the whole protocol was 45 patients(15 males, 30 females, mean age 56). 2. At baseline, the mean dietary intake of saturated fat of subjects was 11.12 g, and cholesterol was 135.2 mg. 3. After 8 week treatment with plant sterols, serum concentrations of total cholesterol and LDL-cholesterol were significantly reduced by 4.38%(p= 0.039), 8.28%(p=0.036) respectively. However, HDL-cholesterol and triglyceride did not change significantly. 4. Two-thirds of the subjects responded to treatment with plant sterols, and the mean reduction rates in LDL-cholesterol and total cholesterol of those subjects were 14.1% and 9.2% respectively. CONCLUSION: We conclude that plant sterols reduce serum total cholesterol and LDL-cholesterol concentrations significantly. These results suggest that plant sterols are also effective for those with low cholesterol intake.
Absorption ; Beverages ; Cholesterol* ; Cholesterol, LDL ; Cross-Over Studies ; Female ; Humans ; Hypercholesterolemia* ; Intestine, Small ; Korea ; Lipoproteins ; Male ; Phytosterols ; Plants* ; Triglycerides