ABSTRACT
PURPOSE: This study aimed to identify the best way of developing equivalent item sets and to propose a stable and effective management plan for periodical licensing examinations. METHODS: Five pre-equated item sets were developed based on the predicted correct answer rate of each item using linear programming. These pre-equated item sets were compared to the ones that were developed with a random item selection method based on the actual correct answer rate (ACAR) and difficulty from item response theory (IRT). The results with and without common items were also compared in the same way. ACAR and the IRT difficulty were used to determine whether there was a significant difference between the pre-equating conditions. RESULTS: There was a statistically significant difference in IRT difficulty among the results from different pre-equated conditions. The predicted correct answer rate was divided using 2 or 3 difficulty categories, and the ACAR and IRT difficulty parameters of the 5 item sets were equally constructed. Comparing the item set conditions with and without common items, including common items did not make a significant contribution to the equating of the 5 item sets. CONCLUSION: This study suggested that the linear programming method is applicable to construct equated-item sets that reflect each content area. The suggested best method to construct equated item sets is to divide the predicted correct answer rate using 2 or 3 difficulty categories, regardless of common items. If pre-equated item sets are required to construct a test based on the actual data, several methods should be considered by simulation studies to determine which is optimal before administering a real test.
Subject(s)
Licensure , Methods , Programming, LinearABSTRACT
BACKGROUND/OBJECTIVES: Numerous researches have studied the association between sugar intake and obesity of children in many countries. This study was undertaken to investigate the association between beverage intake and obesity of children by reviewing a database for total sugar contents established in all foods and presented in a nutrition survey by the Korea National Health and Nutrition Examination Survey (KNHANES). SUBJECTS/METHODS: Data of 1,520 children aged 6–11 years in the 6th KNHANES (2013–2015) were analyzed for this study. A database for total sugar intake comprises the total sugar contents of all foods included in the results of a nutrition survey using the 24-hour recall method of 6th KNHANES. Beverages were categorized into carbonated beverages, fruit & vegetable drinks, other drinks, tea, and coffee. RESULTS: The average daily beverage intake of all children was 131.75 g/day, and the average daily total sugar intake in beverages was 13.76 g/day. Carbonated beverages had the highest intake rate (58.85 g/day) and also ranked highest for sugar intake (6.36 g/day). After adjusting for confounding variables, the odds ratio for obesity in children with beverage intake of ≥ 200 mL/day significantly increased by 1.83 times (95% CI, 1.11–3.00) as compared to children with beverage intake of < 200 mL/day. Also, a significant increase was observed in the odds ratio for obesity in total children (2.41 times; 95% CI, 1.35–4.33) and boys (3.15 times; 95% CI, 1.53–6.49) with carbonated beverage intake of ≥ 200 mL/day when compared with children who consumed < 200 mL/day. CONCLUSION: A positive association is observed between beverage intake and obesity in Korean children. In particular, an intake of carbonated beverages has a positive correlation with childhood obesity in boys. This study can therefore be used as scientific evidence for reducing sugar, and for the continuous management and research on beverages.
Subject(s)
Child , Humans , Beverages , Carbohydrates , Carbonated Beverages , Coffee , Fruit , Korea , Methods , Nutrition Surveys , Obesity , Odds Ratio , Pediatric Obesity , Tea , VegetablesABSTRACT
PURPOSE@#This study aimed to identify the best way of developing equivalent item sets and to propose a stable and effective managementplan for periodical licensing examinations.@*METHODS@#Five pre-equated item sets were developed based on the predicted correct answer rate of each item using linear programming. These pre-equated item sets were compared to the ones that were developed with a random item selection method based on the actual correct answer rate (ACAR) and difficulty from item response theory (IRT). The results with and without common items were also compared in the same way. ACAR and the IRT difficulty were used to determine whether there was a significant difference between the pre-equating conditions.@*RESULTS@#There was a statistically significant difference in IRT difficulty among the results from different pre-equated conditions. The predicted correct answer rate was divided using 2 or 3 difficulty categories, and the ACAR and IRT difficulty parameters of the 5 item sets were equally constructed. Comparing the item set conditions with and without common items, including common items did not make a significant contribution to the equating of the 5 item sets.@*CONCLUSION@#This study suggested that the linear programming method is applicable to construct equated-item sets that reflect each content area. The suggested best method to construct equated item sets is to divide the predicted correct answer rate using 2 or 3 difficulty categories, regardless of common items. If pre-equated item sets are required to construct a test based on the actual data, several methods should be considered by simulation studies to determine which is optimal before administering a real test.