Research Papers

Inference-Driven Logistic Regression Approach for Identifying Risk Factors of Myopia

2026-01-01T00:00:00Z

Inference-Driven Logistic Regression Approach for Identifying Risk Factors of Myopia Kayathiri, T.; Kayanan, M.; Wijekoon, P. Myopia is a prevalent refractive error among children and adolescents and represents an increasing global public health issue. The present study aims to identify key risk and protective factors associated with myopia onset through statistical inference. A real-world myopia dataset from the R statistical package, which has been referenced in prior research for theoretical validation and factor identification, was analyzed. This investigation extends previous work by utilizing statistical inference to distinguish between variables that elevate myopia risk and those that confer protection. The dataset comprises 618 individuals who were non-myopic at baseline and were observed over a period of at least five years. During this period, 17 clinical and behavioral variables were recorded. Predictor variables include age, spherical equivalent refraction (SPHEQ), axial length (AL), anterior chamber depth (ACD), lens thickness (LT), vitreous chamber depth (VCD), and time spent on activities such as sports (SPORTHR), reading (READHR), computer use (COMPHR), studying (STUDYHR), and watching television (TVHR). The binary response variable was coded as 1 for myopic and 0 otherwise. Logistic regression coefficients were estimated using maximum likelihood estimation (MLE). Findings indicated that age, SPHEQ, AL, SPORTHR, STUDYHR, and TVHR exhibited negative coefficients, suggesting that increases in these variables are associated with a reduced risk of developing myopia. Conversely, positive coefficients for ACD, LT, VCD, READHR, and COMPHR point to elevated myopia risk. At the 5% significance level, SPHEQ and SPORTHR emerged as statistically significant predictors, while READHR and STUDYHR achieved significance at the 10% level. At the 90% confidence interval for odds ratios, SPHEQ, SPORTHR, and STUDYHR show protective effects (odds ratios < 1), whereas READHR is linked to greater risk; these protective effects remain significant at the 95% level. In summary, reduced reading time, increased participation in sports and studying, along with specific ocular measurements, may mitigate the risk of myopia development.

On the development of the adjusted multinomial logistic Liu estimator

2026-01-01T00:00:00Z

On the development of the adjusted multinomial logistic Liu estimator Kayathiri, T.; Kayanan, M.; Wijekoon, P. The multinomial logistic regression (MNLR) model is a widely used statistical tool for predicting categorical response variables with more than two outcomes, based on multiple predictor variables. It finds applications across various fields, including healthcare, social sciences, and marketing. The maximum likelihood estimator (MLE) is the standard method for estimating parameters in MNLR models. However, when predictor variables exhibit multicollinearity, the MLE becomes inefficient, resulting in inflated variances and unstable coefficient estimates. To address this issue, a limited number of biased estimators have been proposed in the literature. This study aimed to develop an efficient estimator that reduces the impact of multicollinearity in MNLR models by introducing the adjusted multinomial logistic Liu estimator (AMLLE), which improves estimation accuracy and stability. A Monte Carlo simulation study was conducted to evaluate the performance of the MLE, multinomial logistic ridge estimator (MLRE), multinomial logistic Liu estimator (MLLE), almost unbiased multinomial logistic Liu estimator (AUMLLE), and AMLLE under moderate to high multicollinearity. The simulations considered a wide range of sample sizes and varying levels of the response variable. The findings indicated that the proposed estimator, AMLLE, outperformed the existing estimators in all scenarios considered. The relative efficiency of AMLLE compared to MLE, based on SMSE, showed substantial improvement across different correlation values. For correlations of 0.5, 0.7, 0.9, and 0.99, AMLLE achieves efficiencies of 38.25, 46.62, 68.73, and 96.79% for n=50; 21.56, 27.03, 46.25, and 90.80% for n=100; and 2.85, 3.80, 9.04, and 41.21% for n=1000, with three response levels. The corresponding efficiencies with five response levels are 43.47, 52.16, 61.86, and 97.95%; 27.66, 33.39, 52.84, and 93.95%; and 3.76, 5.23, 12.41, and 47.05%, respectively. Moreover, increasing the sample size further enhanced the performance of the proposed estimator, while higher correlation and additional response levels tend to reduce its effectiveness. In conclusion, the adjusted multinomial logistic Liu estimator provides a reliable and computationally efficient alternative for parameter estimation in multinomial logistic regression models affected by multicollinearity. It shows strong potential for practical applications, and future research could explore its extension to high-dimensional predictor settings.

IMPACTS OF BIOCHAR ON EROSION POTENTIAL OF SOIL IN SLOPE LAND

2019-01-01T00:00:00Z

IMPACTS OF BIOCHAR ON EROSION POTENTIAL OF SOIL IN SLOPE LAND Madhushani, K.G.S.; Nanthakumaran, A. The study was conducted to evaluate the soil erosion potential in the slope land incorporated with biochar produced by Pinus pinaster (Pinus), Eucalyptus tereticornis (Eucalyptus) and Camellia sinensis (Tea). This study was conducted in Kandy district between latitudes 7.2906 N, 80.6337 E during 27th of August to 20th of November, 2017. There were sixteen plots of land prepared with the plot size of 1.5 mx 2.0 mand each type of biochar made from pinus, eucalyptus and tea incorporated into the 5 cm top soilin each plotseparately. The Complete Randomized Design was used with four treatments such as soil with tea biochar, soil with eucalyptus biochar, soil with pinus biochar and the control with each of four replicates. At the bottom of these plots, a ditch was excavated and covered with polythene and collected the eroded soil once in two weeks after the incorporation of different biochar with soil. Duncan‟ s multiple range tests were carried out using SPSS 25.0. The estimated soil losses in the plots with tea biochar, pinus biochar, eucalyptus biochar and control were 98.81 g, 219.77 g, 218.96 g and 781.83 g respectively. There was a significant reduction in the rate of soil erosion in the plots with tea biochar as 2.74 gm-2week-1. Plots with pinus and with eucalyptus biochar had almost similar reduction in the soil erosion rate as 6.08 gm-2week-1 and 6.12 gm-2week-1 respectively while the erosion rate in the control plot recorded as 21.72 gm-2week-1. Hence, application of tea biochar as a soil amendment could be recommended to reduce the soil erosion significantly in slope land in the hilly area.

Economic status of rural households with rain water harvesting systems (A case study in Monaragala District)

2015-01-01T00:00:00Z

Economic status of rural households with rain water harvesting systems (A case study in Monaragala District) Sandamali, W.D.P.; Nanthakumaran, A. Water scarcity is one of the major problems particularly for the rural households in the dry zone of Sri Lanka. It is believed that Rain Water Harvesting (RWH) may be a solution for this problem. As a result the rural households were provided the RWH structures to collect and store the rain water. The objective of this study was to assess the economic benefit of rain water harvesting. Questionnaire survey was conducted among randomly selected forty five rural households at Siripuragama GN division in Monaragala district during September to December, 2014. The data of time taken for water collection during non-rainy season, usage of Rain water harvesting system (RWHS), quantity of harvested rain water and the income earned by cultivating crops using Rain water harvesting were collected from the respondents. The results revealed that the women saved 26 man days whereas the men 16 man days and the children saved 70 hours per annum by using RWHS. Further an income earned by cultivating crops using harvested rain water and the reduction in the charges for the electricity due to rain water harvesting were assessed and considered to be an additional income for the households due to RWH. Well water consumers who had RWHS saved SLRs. 30505 (US$ 227) while non ‘Samurdhi’ beneficiaries of pipe born water consumers saved the SLRs.13046 (US$ 97) and ‘Samurdhi’ beneficiaries of pipe born water consumers saved SLRs.12341 (US$ 92) per annum. Installation of RWHS not only improve the economic status of the rural households but also conserve the water resource, hence it could be a win solution to the society and the environment.