Determination of Minimum Sample Size Requirement for Multiple Linear Regression and Analysis of Covariance Based on Experimental and Non-experimental Studies

  Background: MLR and ANCOVA are common statistical techniques and are used for both experimental and non-experimental studies. However, both types of study designs may require different basis of sample size requirement. Therefore, this study aims to proposed sample size guidelines for MLR and ANCOVA for both experimental and non-experimental studies. Methods: We estimated the minimum sample sizes required for MLR and ANCOVA by using Power and Sample Size software (PASS) based on the pre-specified values of alpha, power and effect size (R2). In addition, we also performed validation of the estimates using a real clinical data to evaluate how close the approximations of selected statistics which were derived from the samples were to the actual parameters in the targeted populations. All the coefficients, effect sizes and r-squared obtained from the sample were then compared with their respective parameters in the population. Results: Small minimum sample sizes required for performing both MLR and ANCOVA when r-squared is used as the effect size. However, the validation results based on an evaluation from a real-life dataset suggest that a minimum sample size of 300 or more is necessary to generate a close approximation of estimates with the parameters in the population. Conclusions: We proposed sample size calculation when r-squared is used as an effect size is more suitable for experimental studies. However, taking a larger sample size such as 300 or more is necessary for clinical survey that is conducted in a non-experimental manner

Factors Influencing Visual Improvement after Phacoemulsification Surgery among Malaysian Cataract Patients

Blindness and visual impairment are part of the global burden of eye disease, with cataract being one of the leading causes of blindness. This study aimed to determine the factors affecting visual acuity (VA) improvement among cataract patients after phacoemulsification surgery in Malaysia. Cataract patients aged over 18 who underwent phacoemulsification surgery between January 2014 and December 2018 were included in this retrospective cohort study. Patients’ sociodemographic, comorbidities, surgical, and related complication factors were extracted from the National Eye Database. The outcome was measured by the difference in visual acuity before and after the operation and was categorized as “improved”, “no change”, and “worse”. A total of 180,776 patients were included in the final analysis. Multinomial logistic regression analysis showed “no changes in VA” was significantly higher in patients aged less than 40 years old (OR: 1.66; 95% CI: 1.22, 2.26), patients with ocular comorbidities (OR: 1.65; 95% CI: 1.53, 1.77), patients who had undergone surgery lasting more than 60 min (OR: 1.39; 95% CI: 1.14, 1.69), patients who had surgery without an intraocular lens (IOL) (OR: 1.64; 95% CI: 1.20, 2.26), and patients with postoperative complications (OR: 8.76; 95% CI: 8.13, 9.45). Worsening VA was significantly higher among male patients (OR: 1.11; 95% CI: 1.01, 1.22), patients who had ocular comorbidities (OR: 1.76; 95% CI: 1.59, 1.96), patients who had undergone surgery lasting more than 60 min (OR: 1.94; 95% CI: 1.57, 2.41), patients who had surgery without an IOL (OR: 2.03; 95% CI: 1.48, 2.80), and patients with postoperative complications (OR: 21.46; 95% CI: 19.35, 23.80). The factors impacting “no changes” in and “worsening” of VA after cataract surgery were the following: older age, male gender, ethnicity, ocular comorbidities, surgeon grade, absence of IOL, intraoperative complication, and postoperative problems

Comparative Prediction of Red Alga Biosorbent Performance in Dye Removal using Multivariate Models of Response Surface Methodology (RSM) and Artificial Neural Network (ANN)

Red algae species, Euchema Spinosum (ES) in Malaysia possesses excellent biosorbent properties in removing dyes from aqueous solutions. In the present study, the experimental design for the biosorption process was carried out via response surface methodology (RSMCCD). A total of 20 runs were carried out to generate a quadratic model and further analysed for optimisation. Prior to the evaluation, the characterisation study of the ES was performed. It was observed that the maximum uptake capacity of 399 mg/g (>95%) is obtained at equilibrium time of 60 min, pH solution of 6.9-7.1, dosage of 0.72 g/L and initial dye concentration of 300 g/L through statistical optimisation (CCD-RSM) based on the desirability function. It is demonstrated in the present study that the ANN model (R2=0.9994, adjR2=0.9916, MSE=0.19, RMSE=0.4391, MAPE=0.087 and AARE=0.001) is able to provide a slightly better prediction in comparison to the RSM model (R2= 0.9992, adj-R2= 0.9841, MSE=1.95, RMSE=1.395, MAPE=0.08 and AARE=0.001). Moreover, the SEM-EDX analysis indicates the development of a considerable number of pore size ranging between 132 to 175 m. From the experimental observations, it is evident that the ES can achieve high removal rate (>95%), indeed become a promising eco-friendly biosorptive material for MB dye removal