Wanitjirattikal, Puntipa
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Item type:Publication, Comparing the equivalence testing with using two one-sided test, square root of f distribution and 2-DF for shift-scale-equivalence test(2019-06-01)In pharmaceutical and medical studies, we would like to show any formulations or two treatments are equivalent. For example, Westergren ESR and STATplus ESR are two popular measurements of sedimentation rate, which are used to monitor disease severity in patients with rheumatoid arthritis and other inflammatory rheumatologic conditions. Westergren ESR is a well-known measurement that was developed by R. S.Fahraeus and A.V.A. Westergren in 1921, while STATplus ESR is an innovative measurement to accelerate turnaround time. Compared with Westergren ESR, the result from STATplus ESR is easier to understand. Since these two measurements can be used to test the same study, it is necessary to know if they can be switched. Typically, a new measurement process is compared with an existing measurement process. Paired data of these two measurements occur because they are used on the same subject. Usually, paired t- test is appropriate for paired data, but it does not fit well for some situations because paired t-test can only be used to check significant differences from paired data. If the paired data have positive or negative association, the result from the paired t-test might be the same. For example, one paired dataset has positive correlation, and the other one paired dataset has negative correlation. But paired t-tests give the same conclusion because they have the same differences .Moreover, the paired t-test might have low power for scale-type relationships. In this paper, we propose a test that has reasonable power for both shift and scale-type relationships, which is based on shift- scale type relationships. We consider an equivalence testing for hypothesis. It is an approach to swap the hypotheses so that statistical equivalence of the two measurements is the alternative hypothesis and bears the burden of proof. We conclude “equivalence” only if there is evidence to support the claim that the magnitude of disagreement between the two measurements lie within specified limits. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Simplified Approach to Constructing Coherent Topics and Subtopics from Text Data: A Case Study Using University Reviews(2024-01-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Comparison of Machine Learning Methods for Binary Classification of Multicollinearity Data(2024-12-02); This study examines the effectiveness of binary classification performance in multicollinearity. Four machine learning methods, namely backpropagation neural network, Naïve Bayes, support vector machine, and random forest, are compared in terms of their efficiency in handling multicollinear data. The evaluation of binary classification performance efficiency considers multicollinearity in independent variables, considering both a constant correlation model and the Toeplitz correlation. Correlation coefficients of 0.1 and 0.9 are explored in the analysis. The independent variables in this study are simulated from a multivariate normal distribution with 10, 20, 30, and 40 variables, respectively. The dependent variable is constructed using the logit function with sample sizes of 100 and 200. The simulation and data analysis are performed using the R Studio program and repeated 1,000 times for each scenario. The findings of this research reveal that the backpropagation neural network and Naïve Bayes methods exhibit superior performance in determining the mean accuracy percentage under constant correlation. On the other hand, the backpropagation neural network and support vector machine are the most effective methods in determining the mean accuracy percentage when dealing with multicollinearity in the form of Toeplitz correlation. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Superiority, Non-inferiority, Equivalence Test, and Innovative Equivalence Test(2021-06-24)In pharmaceutical and medical studies, randomized controlled trials (RCTs) aim to prove that a new treatment has better or superior efficacy than standard treatment or placebo. In fact, RCTs can also be used to evaluate the efficacy of a new treatment having similar or equivalence efficacy, or not worse or non-inferior efficacy depending on the objectives of the research. Meanwhile, the non-inferiority trials are more frequently found in research. However, the equivalence trials are another efficacy that RCTs would like to know sometimes. The purposes of this article are to provide a basic understanding for readers about the distinctions among the types of research, statistical hypothesis testing, the interpretation of hypothesis testing as well as the differences between statistical significance and clinical significance and also introduce an innovative equivalence test calls 2-df for shift-scale equivalence test.