The Derivation and Choice of Appropriate Test Statistic (Z, t, F and Chi-Square Test) in Research Methodology

Abebe, Teshome Hailemeskel

doi:10.11648/j.ml.20190503.11

Cited by 23 publications

(9 citation statements)

References 5 publications

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“…The sample efficiency rate of robotic collection method is 96.9%, lower than that of all manual collection methods. The chi-square [25] test value of the sample efficiency of different sampling method groups was 3.751, p = 0.586, meaning that there was no statistically significant difference in the sample efficiency of the six sampling methods, and that the robot automatic nasopharyngeal swab collection showed reliable sample validity.…”

Section: Effectiveness and Safety Analysismentioning

confidence: 95%

A study on the performance and cost-effectiveness of robots in replacing manual nucleic acid collection method: Experience from the COVID-19 pandemic

Chi

Gong

et al. 2022

PLoS ONE

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Background The COVID-19 pandemic has led nucleic acid collection and detection became a measure to ensure normal life in China. Considering the huge detection demand, it has emerged that robots replace manual sample collection. However, the cost-effectiveness of nucleic acid collection by robots instead of humans remain unknown. Methods This study was approved by the Ethics Committee of the Shenzhen Luohu District People’s Hospital, number 2021-LHQRMYY-KYLL-031a. All participants signed the written informed consent of this study. 273 volunteers were recruited on December 1st 2021 from Shenzhen and divided into six groups: one group to be sampled by robots and the others to be sampled manually with varying specifications for swab rotation and insertion time. Questionnaires were distributed to the robot group to ask them sampling feeling. The effectiveness and safety of sampling were evaluated through the sampling efficiency, adverse events and sampling feeling of different groups. The economics of the different methods were judged by comparing the sampling cost for each. Results The sampling efficiency of the robot group was 96.9%, and there was no statistically significant difference between the other five manually sampled groups (p = 0.586). There were no serious adverse events in any of the six groups, but nasal soreness and tearing did occur in all group. Of the volunteers who underwent robotic sampling, 85.94% reported that the experience was either no different or more comfortable than the manual sampling. In economic terms, a single robot used to replace medical staff for sample collection becomes economically advantageous when the working time is ≥ 455 days. If multiple robots are used to replace twice the number of manual collections, it becomes more economical at 137 days and remains so as long as the robot is used. Conclusions It appears safe and effective for robots to replace manual sampling method. Implementation of robotic sampling is economical and feasible, and can significantly save costs when working over a long term.

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Section: Effectiveness and Safety Analysismentioning

confidence: 95%

A study on the performance and cost-effectiveness of robots in replacing manual nucleic acid collection method: Experience from the COVID-19 pandemic

Chi

Gong

et al. 2022

PLoS ONE

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“…Initially, researchers used mathematical models to fit data distributions, such as Gaussian models, chi-square distribution models, etc. [8,9]. These are statistical-based outlier detection methods [10].…”

Section: Related Workmentioning

confidence: 99%

Outlier Detection Based on Autoencoder Ensembles with Denoising layer and Attention Mechanism

Ma,

Yu,

2023

J. Phys.: Conf. Ser.

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In the field of outlier detection, two common challenges have persisted. Firstly, outlier detection datasets are often small in size, which can lead to overfitting issues when using deep learning models such as autoencoders. Secondly, as the dimensionality of datasets increases, many dimensions may be irrelevant or noisy, which can adversely affect the model’s ability to learn meaningful features. This phenomenon is known as “the curse of dimensionality.” To address these challenges, this study proposes a solution using an ensemble of autoencoders with denoising layers to mitigate overfitting. Additionally, a novel attention mechanism is introduced to predict the importance of each feature, thereby addressing the curse of the dimensionality problem. The proposed approach is evaluated on five datasets, including BreastW and Vowels, and compared with existing methods. Experimental results demonstrate that the proposed method outperforms existing methods on four out of the five datasets, showcasing its effectiveness.

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“…Therefore, the second step assigns a statistical test from the list of available statistical tests based on the different experimental settings (scenarios) and the type of the dependent and independent variables. The statistical tests available for this step include ANOVA, the Kruskal-Wallis, and Chi-squared [37][38][39]. As an example, in order to investigate whether the office orientation impacts the values of the maximum visual comfort, the office orientation and the maximum hourly visual comfort are considered as the independent variable and dependent variables, respectively.…”

Section: The Proposed Framework-stagementioning

confidence: 99%

Section: The Proposed Framework-stagementioning

confidence: 99%

A Novel Framework for Optimizing Indoor Illuminance and Discovering Association of Involved Variables

et al. 2022

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The associations between various design variables affecting the visual performance of responsive facade systems are investigated in this study. First, we propose a data-driven approach to study practical aspects of illuminance optimization for responsive facades. In this approach, the hourly indoor illuminance data are combined with the location information to generate an objective function. This function is then utilized to evaluate the visual performance of responsive facade systems by matching a variety of facade angle movements to hourly sunshine patterns. Next, statistical tests were deployed to evaluate the role of design variables in different scenarios. The results provide detailed information about the design variables and their effects on visual comfort at 0.05 significant levels. On average, facade angles, facade configurations, facade orientations, and facade locations were significant in 100%, 41%, 87%, and 45% of different possible combinations of scenarios/variables, respectively.

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The Derivation and Choice of Appropriate Test Statistic (Z, t, F and Chi-Square Test) in Research Methodology

Cited by 23 publications

References 5 publications

A study on the performance and cost-effectiveness of robots in replacing manual nucleic acid collection method: Experience from the COVID-19 pandemic

A study on the performance and cost-effectiveness of robots in replacing manual nucleic acid collection method: Experience from the COVID-19 pandemic

Outlier Detection Based on Autoencoder Ensembles with Denoising layer and Attention Mechanism

A Novel Framework for Optimizing Indoor Illuminance and Discovering Association of Involved Variables

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