Bootstrap generated confidence interval for time averaged measure

Author(s):  
Jinsoo Park ◽  
Haneul Lee ◽  
Yun Bae Kim

In the simulation output analysis, there are some measures that should be calculated by time average concept such as the mean queue length. Especially, the confidence interval of those measures might be required for statistical analysis. In this situation, the traditional method that utilizes the central limit theorem (CLT) is inapplicable if the output data set has autocorrelation structure. The bootstrap is one of the most suitable methods which can reflect the autocorrelated phenomena in statistical analysis. Therefore, the confidence interval for a time averaged measure having autocorrelation structure can also be calculated by the bootstrap methods. This study introduces the method that constructs these confidence intervals applying the bootstraps. The bootstraps proposed are the threshold bootstrap (TB), the moving block bootstrap (MBB) and stationary bootstrap (SB). Finally, some numerical examples will be provided for verification.

2021 ◽  
Vol 28 ◽  
pp. 146-150
Author(s):  
L. A. Atramentova

Using the data obtained in a cytogenetic study as an example, we consider the typical errors that are made when performing statistical analysis. Widespread but flawed statistical analysis inevitably produces biased results and increases the likelihood of incorrect scientific conclusions. Errors occur due to not taking into account the study design and the structure of the analyzed data. The article shows how the numerical imbalance of the data set leads to a bias in the result. Using a dataset as an example, it explains how to balance the complex. It shows the advantage of presenting sample indicators with confidence intervals instead of statistical errors. Attention is drawn to the need to take into account the size of the analyzed shares when choosing a statistical method. It shows how the same data set can be analyzed in different ways depending on the purpose of the study. The algorithm of correct statistical analysis and the form of the tabular presentation of the results are described. Keywords: data structure, numerically unbalanced complex, confidence interval.


1989 ◽  
Vol 72 (2) ◽  
pp. 237-241
Author(s):  
Gerald L Stahl ◽  
D Dal Kratzer ◽  
Charles W Kasson

Abstract A modification of the AOAC microbiological determination of neomycin in feeds was collaboratively studied by 12 laboratories. The official method was modified by substituting a constant salt concentration diluent for the feed extract diluent, preparing the agar medium in tris buffer, and performing the test with a monolayer plating system. Each laboratory performed single assays on 8 samples in a randomized sequence. The samples included duplicates of a cattle and swine feed at 2 different marketed concentrations. The mean recovery across all laboratories was 110.7% of theory with a range of means of 69.4-128.6 across the 12 laboratories. The results of one laboratory and 2 additional values from different laboratories were deemed outliers and excluded from statistical analysis. The statistical analysis gave a confidence interval of ± 26% for individual assays.


2019 ◽  
Vol 43 (3) ◽  
pp. 169-172
Author(s):  
Elisabetta Stenner ◽  
Giulia Barbati ◽  
Nicole West ◽  
Fabia Del Ben ◽  
Francesca Martin ◽  
...  

Abstract Background To evaluate if procalcitonin (PCT) measurements made using the new point-of-care testing (POCT) ichroma™ are interchangeable with those made using Kryptor. Methods Serum samples (n = 117) were processed sequentially on Kryptor and ichroma™. Statistical analysis was performed using Passing-Bablok (PB) regression and the Bland-Altman (BA) test. Cohen’s kappa statistic was used to calculate the concordance at the clinically relevant cutoffs. Results PB regression did not show a significant deviation from linearity; proportional and constant differences were observed between ichroma™ and Kryptor. The 95% confidence interval (CI) of the mean bias percentage was very large, exceeding the maximum allowable total error (TE) (approximately 20%) and the clinical reference change value (about 60%). However, the concordance between methods at the clinically relevant cutoffs was strong, with the exception of the 0.25 ng/mL cutoff, which was moderate. Conclusions Our data suggest that ichroma™ is not interchangeable with Kryptor, so cannot be mixed; one must choose one instrument only and be consistent. However, while the strong concordance at the clinically relevant cutoffs allows us to consider ichroma™ a suitable option to Kryptor to support clinicians’ decision-making, nevertheless the moderate agreement at the 0.25 ng/mL cutoff recommends caution in interpreting the data around this cutoff.


2003 ◽  
Vol 4 (2) ◽  
pp. 1-8
Author(s):  
Endang Wahyuningrum

Multilocationtrials play an important role in agronomic research. Theseare often used to analyse the adaptability of genotypes indifferent environments. Multilocation trials also are usedto find out which environment is the best location to adaptfor each genotype that is the highest yielding in the environmentand to determine the pattern of response of genotypes acrossenvironments. ANOVA is used to compute genotype and environmentadditive effects. However, it cannot be used to analyse agenotype-environmental interaction. Principle component analysis(PCA) is only used to analyse non additive interaction effects.The statistical analysis recommended here combines the Anovawith PCA that is Additive Main effects and MultiplicativeInteraction (AMMI) with PCA. It begins with the usual analysisof variance to compute genotype and environment additive effects,and then applies PCA to analyse non additive interaction effects.The results of AMMI analysis is presented graphically in theform of biplots. The use of these procedure is exemplifiedusing secondary data set of the mean yield of padi from TheCenter of Indonesian Padi Research in Sukamandi.


2020 ◽  
Author(s):  
Avtandil G. Amiranashvili ◽  
Ketevan R. Khazaradze ◽  
Nino D. Japaridze

Results of a comparative statistical analysis of the daily data associated with New coronavirus COVID-19 infection of confirmed cases (Č) of the population in Georgia (GEO), Armenia (ARM), Azerbaijan (AZE), Turkey (TUR) and Russia (RUS) amid a global pandemic (WLD) in the period from March 14 to July 31, 2020 are presented. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, a correlation and autocorrelation analysis of the observational data was carried out, the periodicity in the time- series of Č were revealed, the calculation of the interval prediction values of Č taking into account the periodicity in the time-series of observations from August 1 to 31, 2020 (ARM, AZE) and from August 1 to September 11, 2020 (WLD, GEO, TUR, RUS) were carried out. Comparison of real and calculated predictions data on Č in the study sites from August 1 to August 31, 2020 is carried out. It was found that daily, monthly and mean weekly real values of Č for all the studied locations practically fall into the 99% confidence interval of the predicted values of Č for the specified time period. A dangerous situation with the spread of coronavirus infection may arise when the mean weekly values of Č of the 99% upper level of the forecast confidence interval are exceeded within 1-2 weeks. Favorable - when the mean weekly values of Č decrease below 99% of the lower level of the forecast confidence interval.


1982 ◽  
Vol 61 (s109) ◽  
pp. 34-34
Author(s):  
Samuel J. Agronow ◽  
Federico C. Mariona ◽  
Frederick C. Koppitch ◽  
Kazutoshi Mayeda

2020 ◽  
Author(s):  
Hideya Kawasaki ◽  
Hiromi Suzuki ◽  
Masato Maekawa ◽  
Takahiko Hariyama

BACKGROUND As pathogens such as influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can easily cause pandemics, rapid diagnostic tests are crucial for implementing efficient quarantine measures, providing effective treatments to patients, and preventing or containing a pandemic infection. Here, we developed the immunochromatography-NanoSuit® method, an improved immunochromatography method combined with a conventional scanning electron microscope (SEM), which enables observation of immunocomplexes labeled with a colloidal metal. OBJECTIVE A total of 197 clinical samples from patients suspected to be suffering from influenza were provided by a general hospital at the Hamamatsu University School of Medicine for examination using the Flu kit. METHODS Immunochromatography kit The ImunoAce® Flu kit (NP antigen detection), a human influenza commercial diagnosis kit, was purchased from TAUNS Laboratories, Inc. (Shizuoka, Japan). Au/Pt nanoparticles were utilized to visualize the positive lines. A total of 197 clinical samples from patients suspected to be suffering from influenza were provided by a general hospital at the Hamamatsu University School of Medicine for examination using the Flu kit. After macroscopic diagnosis using the Flu kit, the samples were stored in a biosafety box at room temperature (20-25 °C / 68 - 77 °F). The IgM detection immunochromatography kit against SARS-CoV-2 was obtained from Kurabo Industries, Ltd. (Osaka, Japan). One step rRT-PCR for influenza A rRT-PCR for influenza A was performed as described previously using Flu A universal primers. A Ct within 38.0 was considered as positive according to the CDC protocol. The primer/probe set targeted the human RNase P gene and served as an internal control for human nucleic acid as described previously. SEM image acquisition The immunochromatography kit was covered with a modified NanoSuit® solution based on previously published components (Nisshin EM Co., Ltd., Tokyo, Japan), placed first onto the wide stage of the specimen holder, and then placed in an Lv-SEM (TM4000Plus, Hitachi High-Technologies, Tokyo, Japan). Images were acquired using backscattered electron detectors with 10 or 15 kV at 30 Pa. Particle counting In fields containing fewer than 50 particles/field, the particles were counted manually. Otherwise, ImageJ/Fiji software was used for counting. ImageJ/Fiji uses comprehensive particle analysis algorithms that effectively count various particles. Images were then processed and counting was performed according to the protocol. Diagnosis and statistics The EM diagnosis and criteria for a positive test were defined as follows: particle numbers from 6 fields from the background area and test-line were statistically analyzed using the t-test. If there were more than 5 particles in one visual field and a significant difference (P < 0.01) was indicated by the t-test, the result was considered positive. Statistical analysis using the t-test was performed in Excel software. Statistical analysis of the assay sensitivity and specificity with a 95% confidence interval (95% CI) was performed using the MedCalc statistical website. The approximate line, correlation coefficient, and null hypothesis were calculated with Excel software. RESULTS Our new immunochromatography-NanoSuit® method suppresses cellulose deformity and makes it possible to easily focus and acquire high-resolution images of gold/platinum labeled immunocomplexes of viruses such as influenza A, without the need for conductive treatment as with conventional SEM. Electron microscopy (EM)-based diagnosis of influenza A exhibited 94% clinical sensitivity (29/31) (95% confidence interval [95%CI]: 78.58–99.21%) and 100% clinical specificity (95%CI: 97.80–100%). EM-based diagnosis was significantly more sensitive (71.2%) than macroscopic diagnosis (14.3%), especially in the lower influenza A-RNA copy number group. The detection ability of our method is comparable to that of real-time reverse transcription-polymerase chain reaction. CONCLUSIONS This simple and highly sensitive quantitative analysis method involving immunochromatography can be utilized to diagnose various infections in humans and livestock, including highly infectious diseases such as COVID-19.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Nana-Kwadwo Biritwum ◽  
Dziedzom K. de Souza ◽  
Odame Asiedu ◽  
Benjamin Marfo ◽  
Uche Veronica Amazigo ◽  
...  

Abstract Background The control of onchocerciasis in Ghana started in 1974 under the auspices of the Onchocerciasis Control Programme (OCP). Between 1974 and 2002, a combination of approaches including vector control, mobile community ivermectin treatment, and community-directed treatment with ivermectin (CDTI) were employed. From 1997, CDTI became the main control strategy employed by the Ghana OCP (GOCP). This review was undertaken to assess the impact of the control interventions on onchocerciasis in Ghana between 1974 and 2016, since which time the focus has changed from control to elimination. Methods In this paper, we review programme data from 1974 to 2016 to assess the impact of control activities on prevalence indicators of onchocerciasis. This review includes an evaluation of CDTI implementation, microfilaria (Mf) prevalence assessments and rapid epidemiological mapping of onchocerciasis results. Results This review indicates that the control of onchocerciasis in Ghana has been very successful, with a significant decrease in the prevalence of infection from 69.13% [95% confidence interval) CI 60.24–78.01] in 1975 to 0.72% (95% CI 0.19–1.26) in 2015. Similarly, the mean community Mf load decreased from 14.48 MF/skin snip in 1975 to 0.07 MF/skin snip (95% CI 0.00–0.19) in 2015. Between 1997 and 2016, the therapeutic coverage increased from 58.50 to 83.80%, with nearly 100 million ivermectin tablets distributed. Conclusions Despite the significant reduction in the prevalence of onchocerciasis in Ghana, there are still communities with MF prevalence above 1%. As the focus of the GOCP has changed from the control of onchocerciasis to its elimination, both guidance and financial support are required to ensure that the latter goal is met.


2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Chao Xiong ◽  
Claudia Stolle ◽  
Patrick Alken ◽  
Jan Rauberg

Abstract In this study, we have derived field-aligned currents (FACs) from magnetometers onboard the Defense Meteorological Satellite Project (DMSP) satellites. The magnetic latitude versus local time distribution of FACs from DMSP shows comparable dependences with previous findings on the intensity and orientation of interplanetary magnetic field (IMF) By and Bz components, which confirms the reliability of DMSP FAC data set. With simultaneous measurements of precipitating particles from DMSP, we further investigate the relation between large-scale FACs and precipitating particles. Our result shows that precipitation electron and ion fluxes both increase in magnitude and extend to lower latitude for enhanced southward IMF Bz, which is similar to the behavior of FACs. Under weak northward and southward Bz conditions, the locations of the R2 current maxima, at both dusk and dawn sides and in both hemispheres, are found to be close to the maxima of the particle energy fluxes; while for the same IMF conditions, R1 currents are displaced further to the respective particle flux peaks. Largest displacement (about 3.5°) is found between the downward R1 current and ion flux peak at the dawn side. Our results suggest that there exists systematic differences in locations of electron/ion precipitation and large-scale upward/downward FACs. As outlined by the statistical mean of these two parameters, the FAC peaks enclose the particle energy flux peaks in an auroral band at both dusk and dawn sides. Our comparisons also found that particle precipitation at dawn and dusk and in both hemispheres maximizes near the mean R2 current peaks. The particle precipitation flux maxima closer to the R1 current peaks are lower in magnitude. This is opposite to the known feature that R1 currents are on average stronger than R2 currents.


Author(s):  
Hila Beck ◽  
Riki Tesler ◽  
Sharon Barak ◽  
Daniel Sender Moran ◽  
Adilson Marques ◽  
...  

Schools with health-promoting school (HPS) frameworks are actively committed to enhancing healthy lifestyles. This study explored the contribution of school participation in HPS on students’ health behaviors, namely, physical activity (PA), sedentary behavior, and dieting. Data from the 2018/2019 Health Behavior in School-aged Children study on Israeli adolescents aged 11–17 years were used. Schools were selected from a sample of HPSs and non-HPSs. Between-group differences and predictions of health behavior were analyzed. No between-group differences were observed in mean number of days/week with at least 60 min of PA (HPS: 3.84 ± 2.19 days/week, 95% confidence interval of the mean = 3.02–3.34; non-HPS: 3.93 ± 2.17 days/week, 95% confidence interval of the mean = 3.13–3.38). Most children engaged in screen time behavior for >2 h/day (HPS: 60.83%; non-HPS: 63.91%). The odds of being on a diet were higher among more active children (odds ratio [OR] = 1.20), higher socio-economic status (OR = 1.23), and female (OR = 2.29). HPS did not predict any health behavior. These findings suggest that HPSs did not contribute to health behaviors more than non-HPSs. Therefore, health-promoting activities in HPSs need to be improved in order to justify their recognition as members of the HPS network and to fulfill their mission.


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