An evaluation of diagnostic tests and their roles in validating forest biometric models

2004 ◽  
Vol 34 (3) ◽  
pp. 619-629 ◽  
Author(s):  
Yuqing Yang ◽  
Robert A Monserud ◽  
Shongming Huang
Keyword(s):  
Model Validation ◽  
Statistical Tests ◽  
Model Development ◽  
Nonparametric Tests ◽  
T Test ◽  
Sign Test ◽  
Rank Test ◽  
Wide Range ◽  
Kolmogorov Smirnov ◽  
Smirnov Test

Model validation is an important part of model development. It is performed to increase the credibility and gain sufficient confidence about a model. This paper evaluated the usefulness of 10 statistical tests, five parametric and five nonparametric, in validating forest biometric models. The five parametric tests are the paired t test, the Χ2 test, the separate t test, the simultaneous F test, and the novel test. The five nonparametric tests are the Brown-Mood test, the Kolmogorov–Smirnov test, the modified Kolmogorov–Smirnov test, the sign test, and the Wilcoxon signed-rank test. Nine benchmark data sets were selected to evaluate the behavior of these tests in model validation; three were collected from Alberta and six were published elsewhere. It was shown that the usefulness of statistical tests in model validation is very limited. None of the tests seems to be generic enough to work well across a wide range of models and data. Each model passed one or more tests, but not all of them. Because of this, caution should be exercised when choosing a statistical test or several tests together to try to validate a model. It is important to reduce and remove any potential personal bias in selecting a favorite test, which can influence the outcome of the results.

Investigation of The Nutritional Approaches of Student Athletes During The Covid-19 Epidemic

2021 ◽  
Vol 15 (7) ◽  
pp. 1940-1944
Author(s):  
Sevcan Altun ◽  
Aykut Aksu ◽  
Osman Imamoglu ◽  
Murat Erdogdu ◽  
Kursat Karacabey
Keyword(s):  
Student Athletes ◽  
Eating Habits ◽  
T Test ◽  
Outbreak Period ◽  
Significant Difference ◽  
Package Program ◽  
Kolmogorov Smirnov ◽  
The Subject ◽  
The University ◽  
Smirnov Test

The aim of this study is to investigate the nutritional approaches of student athletes studying at the university during the coronavirus outbreak period. Participants consisted of students studying and doing sports at the University. 446 students, 246 males and 200 females, participated in the study. Besides the personal form, students were filled the questionnaire testing questionnaire. Students voluntarily participated. The surveys were done on social media. Nutritional habits questionnaire consists of 12 questions. In the preparation of the survey questions, the questions proved validity of the researches which have been done on the subject before have been used. SPSS 23.00 package program was used in statistical analyses. Kolmogorov-Smirnov test was performed to test whether the data was normally distributed and it was determined that the data showed normal distribution. Independent t-test, paired t-test, unidirectional variance analysis and LSD tests were used in statistical operations. There was no significant difference in students' nutrition approaches by gender, both in the pre-outbreak period and in the outbreak period points (p> 0.05). Nutrition scores were significantly increased during the outbreak period (p <0.001). A significant difference was found between the students who felt bad before the epidemic and those who felt well before the epidemic and their nutritional scores according to the levels they felt (p <0.05). A significant difference was found between the pre-outbreak period and post-epidemic nutrition scores of the sports faculty students (p <0.05). During the coronavirus epidemic, university student athletes have either increased their nutritional opportunities or have changed their eating habits positively to keep their immune systems strong or both. The fact that sports faculty students have better nutrition compared to other faculty students can be attributed to their taking courses in nutrition, health and similar. It is recommended to give lectures or seminars on nutrition to athlete students. Keywords: Student, Nutrition, Sports Nutrition, Nutritional Approach, Covid-19

Abstract 2374: A New More Sensitive Method to Assess Balance Among Stroke Trial Populations

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Pitchaiah Mandava ◽  
Michael E Brooks ◽  
Chase S Krumpelman ◽  
Thoma A Kent
Keyword(s):  
Nearest Neighbor ◽  
Statistical Tests ◽  
T Test ◽  
P Value ◽  
Large Artery ◽  
Population Distributions ◽  
Multiple Dimensions ◽  
Kolmogorov Smirnov ◽  
Baseline Factors ◽  
Stroke Trial

Background: Stroke outcome is dependent on baseline factors such as NIHSS and age. Relationships between these variables and outcomes are often non-linear and imbalances can influence outcomes, particularly in subgroup analysis with smaller number of subjects. Balance in baseline variables factors are typically compared by Wilcoxon rank sum, t-test or ANOVA. Because of non-linearity, these tests may be insensitive to important differences in the distribution of these factors and if multiple factors are considered simultaneously. We adapted a multi-dimensional extension of Kolmogorov-Smirnov (KS) test proposed by Fasano and Franceschini (FF) to compare population distributions. The FF algorithm provides a method to calculate KS Distance (KSD) between two distributions in multiple dimensions and a probability value can be obtained. We hypothesized that the FF algorithm would be more sensitive than traditional statistical tests to determine whether baseline factors differed among two trial arms. We further show that matching for baseline variables (nearest neighbor Euclidean matching, pPAIRS©; Mandava Kent Stroke 2010) improves the KSD, indicating closer matched populations. Methods: The NINDS database was used for this study ( ntis.gov ). The subgroup of rt-PA and placebo treated normoglycemic subjects with large artery stroke was analyzed. Median and mean NIHSS and age were compared and KSD and a p value were calculated using a custom program, pPOPULATION© written in Matlab®. rt-PA and placebo subjects were then matched using pPAIRS© and outliers eliminated. KSD and p value for the post-matched groups were calculated. Results: The left half of the table shows the pre-match comparisons. Baseline variables were not different using usual tests. A KSD value of 0.283, however yielded p=0.008, suggesting that the population distributions are indeed different when two variables are considered simultaneously. Right half of the table shows the post-match comparisons of baseline variables. The KSD value, 0.217, is lower and is associated with a p value = 0.175, indicating that the post-matched distributions are similar. a Wilcoxon Rank-Sum; b Student t-test; Conclusion: We demonstrate here a new application of a 2d version of the KS distance to verify the similarity of stroke populations and show that it is more sensitive than traditional difference testing. This finding is important because baseline imbalances are critical for accurate assessment of outcome. This algorithm can be further extended to additional dimensions (e.g.: glucose). Its relative advantages over other methods will be discussed.

The relationship between age and athletes' view of the phenomenon of doping

2021 ◽  
Vol 3 (2) ◽  
pp. 45-48
Author(s):  
Mohammad Saeed Kiani ◽  
◽  
Keivan Shabani Moghaddam ◽  
Keyword(s):  
T Test ◽  
Statistical Population ◽  
The Face ◽  
Kolmogorov Smirnov ◽  
Spss Software ◽  
Science Classes ◽  
New Generation ◽  
The Relationship ◽  
Cluster Random Sampling ◽  
Smirnov Test

The purpose of this study was to investigate the relationship between age and athletes' attitude to doping. A 40- question researcher-made questionnaire was used to collect the data. The face and content validity of the questionnaire was confirmed by a survey of professors related to the research subject and its reliability was reported to be 0.79 using Cronbach's alpha. The statistical population of the study consisted of all athletes in Kermanshah province that to the large number of samples, cluster random sampling method was used. Finally, 700 questionnaires were returned, out of which 431 were used. Data were analyzed using SPSS software. Descriptive statistics (mean, standard deviation, percentage, tables, graphs, etc.) for analysis of data as well as inferential statistics (one-sample t-test, independent t-test and analysis of variance) and Kolmogorov-Smirnov test was used to determine the normality of the data distribution. The results showed that there is a difference between the new generation of athletes and the older generation in terms of doping. Therefore, the athlete should consult with experienced people (those who use these substances) and a physician, and be aware of the side effects of these supplements by attending training and science classes. Avoid using them whenever possible.

Parametric and non-parametric tests for the evaluation of interlaminar fracture toughness of polymer composites

2020 ◽  
pp. 073168442097307
Author(s):  
Hande Yavuz ◽  
Durdu Hakan Utku
Keyword(s):  
Fracture Toughness ◽  
Polymer Composites ◽  
Beam Theory ◽  
Calibration Method ◽  
T Test ◽  
Interlaminar Fracture Toughness ◽  
Interlaminar Fracture ◽  
Kolmogorov Smirnov ◽  
Composite Samples ◽  
Smirnov Test

This study is based on the statistical analysis of interlaminar fracture toughness of various laminated polymer composites used in aerospace applications through parametric and non-parametric tests. Tukey’s, Dunkan’s, two-sample t-test, and Kolmogorov–Smirnov tests are used to analyze tensile mode interlaminar fracture toughness of various fiber-reinforced polymer composites obtained by beam theory, modified beam theory, and modified compliance calibration method. Among the studied composite samples, modified compliance calibration method provided the highest average interlaminar fracture toughness, whereas the modified beam theory showed the lowest one. Room temperature cured carbon fiber-reinforced composite samples exhibited higher interlaminar fracture toughness than the autoclave cured samples. Two-sample t-test show that all methods are found coherent with each other in terms of being significantly different. On the contrary, Kolmogorov–Smirnov test revealed no significant difference. Besides, Tukey’s and Duncan’s tests exhibited almost the same results in regard to significant differences except those obtained by the modified compliance calibration method. Two-sample t-test method should have to be performed in order to observe significant relations rather than Kolmogorov–Smirnov test, since the results of Tukey’s and Duncan’s tests are only consistent with each other for the beam theory and modified beam theory method.

scholarly journals Statistical approach Based on Deep Neural Networks for Oscillometric Blood Pressure Estimation

2018 ◽  
Author(s):  
Soojeong Lee ◽  
Joon-Hyuk Chang
Keyword(s):  
Blood Pressure ◽  
Regression Model ◽  
Statistical Tests ◽  
Single Point ◽  
Absolute Error ◽  
Rank Test ◽  
Physiological Properties ◽  
Kolmogorov Smirnov ◽  
The Mean ◽  
Blood Pressure Estimation

Oscillometric blood pressure (BP) devices currently estimate a single point but do not identify fluctuations in BP or distinguish them from variations in response to physiological properties. In this paper, to analyze BP normality based on oscillometric measurements, we use statistical approaches including kurtosis, skewness, Kolmogorov-Smirnov, and correlation tests. Then, to mitigate uncertainties, we use a deep neural network (DNN) to determine the confidence limits (CLs) of BP measurements based on their normality. The proposed DNN regression model decreases the standard deviation of error (SDE) of the mean error (ME) and the mean absolute error (MAE) and reduces the uncertainty of the CLs and SDEs of the proposed technique. We validate the normality of the distribution of the BP estimation distribution which fits the Gaussian distribution very well. We use a rank test in the DNN regression model to demonstrate the independence of the artificial SBP and DBP estimations. First, we perform statistical tests to verify the normality of the BP measurements for individual subjects. The proposed methodology provides accurate BP estimations and reduces the uncertainties associated with the CLs and SDEs based on the DNN regression estimator.

Dynamic knee valgus alignment in healthy young adults and its association with single leg triple hop distance and athletic single leg stability

2021 ◽  
Vol 71 (11) ◽  
pp. 2687-2691
Author(s):  
Jassia Ramzan ◽  
Muhammad Osama ◽  
Ghania Riffat ◽  
Mirza Mohammed Waqar Baig ◽  
Fatima Aiman
Keyword(s):  
Young Adults ◽  
Cross Sectional Study ◽  
T Test ◽  
Rank Test ◽  
Knee Valgus ◽  
Cross Sectional ◽  
Signed Rank ◽  
Signed Rank Test ◽  
Kolmogorov Smirnov ◽  
Gender Based

Objective The purpose of the current study was to determine the dynamic knee valgus angulation (DKVA) among sedentary young adults and the relationship of DKVA with triple hop distance and athletic single leg stability. Methods A cross sectional study was conducted on a sample of 72 healthy sedentary young adults aged 18-26 years out of which 29 (38.33%) were males and 43 (61.76%) were females. DKVA, single leg triple hop distance and athletic single leg stability were the outcome measurements for the study. Shapiro-Wilk and Kolmogorov Smirnov tests were used to determine normality of data. Independent t-test and Mann Whitney-U test were used for gender based comparison, paired t-test and Wilcoxon signed-rank test for comparing values of right and left leg, Freidman test for comparing the values of DKVA in different tasks and Pearson and Spearman correlation was used to determine relationship between two variables. Confidence interval was kept at 95% and p<0.05 was considered significant. Results DKVA was found to be lower for dominant leg in all tasks, and higher for single leg tasks as compared to drop jump screening test for both legs. Greater values of DKVA were observed in females in all tasks. Single leg triple hop distance and athletic single leg stability scores were higher in males as compared to females. No significant correlation of DKVA was observed with single leg triple hop distance and athletic single leg stability. Continuous...

Is There Significance beyond the T-Test?

1988 ◽  
Vol 22 (4) ◽  
pp. 334-335 ◽  
Author(s):  
Eric G. Boyce ◽  
Jean M. Nappi
Keyword(s):  
Training Programs ◽  
Statistical Tests ◽  
Nonparametric Tests ◽  
Statistical Test ◽  
T Test ◽  
Wilcoxon Rank Sum Test ◽  
Continuous Scale ◽  
Parametric Statistical Test ◽  
And Training ◽  
Normally Distributed

Choosing the most appropriate statistical test may be routine for statisticians, but not for clinicians. The t-test, a parametric statistical test, may be used inappropriately. This commentary describes the assumptions of and alternatives to the t-test. T-tests are used to compare two groups of data that are from a continuous scale and normally distributed. Determining if data are normally distributed can be difficult but selected methods can be useful. Two nonparametric tests, the Mann-Whitney U test and the Wilcoxon rank sum test, may be more appropriate in analyzing data that are neither continuous nor normally distributed. Statistical results may vary with the test chosen. Investigators are responsible for using the appropriate statistical tests. Statisticians and texts can be consulted. Pharmacy educational and training programs may need further emphasis in the area of statistics.

scholarly journals Inferring exemplar discriminability in brain representations

2016 ◽  
Author(s):  
Hamed Nili ◽  
Alexander Walther ◽  
Arjen Alink ◽  
Nikolaus Kriegeskorte
Keyword(s):  
Fixed Effects ◽  
Statistical Tests ◽  
Random Effect ◽  
Nonparametric Tests ◽  
Test Statistics ◽  
Brain Response ◽  
Test Statistic ◽  
Mahalanobis Distances ◽  
Linear Discriminant ◽  
Wide Range

AbstractRepresentational distinctions within categories are important in all perceptual modalities and also in cognitive and motor representations. Recent pattern-information studies of brain activity have used condition-rich designs to sample the stimulus space more densely. To test whether brain response patterns discriminate among a set of stimuli (e.g. exemplars within a category) with good sensitivity, we can pool statistical evidence over all pairwise comparisons. A popular test statistic reflecting exemplar information is the exemplar discriminability index (EDI), which is defined as the average of the pattern dissimilarity estimates between different exemplars minus the average of the pattern dissimilarity estimates between repetitions of identical exemplars. The EDI is commonly tested with a t test (H0: population mean EDI = 0) across subjects (subject as random effect). However, it is unclear whether this approach is either valid or optimal. Here we describe a wide range of statistical tests of exemplar discriminability and assess the validity (specificity) and power (sensitivity) of each test. The tests include previously used and novel, parametric and nonparametric tests, which treat subject as a random or fixed effect, and are based on different dissimilarity measures, different test statistics, and different inference procedures. We use simulated and real data to determine which tests are valid and which are most sensitive. The popular across-subject t test of the EDI (typically using correlation distance as the pattern dissimilarity measure) requires the assumption that the EDI is 0-mean normal under H0, which is not strictly true. Reassuringly, our simulations suggest that the test controls the false-positives rate at the nominal level and is thus valid in practice. However, test statistics based on average Mahalanobis distances or average linear-discriminant t values (both accounting for the multivariate error covariance among responses) are substantially more powerful for both random- and fixed-effects inference. We suggest preferred procedures for safely and sensitively detecting subtle pattern differences between exemplars.

Investigation of The Nutritional Approaches of Student Athletes During The Covid-19 Epidemic

2021 ◽  
Vol 15 (6) ◽  
pp. 2031-2034
Author(s):  
Sevcan Altun ◽  
Aykut Aksu ◽  
Osman Imamoglu ◽  
Murat Erdogdu ◽  
Kursat Karacabey
Keyword(s):  
Student Athletes ◽  
Eating Habits ◽  
T Test ◽  
Outbreak Period ◽  
Significant Difference ◽  
Package Program ◽  
Kolmogorov Smirnov ◽  
The Subject ◽  
The University ◽  
Smirnov Test

The aim of this study is to investigate the nutritional approaches of student athletes studying at the university during the coronavirus outbreak period. Participants consisted of students studying and doing sports at the University. 446 students, 246 males and 200 females, participated in the study. Besides the personal form, students were filled the questionnaire testing questionnaire. Students voluntarily participated. The surveys were done on social media. Nutritional habits questionnaire consists of 12 questions. In the preparation of the survey questions, the questions proved validity of the researches which have been done on the subject before have been used. SPSS 23.00 package program was used in statistical analyses. Kolmogorov-Smirnov test was performed to test whether the data was normally distributed and it was determined that the data showed normal distribution. Independent t-test, paired t-test, unidirectional variance analysis and LSD tests were used in statistical operations. There was no significant difference in students' nutrition approaches by gender, both in the pre-outbreak period and in the outbreak period points (p> 0.05). Nutrition scores were significantly increased during the outbreak period (p <0.001). A significant difference was found between the students who felt bad before the epidemic and those who felt well before the epidemic and their nutritional scores according to the levels they felt (p <0.05). A significant difference was found between the pre-outbreak period and post-epidemic nutrition scores of the sports faculty students (p <0.05). During the coronavirus epidemic, university student athletes have either increased their nutritional opportunities or have changed their eating habits positively to keep their immune systems strong or both. The fact that sports faculty students have better nutrition compared to other faculty students can be attributed to their taking courses in nutrition, health and similar. It is recommended to give lectures or seminars on nutrition to athlete students. Keywords: Student, Nutrition, Sports Nutrition, Nutritional Approach, Covid-19

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