One-sample Sign Test Research Articles

Clinical Trial Data on the Mechanical Removal of 14-Day-Old Dental Plaque Using Accelerated Micro-Droplets of Air and Water (Airfloss)

Novel strategies to combat dental biofilms aim at reducing biofilm stability with the ultimate goal of facilitating mechanical cleaning. To test the stability of dental biofilms, they need to be subjected to a defined mechanical stress. Here, we employed an oral care device (Airfloss) that emits microbursts of compressed air and water to apply a defined mechanical shear to 14-day-old dental plaque in 20 healthy participants with no signs of oral diseases (clinical trial no. NCT05082103). Exclusion criteria included pregnant or nursing women, users of oral prostheses, retainers or orthodontic appliances, and recent antimicrobial or anti-inflammatory therapy. Plaque accumulation, before and after treatment, was assessed using fluorescence images of disclosed dental plaque on the central incisor, first premolar, and first molar in the third quadrant (120 images). For each tooth, the pre- and post-treatment plaque percentage index (PPI) and Turesky modification of the Quigley-Hein plaque index (TM-QHPI) were recorded. The mean TM-QHPI significantly decreased after treatment (p = 0.03; one-sample sign test), but no significant difference between the mean pre- and post-treatment PPI was observed (p = 0.09; one-sample t-test). These data are of value for researchers that seek to apply a defined mechanical shear to remove and/or disrupt dental biofilms.

Quantifying pulmonary perfusion from noncontrast computed tomography.

PurposeComputed tomography (CT)‐derived ventilation methods compute respiratory induced volume changes as a surrogate for pulmonary ventilation. Currently, there are no known methods to derive perfusion information from noncontrast CT. We introduce a novel CT‐Perfusion (CT‐P) method for computing the magnitude mass changes apparent on dynamic noncontrast CT as a surrogate for pulmonary perfusion.Methods CT‐Perfusion is based on a mass conservation model which describes the unknown mass change as a linear combination of spatially corresponding inhale and exhale HU estimated voxel densities. CT‐P requires a deformable image registration (DIR) between the inhale/exhale lung CT pair, a preprocessing lung volume segmentation, and an estimate for the Jacobian of the DIR transformation. Given this information, the CT‐P image, which provides the magnitude mass change for each voxel within the lung volume, is formulated as the solution to a constrained linear least squares problem defined by a series of subregional mean magnitude mass change measurements. Similar to previous robust CT‐ventilation methods, the amount of uncertainty in a subregional sample mean measurement is related to measurement resolution and can be characterized with respect to a tolerance parameter τ. Spatial Spearman correlation between single photon emission CT perfusion (SPECT‐P) and the proposed CT‐P method was assessed in two patient cohorts via a parameter sweep of τ. The first cohort was comprised of 15 patients diagnosed with pulmonary embolism (PE) who had SPECT‐P and 4DCT imaging acquired within 24 h of PE diagnosis. The second cohort was comprised of 15 nonsmall cell lung cancer patients who had SPECT‐P and 4DCT images acquired prior to radiotherapy. For each test case, CT‐P images were computed for 30 different uncertainty parameter values, uniformly sampled from the range [0.01, 0.125], and the Spearman correlation between the SPECT‐P and the resulting CT‐P images were computed.ResultsThe median correlations between CT‐P and SPECT‐P taken over all 30 test cases ranged between 0.49 and 0.57 across the parameter sweep. For the optimal tolerance τ = 0.0385, the CT‐P and SPECT‐P correlations across all 30 test cases ranged between 0.02 and 0.82. A one‐sample sign test was applied separately to the PE and lung cancer cohorts. A low Spearmen correlation of 15% was set as the null median value and two‐sided alternative was tested. The PE patients showed a median correlation of 0.57 (IQR = 0.305). One‐sample sign test was statistically significant with 96.5 % confidence interval: 0.20–0.63, P < 0.00001. Lung cancer patients had a median correlation of 0.57(IQR = 0.230). Again, a one‐sample sign test for median was statistically significant with 96.5 percent confidence interval: 0.45–0.71, P < 0.00001.Conclusion CT‐Perfusion is the first mechanistic model designed to quantify magnitude blood mass changes on noncontrast dynamic CT as a surrogate for pulmonary perfusion. While the reported correlations with SPECT‐P are promising, further investigation is required to determine the optimal CT acquisition protocol and numerical method implementation for CT‐P imaging.

Effective factors in rural entrepreneurship development: A case study of villages in the central district of Bardaskan city

&lt;p&gt;In the last few decades, entrepreneurship as a strategy in the development and prosperity of human societies has turned into an unmatched alternative through which all factors, resources and facilities of a society are spontaneously mobilized through being placed in an evolutionary process in order to achieve high social ideals so that they become the source of many positive socio-economic consequences. Considering the importance of rural settlements in the national and regional space, the main purpose of the present study is to investigate the factors influencing rural entrepreneurship development at the villages in the central district of Bardaskan city. This research is an applied study in terms of purpose and a descriptive-analytical study in terms of methodology. Data has been collected through questionnaire and field survey. The research statistical population comprised 22 villages with over 100 inhabitants in the central district of Bardaskan, In the present study, which with regard to the limited statistical population (number of villages including above 100 people), sampling was not performed and all the villages of this district were considered as the sample population. The population of these 22 villages in 2016 amounted to 10,331 people in the form of 3,636 households, which by calculating through the modified Cochran formula, 374 households were obtained. The number of questionnaires for each village was determined in proportion to the population of each village. Then, selection of households at the village level was done through simple random sampling method so that the principle of equal opportunity to choose households was observed. Its validity was approved based on the expert opinion through content and Delphi methods and its reliability was calculated and confirmed through study of the guidebook and using Cronbach's alpha coefficient (70%-85%). Finally, the collected data was analyzed in the SPSS software environment using one-sample sign test ‎‏and Friedman test. According to the results obtained from the one-sample sign test, it was found that factors of the existence of infrastructure facilities and services, government measures and support and the required capital supply with first to second priorities and an average of 4.65, standard deviation of 0.49 and significance level of 0.0001 are effective in entrepreneurship development in rural areas.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

Quantile inference based on clustered data

One-sample sign test is one of the common procedures to develop distribution-free inference for a quantile of a population. A basic requirement of this test is that the observations in a sample must be independent. This assumption is violated in certain settings, such as clustered data, grouped data and longitudinal studies. Failure to account for dependence structure leads to erroneous statistical inferences. In this study, we have developed statistical inference for a population quantile of order p in either balanced or unbalanced designs by incorporating dependence structure when the distribution of within-cluster observations is exchangeable. We provide a point estimate, develop a testing procedure and construct confidence intervals for a population quantile of order p. Simulation studies are performed to demonstrate that the confidence intervals achieve their nominal coverage probabilities. We finally apply the proposed procedure to Academic Performance Index data.

Students' Conception about the Relation of Mathematics to Real-Life

Present paper has studied the conceptions of high school students about mathematical relations to the real life in the three strands; mathematics, experimental science and humanities. Regard to this research, research methodology was survey. Consequently 780 girl high school students are chosen via multi-steps cluster sampling method randomly. Questionnaire forms are applied in four parts as research instrumentation. Data are analyzed thereby descriptive and inferential statistics for further analysis as a result of the process that is demonstrated via one-sample sign test in order to collect and analyze of students' responses regard to self-conception about mathematics in real-life. Accord to the findings and results, it seems that students believed that the generalization of mathematics to the real life is surprisingly insufficiency. These views and responses are indicated that it necessaries to modify the textbooks and curriculums in terms of mathematics development and students' needs in real-life. Also teachers have to spend the special courses for this important.

Optimal sign tests for data from ranked set samples

This paper considers the one-sample sign test for data obtained from general ranked set sampling when the number of observations for each rank are not necessarily the same, and proposes a weighted sign test because observations with different ranks are not identically distributed. The optimal weight for each observation is distribution free and only depends on its associated rank. It is shown analytically that (1) the weighted version always improves the Pitman efficiency for all distributions; and (2) the optimal design is to select the median from each ranked set.

Procedure-Related Miscarriages and Down Syndrome–Affected Births

In Brief Objective To determine how pregnant women of varying ages, races, ethnicities, and socioeconomic backgrounds value procedure-related miscarriage and Down–syndrome-affected birth. Methods We studied cross-sectionally 534 sociodemographically diverse pregnant women who sought care at obstetric clinics and practices throughout the San Francisco Bay area. Preferences for procedure-related miscarriage and the birth of an infant affected by Down syndrome were assessed using the time trade-off and standard gamble metrics. Because current guidelines assume that procedure-related miscarriage and Down syndrome–affected birth are valued equally, we calculated the difference in preference scores for those two outcomes. We also collected detailed information on demographics, attitudes, and beliefs. Results On average, procedure-related miscarriage was preferable to Down syndrome–affected birth, as evidenced by positive differences in preference scores for them (time trade-off difference: mean = 0.09, median = 0.06; standard gamble difference: mean = 0.11, median = 0.02; P < .001 for both, one-sample sign test). There was substantial subject-to-subject variation in preferences that correlated strongly with attitudes about miscarriage, Down syndrome, and diagnostic testing. Conclusion Pregnant women tend to find the prospect of a Down syndrome–affected birth more burdensome than a procedure-related miscarriage, calling into question the equal risk threshold for prenatal diagnosis. Individual preferences for those outcomes varied profoundly. Current guidelines do not appropriately consider individual preferences in lower-risk women, and the process for developing prenatal testing guidelines should be reconsidered to better reflect individual values. Pregnant women perceive that a Down syndrome–affected birth is worse than a procedure-related miscarriage, calling into question the equal risk threshold for prenatal diagnosis.

Procedure-related miscarriages and down syndrome–affected births: implications for prenatal testing based on women’s preferences

Objective: To determine how pregnant women of varying ages, races, ethnicities, and socioeconomic backgrounds value procedure-related miscarriage and Down–syndrome-affected birth. Methods: We studied cross-sectionally 534 sociodemographically diverse pregnant women who sought care at obstetric clinics and practices throughout the San Francisco Bay area. Preferences for procedure-related miscarriage and the birth of an infant affected by Down syndrome were assessed using the time trade-off and standard gamble metrics. Because current guidelines assume that procedure-related miscarriage and Down syndrome–affected birth are valued equally, we calculated the difference in preference scores for those two outcomes. We also collected detailed information on demographics, attitudes, and beliefs. Results: On average, procedure-related miscarriage was preferable to Down syndrome–affected birth, as evidenced by positive differences in preference scores for them (time trade-off difference: mean = 0.09, median = 0.06; standard gamble difference: mean = 0.11, median = 0.02; P < .001 for both, one-sample sign test). There was substantial subject-to-subject variation in preferences that correlated strongly with attitudes about miscarriage, Down syndrome, and diagnostic testing. Conclusion: Pregnant women tend to find the prospect of a Down syndrome–affected birth more burdensome than a procedure-related miscarriage, calling into question the equal risk threshold for prenatal diagnosis. Individual preferences for those outcomes varied profoundly. Current guidelines do not appropriately consider individual preferences in lower-risk women, and the process for developing prenatal testing guidelines should be reconsidered to better reflect individual values.

Statistics: A First Course

(NOTE: Each chapter ends with Solutions to the Practice Exercises.) 1. Introduction. Numerical Data and Categorical Data. Nominal, Ordinal, Interval, and Ratio Data. Sample Data and Populations. Biased Data. Statistics, Past and Present. The Study of Statistics. Statistics, What Lies Ahead. 2. Summarizing Data: Listing and Grouping. Dot Diagrams. Stem-and-Leaf Displays. Frequency Distributions. Graphical Presentations. 3 Summarizing Data: Statistical Descriptions. Measures of Location: The Mean. Measures of Location: The Weighted Mean. Measures of Location: The Median and Other Fractiles. Measures of Location: The Mode. Measures of Variation: The Range. Measures of Variation: The Standard Deviation. Some Applications of the Standard Deviation. The Description of Grouped Data. Some Further Descriptions. Technical Note Summations. Review: Chapters 1,2, & 3. 4. Possibilities and Probabilities. Counting. Permutations. Combinations. Probability. Mathematical Expectation. A Decision Problem. 5. Some Rules of Probability. 5.1 The Sample Space. Events. Some Basic Rules of Probability. Probabilities and Odds. Addition Rules. Conditional Probability. Independent Events. Multiplication Rules. Bayes' Theorem. Review: Chapters 4 & 5. 6. Probability Distributions. Probability Distributions. The Binomial Distribution. The Hypergeometric Distribution. The Poisson Distribution. The Multinomial Distribution. The Mean of a Probability Distribution. The Standard Deviation of a Probability Distribution. Chebyshev's Theorem. 7. The Normal Distribution. Continuous Distributions. The Normal Distribution. Some Applications. The Normal Approximation to the Binomial Distribution. 8. Sampling and Sampling Distributions. Random Sampling. Sampling Distributions. The Standard Error of the Mean. The Central Limit Theorem. Review: Chapters 6, 7, & 8. 9. Problems of Estimation. The Estimation of Means. Confidence Intervals for Means. Confidence Intervals for Means (Small Samples). Confidence Intervals for Standard Deviations. The Estimation of Proportions. 10. Tests Concerning Means. 10.1 Test of Hypotheses. Significance Tests. Tests Concerning Means. Tests Concerning Means (Small Samples). Differences Between Means. Differences Between Means (Small Samples). Differences Between Means (Paired Data). Differences Among k Means. Analysis of Variance. 11. Tests Based on Count Data. Tests Concerning Proportions. Tests Concerning Proportions (Large Samples). Differences Between Proportions. Differences Among Proportions. Contingency Tables. Goodness of Fit. Review: Chapters 9, 10, & 11. 12. Regression and Correlation. Curve Fitting. The Method of Least Squares. Regression Analysis. The Coefficient of Correlation. The Interpretation of r. A Significance Test for r. 13. Nonparametric Tests. The One-Sample Sign Test. The Paired-Sample Sign Test. The Sign Test (Large Samples). Rank Sums: The U Test. Rank Sums: The U Test (Large Samples). Rank Sums: The H Test. Tests of Randomness: Runs. Tests of Randomness: Runs (Large Samples). Tests of Randomness: Runs Above and Below the Median. Rank Correlation. Review: Chapters 12 & 13. Appendix A: TI-83 Tips. Statistical Tables. Answers to Odd-Numbered Exercises. Index.

Short-Term Dynamics of Cavity-Nesting Bird Communities in Disjunct Floodplain Habitats

We studied turnover rates in cavity-nesting bird communities during 1983 and 1984 in 34 cottonwood-willow (Populus-Salix) habitat fragments along the North Platte River in southeastern Wyoming. Our principal goal was to determine whether the equilibrium theory of island biogeography was applicable to this system. We tested two hypotheses: (1) equilibrial turnover of cavity-nesting bird species does not occur in disjunct floodplain habitats, and (2) no significant relations exist between absolute turnover rate (ATR) and habitat-fragment features. Paired-t tests and a one-sample sign test corroborated equilibrial turnover for the group of fragments collectively, but examination of the hypothesis at the level of individual fragments did not support the equilibrium model. Simpleand partialregression coefficients indicated ATR was positively associated with fragment size, the reverse of what equilibrium theory predicts; ATR, however, was negatively related to distance to nearest streamside habitat fragment (analogous to degree of isolation), which is consistent with the theory. ATR was significantly related to five fragment features in a validated multiple regression model: amount of edge/hectare, size of fragment, frequencies of snag classes 4 (56 to 70 cm dbh) and 6 (>85 cm dbh), and the presence of palustrine wetland bordering each fragment. Short-term dynamics of cavity-nesting bird communities in the system we studied are not completely predictable from the equilibrium theory. Fragment features appear to be the important deterministic forces affecting species richness and dynamics, but stochastic immigration and extinction may also be operative. Application of equilibrium island-biogeographic theory to conserve the system we analyzed is inappropriate. Instead, recommendations that recognize the deterministic influences we have identified should be used.

Effect of Non-Normality on the Power Function of the Sign Test

Abstract The power function of the one sided, one-sample sign test is studied for populations which deviate from exact normality, either by skewness, kurtosis, or both. The terms of the Edgeworth asymptotic expansion of order more than N −3/2 are used to represent the population density. Three sets of hypotheses and alternatives, concerning the location of (1) the median, (2) the mean, and (3) the median as approximated by the mean and coefficient of skewness, are considered in an attempt to make valid comparisons between the power of the sign test and Student's t test under the same conditions. Numerical results are given for samples of size 10, significance level .05, and for several combinations of the coefficients of skewness and kurtosis. The computations reveal that in general the sign test performs well in comparison with the t test, and in the case of leptokurtic distributions, there is almost no difference in power.