scholarly journals Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

2006 ◽  
Vol 134 (5) ◽  
pp. 1442-1453 ◽  
Author(s):  
Kuan-Man Xu
Keyword(s):  
Euclidean Distance ◽  
Probability Distributions ◽  
Statistical Tests ◽  
Statistical Significance ◽  
Bootstrap Method ◽  
Statistical Hypothesis ◽  
Object Size ◽  
Size Category ◽  
Significance Level ◽  
The Bootstrap Method

Abstract A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries–Matusita distance, and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called “cloud objects.” Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object, and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

scholarly journals Poverty in Germany – Statistical Inference and Decomposition

2011 ◽  
Vol 231 (2) ◽  
Author(s):  
Timm Bönke ◽  
Carsten Schröder
Keyword(s):  
Cross Sections ◽  
Regional Differences ◽  
Statistical Significance ◽  
Bootstrap Method ◽  
Single Parents ◽  
Sample Survey ◽  
German Sample ◽  
Socioeconomic Characteristics ◽  
New States ◽  
The Bootstrap Method

SummaryBased on six harmonized cross-sections of the German Sample Survey of Income and Expenditure, we study inter-temporal changes in poverty from year 1978 to 2003. Results are decomposed by region and household types, and the bootstrap method is applied to test for the statistical significance of all our findings. Across household types, single parents with children have the highest poverty risk.Most striking is a huge regional divide in poverty which only narrows slightly over the period under investigation: the incidence and the intensity of poverty are substantially higher in the New states. A nonlinear Oaxaca-Blinder decomposition is conducted to quantify the separate contribution of regional differences in households’ characteristics to the likelhood of being poor. Estimates from the decomposition indicate that differences in the distributions of socioeconomic characteristics play a negligible role for the 1993 poverty divide. Already in year 2003, however, differences in the distributions of characteristics explain more than fifty percent of the poverty divide, indicating that the poverty divide is likely to become a persistent phenomenon.

scholarly journals Statistical tests and their application in geodesy

Tehnika ◽  
2021 ◽  
Vol 76 (2) ◽  
pp. 147-154
Author(s):  
Anastasija Martinenko ◽  
Vesna Jevremović ◽  
Petko Vranić ◽  
Jovan Popović ◽  
Marko Pejić
Keyword(s):  
Statistical Data ◽  
Statistical Tests ◽  
Bootstrap Method ◽  
Nonparametric Tests ◽  
Statistical Test ◽  
Ratio Test ◽  
Correct Conclusion ◽  
Scientific Analysis ◽  
Measurement Results ◽  
The Bootstrap Method

The correct conclusion about the assumptions concerning some phenomena can be obtained only through scientific analysis of statistical data. The scientific procedure of verifying a hypothesis using measurement results is called a statistical test. Depending on whether the hypotheses about the parameters in the feature distribution are tested or the distribution as a whole is tested, a parametric or non-parametric test is selected. The most significant representatives of parametric tests are the Probability Ratio Test, the Neumann - Pearson Lemma and the Bootstrap method, while the Pearson x2 test and the Kolmogorov test are presented as representatives of nonparametric tests. The paper presents the theoretical basis of some methods used in construction of statistical tests with given examples in geodesy.

scholarly journals Knowledge of Adverse Events Following Immunization Reporting Tool and System Among Primary Healthcare Workers in Jigawa State

2020 ◽  
Vol 41 (S1) ◽  
pp. s308-s308
Author(s):  
Ahmad Umar ◽  
Muawiyyah Sufiyan ◽  
Dahiru Tukur ◽  
Mary Onoja-Alexander ◽  
Lawal Amadu ◽  
...  
Keyword(s):  
Adverse Events ◽  
Primary Healthcare ◽  
Statistical Tests ◽  
Statistical Significance ◽  
Sampling Technique ◽  
The State ◽  
Health Facilities ◽  
Cross Sectional ◽  
Significance Level ◽  
Immunization Services

Background: Adverse events following immunization (AEFI) surveillance largely depends on the ability of the healthcare worker (HCW) to timely detect and report cases using the correct reporting tools through an appropriate system. AEFI surveillance is carried out regularly during both routine immunization services and supplemental immunization activities in the state. Objective: We assessed knowledge of adverse events following immunization reporting tools and system among primary HCWs in Jigawa state, northwestern Nigeria. Method: A descriptive cross-sectional design was used for this study. A multistage sampling technique was used to select 290 HCWs that had spent at least 6 months in immunization units of primary healthcare centers of Jigawa state. Data were collected using pretested self-administered structured questionnaire with open and closed ended questions and were analyzed using IBM SPSS version 20 software. All statistical tests were 2-tailed with P < .05 as the statistical significance level. Results: Most of the primary HCWs (93.2%) had AEFI reporting forms in their health facilities, and 68.9% said that the AEFI reporting form could be obtained from a focal or contact person in the health facility. Up to 96.4% of the primary HCWs were aware of how to report AEFI. Also, ~76.6% of primary HCWs knew the correct AEFI reporting flow, but only 15.8% knew that only serious AEFIs are reported. Furthermore, ~78.8% and 19.4% of HCWs mentioned telephone and filling forms as some of the appropriate methods of AEFI notification, respectively. Conclusions: Most primary HCWs had reporting forms in their health facilities and were aware of how to report an AEFI. Most of the respondents knew the correct AEFI reporting flow. The state in collaboration with local government authorities should provide quality training on AEFI reporting and reporting system.Funding: NoneDisclosures: None

scholarly journals Assessment of reliability and validity of Montenegrin version of the oral health impact profile for use among the elderly in Montenegro

2019 ◽  
Vol 147 (9-10) ◽  
pp. 534-540
Author(s):  
Zorica Popovic ◽  
Mirjana Djurickovic ◽  
Agima Ljaljevic ◽  
Snezana Matijevic ◽  
Kosovka Obradovic-Djuricic
Keyword(s):  
Quality Of Life ◽  
Oral Health ◽  
Statistical Tests ◽  
Statistical Significance ◽  
Reliability And Validity ◽  
The Elderly ◽  
Health Impact ◽  
Oral Health Impact Profile ◽  
Significance Level

Introduction/Objective. The quality of life of elderly individuals has an active function in oral health; it is of great importance to learn that elders over the age of 65 years demonstrate an increase in seeking dental services. Oral Health Impact Profile-14 (OHIP-14) is especially suitable for use in the elderly. The aim of this study is to examine the reliability and validity of OHIP-14 in the Montenegrin population aged 65 and over and to determine the influence of oral health on the quality of their life. Methods. The research was conducted from September to December 2016 in the central region of Montenegro, at the Medical University in Podgorica and in the nursing homes of the elderly. The study covered 170 individuals, both sexes, with an average age of 72.32 ? 6.85. The research instrument is OHIP-14 index. Standard statistical tests were used. The statistical significance level is 0.05. Results. The OHIP-14is linguistically and culturally adapted for the Montenegrin population. The value of the Cronbach Alpha Index is 0.892. The relationship between correlations for individual issues and total correlations ranges from 0.21 to 0.69. The value of OHIP-14 is 19.24 ? 7.49. Listed by domains: functional constraints 3.31 ? 1.75; physical pain 4.19 ? 1.31; psychological discomfort 2.52 ? 1.46; physical fitness 4.38 ? 1.40; mental incompetence 1.42 ? 1.23; social incapacity 1.18 ? 1.27 and handicap 2.21 ? 1.32. Conclusion. The OHIP-14 index is reliable and valid and is recommended for use in the Montenegrinspeaking area, for the elderly. There is a significant impact of oral health on the quality of life of the elderly in the central part of Montenegro.

scholarly journals Can innovative trend analysis identify trend change points?

2020 ◽  
Vol 1 (3) ◽  
pp. 6-15
Author(s):  
Sadık Alashan
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Statistical Significance ◽  
Bootstrap Method ◽  
Change Points ◽  
Trend Detection ◽  
Significance Level ◽  
Related Data ◽  
Innovative Trend Analysis ◽  
June July

Trends in temperature series are the main cause of climate change. Because solar energy directs hydro-meteorological events and increasing variations in this resource change the balance between events such as evaporation, wind, and rainfall. There are many methods for calculating trends in a time series such as Mann-Kendall, Sen's slope estimator, Spearman's rho, linear regression and the new Sen innovative trend analysis (ITA). In addition, Mann-Kendall's variant, the sequential Mann Kendall, has been developed to identify trend change points; however, it is sensitive to related data as specified by some researchers. Şen_ITA is a new trend detection method and does not require independent and normally distributed time series, but has never been used to detect trend change points. In the literature, multiple, half-time and multi-durations ITA methods are used to calculate partial trends in a time series without identifying trend change points. In this study, trend change points are detected using the Şen_ITA method and named ITA_TCP. This approach may allow researchers to identify trend change points in a time series. Diyarbakır (Turkey) is selected as a study area, and ITA_TCP has detected trends and trends change points in monthly average temperatures. Although ITA detects only a significant upward trend in August, given the 95% statistical significance level, ITA_TCP shows three upward trends in June, July and August, and a decreasing trend in September. Critical trend slope values are obtained using the bootstrap method, which does not require the normal distribution assumption.

scholarly journals Can innovative trend analysis identify trend change points?

2020 ◽  
Vol 1 (3) ◽  
pp. 6-15
Author(s):  
Sadık Alashan
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Statistical Significance ◽  
Bootstrap Method ◽  
Change Points ◽  
Trend Detection ◽  
Significance Level ◽  
Related Data ◽  
Innovative Trend Analysis ◽  
June July

Trends in temperature series are the main cause of climate change. Because solar energy directs hydro-meteorological events and increasing variations in this resource change the balance between events such as evaporation, wind, and rainfall. There are many methods for calculating trends in a time series such as Mann-Kendall, Sen's slope estimator, Spearman's rho, linear regression and the new Sen innovative trend analysis (ITA). In addition, Mann-Kendall's variant, the sequential Mann Kendall, has been developed to identify trend change points; however, it is sensitive to related data as specified by some researchers. Şen_ITA is a new trend detection method and does not require independent and normally distributed time series, but has never been used to detect trend change points. In the literature, multiple, half-time and multi-durations ITA methods are used to calculate partial trends in a time series without identifying trend change points. In this study, trend change points are detected using the Şen_ITA method and named ITA_TCP. This approach may allow researchers to identify trend change points in a time series. Diyarbakır (Turkey) is selected as a study area, and ITA_TCP has detected trends and trends change points in monthly average temperatures. Although ITA detects only a significant upward trend in August, given the 95% statistical significance level, ITA_TCP shows three upward trends in June, July and August, and a decreasing trend in September. Critical trend slope values are obtained using the bootstrap method, which does not require the normal distribution assumption.

scholarly journals Analisis Spasial berdasarkan Indeks Getis Ord Data Laju Inflasi Tahunan di Pulau Sumatra

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Yuni Naomi Yenusi ◽  
Adi Setiawan ◽  
Lilik Linawati
Keyword(s):  
Spatial Autocorrelation ◽  
Inflation Rate ◽  
Bootstrap Method ◽  
Spatial Cluster ◽  
Significance Level ◽  
Significant Difference ◽  
High Inflation ◽  
The City ◽  
Banda Aceh ◽  
The Bootstrap Method

This study discusses the analysis of year-on-year inflation data on the island of Sumatra using the Getis-Ord General G index and the Getis-Ord Gi* Index, which will be compared with the Bootstrap Method. And the Mann Withney Test for comparison of two time periods. The results showed that the highest average inflation was in Pangkal Pinang City by 5.82, and the lowest was in Banda Aceh City by 3.63. There is a significant difference in the median inflation rate from the cities of inflation on the island of Sumatra except in the cities of Banda Aceh, Palembang and Batam. With a significance level alpha = 5%, it is concluded that there are spatial cluster and spatial autocorrelation patterns in February 2014. Cities with high inflation value cluster with its neighbors are the city of Pangkal Pinang, and the low inflation value cluster is Banda Aceh. It means that a region is close to other regions has a similar level of inflation in terms of high and low at a certain time. In other words, commodities contributing to inflation between adjacent regions are interrelated. Keywords—Getis-Ord General G Index, Getis-Ord Gi* Indeks, Inflation, Spatial Autocorrelation, Spatial cluster.

scholarly journals Field Significance Revisited: Spatial Bias Errors in Forecasts as Applied to the Eta Model

2006 ◽  
Vol 134 (2) ◽  
pp. 519-531 ◽  
Author(s):  
Kimberly L. Elmore ◽  
Michael E. Baldwin ◽  
David M. Schultz
Keyword(s):  
Statistical Significance ◽  
Bootstrap Method ◽  
Bias Error ◽  
Forecast Errors ◽  
Spatial Bias ◽  
Significance Level ◽  
Spatially Correlated ◽  
The Face ◽  
Moving Blocks Bootstrap ◽  
Eta Model

Abstract The spatial structure of bias errors in numerical model output is valuable to both model developers and operational forecasters, especially if the field containing the structure itself has statistical significance in the face of naturally occurring spatial correlation. A semiparametric Monte Carlo method, along with a moving blocks bootstrap method is used to determine the field significance of spatial bias errors within spatially correlated error fields. This process can be completely automated, making it an attractive addition to the verification tools already in use. The process demonstrated here results in statistically significant spatial bias error fields at any arbitrary significance level. To demonstrate the technique, 0000 and 1200 UTC runs of the operational Eta Model and the operational Eta Model using the Kain–Fritsch convective parameterization scheme are examined. The resulting fields for forecast errors for geopotential heights and winds at 850, 700, 500, and 250 hPa over a period of 14 months (26 January 2001–31 March 2002) are examined and compared using the verifying initial analysis. Specific examples are shown, and some plausible causes for the resulting significant bias errors are proposed.

scholarly journals Comparison of the power of statistical tests in connection with the discussion about the reproducibility criterion

2018 ◽  
Vol 15 (5) ◽  
pp. 4-14
Author(s):  
V. E. Osipov
Keyword(s):  
Effect Size ◽  
Statistical Tests ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Mathematical Formulation ◽  
Random Component ◽  
Significance Level ◽  
Two Samples ◽  
Methodology Of Science ◽  
Typical Length

The criterion of reproducibility, as well as its functioning in post-non-classical science, are discussed in the Russian methodology of science. At the same time, critics avoid statistical calculations in their arguments. This raises the following questions: “What is reproducibility?” and “What is the mathematical formulation of the reproducibility criterion?” Literature review has identified five indicators of reproducibility, which was proposed by foreign colleagues. These indicators are being tested and discussed. However, there is no General mathematical formulation of the reproducibility criterion (an integral criterion covering these indicators), and these indicators have not yet become a standard. In the present work, we compare two statistical tests, related to one of these five indicators of reproducibility.Purpose of the study. The aim of this paper is to compare the powers of two tests of statistical significance that can be used to reveal the effect with the requirement of reproducibility of research results. In this case, the reproducibility is estimated by the indicator “significance”. In accordance with the first criterion, the effect is considered to be revealed if the effect size in all studies is significant (i.e. if the significance of the effect size is reproduced in all studies). In accordance with the second criterion, the effect is considered to be revealed if the weighted mean of the effect size obtained as a result of meta-analysis is significant (the significance of the effect size may be absent in individual studies).Materials and methods. Methods of mathematical statistics are used to achieve this goal. The powers of two tests are compared by two estimates. The first estimate is theoretical. The second one was obtained during a statistical experiment. The powers are calculated: 1) for different values of the Cohen’s effect size: “small”, “medium” and “large”, 2) for different degree of heterogeneity: zero (fixed-effect primary studies (from 2 to 8).Results. The power of the first test is less or much less than the power of the second one. The power of the first test decreases with the growth of the number of primary studies, and the power of the second one increases. Taking into account the conventional power value equal to 80%, the first criterion is unsuitable for use in the considered values of the parameters of primary studies (that is, if a two-tailed t-test with the significance level of 0.05 and with two samples of the typical length n=25 is used to determine the significance of the effect size in individual studies), while the power of the second test can be increased if necessary by increasing the number of primary studies included in the meta-analysis.Conclusion. If the criterion of reproducibility, known from the philosophy of science, is intended to confirm the existence of the effect (connection) or, in other words, to reveal the effect, in conditions where there is a significant random component in the measurement process, it is advisable to apply not the first, but the second test.

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