A gamma goodness-of-fit test based on characteristic independence of the mean and coefficient of variation

2008 ◽  
Vol 138 (12) ◽  
pp. 3813-3821 ◽  
Author(s):  
Gregory E. Wilding ◽  
Govind S. Mudholkar
Keyword(s):  
Coefficient Of Variation ◽  
Goodness Of Fit ◽  
Goodness Of Fit Test ◽  
The Mean

scholarly journals Consistency Bands for the Mean Excess Function and Application to Graphical Goodness-of-fit Test for Financial Data

2016 ◽  
Vol 8 (1) ◽  
pp. 42
Author(s):  
Amadou Diadie Ba ◽  
El Hadj Deme ◽  
Cheikh Tidiane Seck ◽  
Gane Samb Lo
Keyword(s):  
Goodness Of Fit ◽  
Empirical Processes ◽  
Financial Data ◽  
Generalized Hyperbolic Distribution ◽  
Goodness Of Fit Test ◽  
Excess Function ◽  
Monthly Data ◽  
Hyperbolic Distribution ◽  
Mean Excess Function ◽  
The Mean

<p>In this paper, we use the modern setting of functional empirical processes and recent techniques on uniform estimation for non parametric objects to derive consistency bands for the mean excess function in the i.i.d. case. We apply our results for modelling Dow Jones data to see how good the Generalized hyperbolic distribution fits monthly data.</p>

scholarly journals A Cautionary Note on the Use of the Kolmogorov–Smirnov Test for Normality

2007 ◽  
Vol 135 (3) ◽  
pp. 1151-1157 ◽  
Author(s):  
Dag J. Steinskog ◽  
Dag B. Tjøstheim ◽  
Nils G. Kvamstø
Keyword(s):  
Goodness Of Fit ◽  
Small Sample ◽  
Power Comparison ◽  
Goodness Of Fit Test ◽  
Kolmogorov Smirnov ◽  
The Mean ◽  
Small Sample Problem ◽  
Tests For Normality ◽  
Test For Normality ◽  
Smirnov Test

Abstract The Kolmogorov–Smirnov goodness-of-fit test is used in many applications for testing normality in climate research. This note shows that the test usually leads to systematic and drastic errors. When the mean and the standard deviation are estimated, it is much too conservative in the sense that its p values are strongly biased upward. One may think that this is a small sample problem, but it is not. There is a correction of the Kolmogorov–Smirnov test by Lilliefors, which is in fact sometimes confused with the original Kolmogorov–Smirnov test. Both the Jarque–Bera and the Shapiro–Wilk tests for normality are good alternatives to the Kolmogorov–Smirnov test. A power comparison of eight different tests has been undertaken, favoring the Jarque–Bera and the Shapiro–Wilk tests. The Jarque–Bera and the Kolmogorov–Smirnov tests are also applied to a monthly mean dataset of geopotential height at 500 hPa. The two tests give very different results and illustrate the danger of using the Kolmogorov–Smirnov test.

scholarly journals P118 External validation of model predicting early-onset surgery in Crohn’s Disease patients

2021 ◽  
Vol 15 (Supplement_1) ◽  
pp. S209-S210
Author(s):  
J Yao ◽  
B Hu ◽  
H Wang ◽  
M Zhi
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Early Onset ◽  
Goodness Of Fit ◽  
Clinical Decision Making ◽  
External Validation ◽  
Therapeutic Strategies ◽  
Goodness Of Fit Test ◽  
The Mean

Abstract Background Screening Crohn’s disease (CD) patients with high risk of early-onset surgery is crucial in launching therapeutic strategies. We have already identified disease behavior, smoking, body mass index, C-reactive protein level at diagnosis, previous perianal or intestinal surgery, maximum bowel wall thickness, use of biologics, and exclusive enteral nutrition as independent significant factors associated with 1-year surgery surgeries risk and further established a prognostic model (Fig.1,World J Gastroenterol. 2020;26(5):524–534). We aimed to validate this model using external cohort. Methods This retrospective study was conducted from Jan, 1, 2017, to Dec, 31, 2019 in three tertiary referral centers including Sixth Affiliated Hospital of Sun Yat-Sen University, Second Affiliated Hospital of Zhejiang University, and Second Affiliated Hospital of Military Medical University. Data of patients with a confirmed diagnosis of CD were collected through hospital electronic system. The published model was validated with calibration using the Hosmer-Lemeshow goodness-of-fit test, and discrimination was assessed using areas under the curve (AUC). Results A total of 756 patients were enrolled in our study with 101 (13.4%) excluded for the sake of incomplete data and loss of follow-up. Of the enrolled patients, 74.8% were male (n = 490) at the mean age of 28.4 ± 11.0 years, with the mean follow-up period of 21.8 ± 8.1 months. An ideal predictive ability of this model was confirmed by receiver operating characteristic curves and AUC as high as 94.5%. Besides, acceptable sensitivity of 69.5% and excellent specificity of 97.0% supported further clinical promotion and application of this model. Conclusion This model owns ideal ability to predict 1-year surgery risk in CD patients, which definitely help clinical decision-making and acid therapeutic strategies launching.

Adjusting a subject-specific time of event in longitudinal studies

2019 ◽  
Vol 29 (7) ◽  
pp. 1787-1798
Author(s):  
Hyunkeun Ryan Cho ◽  
Seonjin Kim ◽  
Myung Hee Lee
Keyword(s):  
Goodness Of Fit ◽  
Real Life ◽  
Model Parameters ◽  
Specific Time ◽  
Goodness Of Fit Test ◽  
Proposed Model ◽  
Subject Specific ◽  
The Subject ◽  
The Mean ◽  
Over Time

Biomedical studies often involve an event that occurs to individuals at different times and has a significant influence on individual trajectories of response variables over time. We propose a statistical model to capture the mean trajectory alteration caused by not only the occurrence of the event but also the subject-specific time of the event. The proposed model provides a post-event mean trajectory smoothly connected with the pre-event mean trajectory by allowing the model parameters associated with the post-event mean trajectory to vary over time of the event. A goodness-of-fit test is considered to investigate how well the proposed model is fit to the data. Hypothesis tests are also developed to assess the influence of the subject-specific time of event on the mean trajectory. Theoretical and simulation studies confirm that the proposed tests choose the correctly specified model consistently and examine the effect of the subject-specific time of event successfully. The proposed model and tests are also illustrated by the analysis of two real-life data from a biomarker study for HIV patients along with their own time of treatment initiation and a body fatness study in girls with different age of menarche.

The Relationship between Innovation Orientation and Strategic Typology in Business Firms

2016 ◽  
Vol 6 (2) ◽  
pp. 1-20 ◽  
Author(s):  
Parviz Kafchehi ◽  
Kaveh Hasani ◽  
Arman Gholami
Keyword(s):  
Significant Relationship ◽  
Goodness Of Fit ◽  
Goodness Of Fit Test ◽  
Chi Square ◽  
Test Analysis ◽  
Statistical Population ◽  
Chi Square Test ◽  
The Mean ◽  
Executive Managers ◽  
The Relationship

The aim of this study is to investigate the relationship between innovation orientation and strategic typology in firms such a way that a classification on the organization's orientation toward innovation and strategy could be obtained. The statistical population includes high executive managers of firms who have been acting in 4 industries of banking (B), food (F), insurance (I), and pharmacy (P), and have been the five pioneering firms in these industries. To test the hypothesis, the mean test analysis, the Goodness- of- Fit- Test, Chi- square test, and cross- tables were used and tested by SPSS18 software. The results show that there is a significant relationship between the firm's orientation toward innovation and competitive strategy; the more firm's orientation toward innovation, the firms uses more Prospector strategy, and their strategies have a more aggressive state. This paper provides a richer understanding of innovation orientation and strategic typology formation for similar firms.

scholarly journals A New Goodness of Fit Test for Multivariate Normality and Comparative Simulation Study

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3003
Author(s):  
Jurgita Arnastauskaitė ◽  
Tomas Ruzgas ◽  
Mindaugas Bražėnas
Keyword(s):  
Goodness Of Fit ◽  
Distribution Density ◽  
Empirical Distribution ◽  
Real Data ◽  
Multivariate Normality ◽  
Data Sets ◽  
Goodness Of Fit Test ◽  
Absolute Deviation ◽  
Test For Multivariate Normality ◽  
The Mean

The testing of multivariate normality remains a significant scientific problem. Although it is being extensively researched, it is still unclear how to choose the best test based on the sample size, variance, covariance matrix and others. In order to contribute to this field, a new goodness of fit test for multivariate normality is introduced. This test is based on the mean absolute deviation of the empirical distribution density from the theoretical distribution density. A new test was compared with the most popular tests in terms of empirical power. The power of the tests was estimated for the selected alternative distributions and examined by the Monte Carlo modeling method for the chosen sample sizes and dimensions. Based on the modeling results, it can be concluded that a new test is one of the most powerful tests for checking multivariate normality, especially for smaller samples. In addition, the assumption of normality of two real data sets was checked.

Semiparametric Inference for Proportional Mean Past Life Model

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Z. Mansourvar ◽  
M. Asadi
Keyword(s):  
Goodness Of Fit ◽  
Asymptotic Properties ◽  
Model Parameters ◽  
Goodness Of Fit Test ◽  
Data Set ◽  
Semiparametric Inference ◽  
Expected Time ◽  
Life Model ◽  
Past Life ◽  
The Mean

Abstract The mean past lifetime provides the expected time elapsed since the failure of a subject given that he/she has failed before the time of observation. In this paper, we propose the proportional mean past lifetime model to study the association between the mean past lifetime function and potential regression covariates. In the presence of left censoring, martingale estimating equations are developed to estimate the model parameters, and the asymptotic properties of the resulting estimators are studied. To assess the adequacy of the model, a goodness of fit test is also investigated. The proposed method is evaluated via simulation studies and further applied to a data set.

Evaluation of Northwest University, Kano Post-UTME Test Items Using Item Response Theory

2016 ◽  
Vol 5 (4) ◽  
pp. 261
Author(s):  
Ado Abdu Bichi ◽  
Hadiza Hafiz ◽  
Samira Abdullahi Bello
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Goodness Of Fit ◽  
Item Difficulty ◽  
High Stakes Testing ◽  
Test Reliability ◽  
Response Theory ◽  
Goodness Of Fit Test ◽  
Test Items ◽  
The Mean

High-stakes testing is used for the purposes of providing results that have important consequences. Validity is the cornerstone upon which all measurement systems are built. This study applied the Item Response Theory principles to analyse Northwest University Kano Post-UTME Economics test items. The developed fifty (50) economics test items was administered to a sample of 600 students. The data obtained was analysed using XCALIBRE 4 and SPSS 20v softwares to determine items parameters base on IRT models. Indicate that, the test measure single trait by satisfying the condition of unidimensionality. Similarly, the goodness of fit test revealed that, the two parameter IRT model was more suitable since no misfit item was observed and the test reliability was 0.86. The mean examinee ability was 0.07 (SD=0.94). The mean item difficulty was -0.63(SD=2.54) and mean item discrimination was 0.28 (SD=0.04). 16 (33%) items were identified as “problematic” based on difficulty indices, 35(71%) also failed to meet the set standards on the basis of discrimination parameters. it can be concluded that, using the IRT approach, the NWU Post-UTME items are not stable as far as item difficulty and discrimination indices are concerned. It is recommended that, the Post-UTME items should be made to pass through all process of standardisation and validation; test development and content experts should be involve in developing and validating the test items in order to obtain valid and reliable results which will lead to valid inferences

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