Statistical properties of Odd Frѐchet Lomax Distribution

A new lifetime distribution with three parameters, called odd Frѐchet Lomax (OFrL), is introduced. Some statistical properties of the OFrL are provided. Explicit expressions for the quntile, moments, moment generating function, probability weighted moments and order statistics are studied. Maximum likelihood estimation technique is employed to estimate the model parameters are studied. In addition, the superiority of the OFrL distribution is illustrated with applications to one real data set. Keywords: Odd Frѐchet -G family; Lomax distribution, Order statistics; moments. DOI: 10.7176/MTM/9-1-0

Are these data real? Statistical methods for the detection of data fabrication in clinical trials.

OBJECTIVES: To test the application of statistical methods to detect data fabrication in a clinical trial. SETTING: Data from two clinical trials: a trial of a dietary intervention for cardiovascular disease and a trial of a drug intervention for the same problem. OUTCOME MEASURES: Baseline comparisons of means and variances of cardiovascular risk factors; digit preference overall and its pattern by group. RESULTS: In the dietary intervention trial, variances for 16 of the 22 variables available at baseline were significantly different, and 10 significant differences were seen in means for these variables. Some of these P values were extraordinarily small. Distributions of the final recorded digit were significantly different between the intervention and the control group at baseline for 14/22 variables in the dietary trial. In the drug trial, only five variables were available, and no significant differences between the groups for baseline values in means or variances or digit preference were seen. CONCLUSIONS: Several statistical features of the data from the dietary trial are so strongly suggestive of data fabrication that no other explanation is likely

A statistical investigation of fraud and misconduct in clinical trials

Research misconduct can arise In any area of research and can discredit the findings. Research misconduct at any level is unacceptable, especially in a clinical trial. Because the results from clinical trials are used to decide whether or not treatments are effective, and affect decisions that may influence treatment choices for large numbers of patients, the prevention and detection of scientific misconduct in clinical trials is particularly important. Chapter 1 outlines some definitions of research misconduct, discusses the underlying motivations behind it, and the overall prevalence of research misconduct beyond that occurring in clinical trials. Different ways to detect and prevent research misconduct are also presented. In addition, an initial insight into the types of scientific misconduct that have been reported as occurring in clinical trials, based on a search of the PubMed database between January 2000 and July 2003 is provided. Thirty-eight published reports were found, but they provide no indication of the relative importance of different types of scientific misconduct in clinical trials. Chapter 2 presents a three-round Delphi survey aimed at achieving consensus among experts in clinical trials on what types of scientific misconduct are most likely to occur, and are most likely to influence the results of a clinical trial. This study identified thirteen forms of scientific misconduct for which there was consensus (>50%) that they would be likely or very likely to distort the results and consensus (>50%) that they would be likely or very likely to occur. Of these, the over-interpretation of 'significant' findings in small trials, selective reporting and inappropriate sub-group analyses were the main themes. To prevent such types of misconduct in clinical trials, the issue of selective reporting of outcomes or sub-group analyses and the opportunistic use of the play of chance (inappropriate sub-group analyses) should be addressed. Full details of the primary and secondary outcomes and sub-group analyses need to be specified clearly in protocols. Any sub-group analyses reported without pre-specification in the protocol would need supporting evidence within the publication for them to be justified. Chapter 3 explores selective reporting and inappropriate sub-group analyses within a cohort of randomised trial protocols approved by the Lancet. It determines the prevalence of selective reporting of primary and secondary outcomes and sub-group analyses in published reports of randomised trials. It also examines how sub-group analyses are described in protocols and how sub-group analyses are reported, and whether they match those specified in the protocol. Of 56 accepted protocols, four non-randomized trials were excluded. For the remaining 52, permission to review them was obtained for 48 (92%). Of those 48 trials, 30 (63%) trials were published. This study identifies some shortcomings in the reporting of the results of primary and secondary outcomes and sub-group analyses. It shows at least one unreported primary, secondary or sub-group analysis in 37%, 87%, and 50% of the trials, respectively. It also shows that the pre-specification and reporting of sub-group analyses are often incomplete and inaccurate. The majority of protocols gave hardly any detail on this matter. There was notable deviation from the protocols in reports in several of the trials. Data fabrication and falsification were judged by the experts in the Delphi survey to be unlikely to occur. However, they can have major effects on the outcomes of clinical trials if it they do occur. A systematic review was conducted in chapter 4, to identify the available statistical techniques that could be used for the detection of data fabrication and falsification. Chapter 5 examines the ability of these statistical techniques to detect data fabrication in data from two randomised controlled trials. In one trial, the possibility of fabricated data had been raised by British Medical Journal (BM) referees and the data were considered likely to contain fraudulent elements. For comparison, a second trial, about which there were no such concerns, was analysed using the same techniques, and no hint appeared of any unusual or unexpected features was shown. Finally, chapter 6 contains some concluding remarks, a discussion of the strengths and weaknesses of this research and suggestions for future research.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

First Order Phase Transformation in Amorphous Ge25Se75 – xSbx Glasses

Non-isothermal Differential scanning calorimetry (DSC) technique was used to study the kinetics of first order phase transformation in Ge25Se75 – xSbx glasses. The X-ray diffraction (XRD) technique was employed to investigate the amorphous and crystalline phases in Ge25Se75 – xSbx glasses. From the heating rate dependences of crystallization temperature; the activation energy for crystallization and other kinetics parameters were derived. The temperature difference (Tc – Tg) and Tc is highest for the samples with 6 % of Sb. Hence, Ge25Se69Sb6 glass is most stable. The enthalpy released is found to be less for Ge25Se69Sb6 glass which further confirms its maximum stability. The activation energy of crystallization (Ec) is found to vary with compositions indicating a structural change due to the addition of Sb. The crystallization data are interpreted in terms of recent analyses developed for non-isothermal conditions. The present investigation indicates that both the glass transition and the crystallization processes occur in a single stage. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3101

A Comparison Study between Regression Models for Analyzing Anemia Diseases

Regression models are the suitable statistical techniques for drawing inferences about relationships among interrelated variables. These models are applicable in many ­fields, such as the social field, physical field, biological sciences, business and medical fields. Regression models are perhaps the most used of all data analysis methods. This research interests in comparing regression models and applying these models in analyzing two real data sets of anemia diseases.  Also, many evaluating methods are applied in the research to choose between models, determining variables that effective the anemia diseases.  The analysis of the results detects the best variables, the suitable model and the best criterion can be used with the medical data.

Novel Heating-Induced Reversion during Crystallization of Al-based Glassy Alloys.

Thermal stability and crystallization of three multicomponent glassy alloys, Al86Y7Ni5Co1Fe0.5Pd0.5, Al85Y8Ni5Co1Fe0.5Pd0.5 and Al84Y9Ni4Co1.5Fe0.5Pd1, were examined to assess the ability to form the mixture of amorphous (am) and fcc-aluminum (α-Al) phases. On heating, the glass transition into the supercooled liquid is shown by the 85Al and 84Al glasses. The crystallization sequences are [am] → [am + α-Al] → [α-Al + compounds] for the 86Al and 85Al alloys, and [am] → [am + α-Al + cubic AlxMy (M = Y, Ni, Co, Fe, Pd)] → [am + α-Al] → [α-Al + Al3Y + Al9(Co, Ni)2 + unknown phase] for the 84Al alloy. The glass transition appears even for the 85Al alloy where the primary phase is α-Al. The heating-induced reversion from [am + α-Al + multicomponent AlxMy] to [am + α-Al] for the 84Al alloy is abnormal, not previously observed in crystallization of glassy alloys, and seems to originate from instability of the metastable AlxMy compound, in which significant inhomogeneous strain is caused by the mixture of solute elements. This novel reversion phenomenon is encouraging for obtaining the [am + α-Al] mixture over a wide range of high temperature effective for the formation of Al-based high-strength nanostructured bulk alloys by warm working

Novel deformation-induced polymorphic crystallization and softening of Al-based amorphous alloys

© 2018 Acta Materialia Inc. Melt-spun amorphous ribbons of Al 90 Y 10 (at.%) (90Al) and Al 84 Y 8.5 Ni 4 Co 2 Pd 1 Fe 0.5 (84Al) are cold-rolled at near to liquid-nitrogen temperature or at room temperature, inducing partial crystallization to nanoscale fcc-Al (α-Al). The crystallization is characterized and contrasted with the distinct sequences of reactions on annealing 90Al and 84Al amorphous alloys. Rolling-induced crystallization leads to softening, opposite to the effect of nanocrystallization induced by annealing. The origins of the hardness changes are analyzed. The rolling induces novel polymorphic crystallization to α-Al with extended solid solubility. This transformation, which occurs equally in 84Al and 90Al, despite the much greater thermal stability of the former, allows the ribbons to retain good bending ductility, and delays the onset of embrittlement on subsequent annealing. Partial crystallization induced by cold-rolling is useful in avoiding the formation of compound phases associated with brittleness, and is a promising process for high-solute Al-based amorphous alloys to be further developed as structural materials