Statistical methods in personality assessment research.

PubMed

Schinka, J A; LaLone, L; Broeckel, J A

1997-06-01

Emerging models of personality structure and advances in the measurement of personality and psychopathology suggest that research in personality and personality assessment has entered a stage of advanced development, in this article we examine whether researchers in these areas have taken advantage of new and evolving statistical procedures. We conducted a review of articles published in the Journal of Personality, Assessment during the past 5 years. Of the 449 articles that included some form of data analysis, 12.7% used only descriptive statistics, most employed only univariate statistics, and fewer than 10% used multivariate methods of data analysis. We discuss the cost of using limited statistical methods, the possible reasons for the apparent reluctance to employ advanced statistical procedures, and potential solutions to this technical shortcoming.

Statistical methods and errors in family medicine articles between 2010 and 2014-Suez Canal University, Egypt: A cross-sectional study.

PubMed

Nour-Eldein, Hebatallah

2016-01-01

With limited statistical knowledge of most physicians it is not uncommon to find statistical errors in research articles. To determine the statistical methods and to assess the statistical errors in family medicine (FM) research articles that were published between 2010 and 2014. This was a cross-sectional study. All 66 FM research articles that were published over 5 years by FM authors with affiliation to Suez Canal University were screened by the researcher between May and August 2015. Types and frequencies of statistical methods were reviewed in all 66 FM articles. All 60 articles with identified inferential statistics were examined for statistical errors and deficiencies. A comprehensive 58-item checklist based on statistical guidelines was used to evaluate the statistical quality of FM articles. Inferential methods were recorded in 62/66 (93.9%) of FM articles. Advanced analyses were used in 29/66 (43.9%). Contingency tables 38/66 (57.6%), regression (logistic, linear) 26/66 (39.4%), and t-test 17/66 (25.8%) were the most commonly used inferential tests. Within 60 FM articles with identified inferential statistics, no prior sample size 19/60 (31.7%), application of wrong statistical tests 17/60 (28.3%), incomplete documentation of statistics 59/60 (98.3%), reporting P value without test statistics 32/60 (53.3%), no reporting confidence interval with effect size measures 12/60 (20.0%), use of mean (standard deviation) to describe ordinal/nonnormal data 8/60 (13.3%), and errors related to interpretation were mainly for conclusions without support by the study data 5/60 (8.3%). Inferential statistics were used in the majority of FM articles. Data analysis and reporting statistics are areas for improvement in FM research articles.

Practical statistics in pain research.

PubMed

Kim, Tae Kyun

2017-10-01

Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.

Statistical Methodologies to Integrate Experimental and Computational Research

NASA Technical Reports Server (NTRS)

Parker, P. A.; Johnson, R. T.; Montgomery, D. C.

2008-01-01

Development of advanced algorithms for simulating engine flow paths requires the integration of fundamental experiments with the validation of enhanced mathematical models. In this paper, we provide an overview of statistical methods to strategically and efficiently conduct experiments and computational model refinement. Moreover, the integration of experimental and computational research efforts is emphasized. With a statistical engineering perspective, scientific and engineering expertise is combined with statistical sciences to gain deeper insights into experimental phenomenon and code development performance; supporting the overall research objectives. The particular statistical methods discussed are design of experiments, response surface methodology, and uncertainty analysis and planning. Their application is illustrated with a coaxial free jet experiment and a turbulence model refinement investigation. Our goal is to provide an overview, focusing on concepts rather than practice, to demonstrate the benefits of using statistical methods in research and development, thereby encouraging their broader and more systematic application.

Integration of Research Studies: Meta-Analysis of Research. Methods of Integrative Analysis; Final Report.

ERIC Educational Resources Information Center

Glass, Gene V.; And Others

Integrative analysis, or what is coming to be known as meta-analysis, is the integration of the findings of many empirical research studies of a topic. Meta-analysis differs from traditional narrative forms of research reviewing in that it is more quantitative and statistical. Thus, the methods of meta-analysis are merely statistical methods,…

Best Practices in Teaching Statistics and Research Methods in the Behavioral Sciences [with CD-ROM

ERIC Educational Resources Information Center

Dunn, Dana S., Ed.; Smith, Randolph A., Ed.; Beins, Barney, Ed.

2007-01-01

This book provides a showcase for "best practices" in teaching statistics and research methods in two- and four-year colleges and universities. A helpful resource for teaching introductory, intermediate, and advanced statistics and/or methods, the book features coverage of: (1) ways to integrate these courses; (2) how to promote ethical conduct;…

Towards evidence-based computational statistics: lessons from clinical research on the role and design of real-data benchmark studies.

PubMed

Boulesteix, Anne-Laure; Wilson, Rory; Hapfelmeier, Alexander

2017-09-09

The goal of medical research is to develop interventions that are in some sense superior, with respect to patient outcome, to interventions currently in use. Similarly, the goal of research in methodological computational statistics is to develop data analysis tools that are themselves superior to the existing tools. The methodology of the evaluation of medical interventions continues to be discussed extensively in the literature and it is now well accepted that medicine should be at least partly "evidence-based". Although we statisticians are convinced of the importance of unbiased, well-thought-out study designs and evidence-based approaches in the context of clinical research, we tend to ignore these principles when designing our own studies for evaluating statistical methods in the context of our methodological research. In this paper, we draw an analogy between clinical trials and real-data-based benchmarking experiments in methodological statistical science, with datasets playing the role of patients and methods playing the role of medical interventions. Through this analogy, we suggest directions for improvement in the design and interpretation of studies which use real data to evaluate statistical methods, in particular with respect to dataset inclusion criteria and the reduction of various forms of bias. More generally, we discuss the concept of "evidence-based" statistical research, its limitations and its impact on the design and interpretation of real-data-based benchmark experiments. We suggest that benchmark studies-a method of assessment of statistical methods using real-world datasets-might benefit from adopting (some) concepts from evidence-based medicine towards the goal of more evidence-based statistical research.

Quantitative Methods for Analysing Joint Questionnaire Data: Exploring the Role of Joint in Force Design

DTIC Science & Technology

2015-08-01

the nine questions. The Statistical Package for the Social Sciences ( SPSS ) [11] was used to conduct statistical analysis on the sample. Two types...constructs. SPSS was again used to conduct statistical analysis on the sample. This time factor analysis was conducted. Factor analysis attempts to...Business Research Methods and Statistics using SPSS . P432. 11 IBM SPSS Statistics . (2012) 12 Burns, R.B., Burns, R.A. (2008) ‘Business Research

Understanding common statistical methods, Part I: descriptive methods, probability, and continuous data.

PubMed

Skinner, Carl G; Patel, Manish M; Thomas, Jerry D; Miller, Michael A

2011-01-01

Statistical methods are pervasive in medical research and general medical literature. Understanding general statistical concepts will enhance our ability to critically appraise the current literature and ultimately improve the delivery of patient care. This article intends to provide an overview of the common statistical methods relevant to medicine.

[Statistics for statistics?--Thoughts about psychological tools].

PubMed

Berger, Uwe; Stöbel-Richter, Yve

2007-12-01

Statistical methods take a prominent place among psychologists' educational programs. Being known as difficult to understand and heavy to learn, students fear of these contents. Those, who do not aspire after a research carrier at the university, will forget the drilled contents fast. Furthermore, because it does not apply for the work with patients and other target groups at a first glance, the methodological education as a whole was often questioned. For many psychological practitioners the statistical education makes only sense by enforcing respect against other professions, namely physicians. For the own business, statistics is rarely taken seriously as a professional tool. The reason seems to be clear: Statistics treats numbers, while psychotherapy treats subjects. So, does statistics ends in itself? With this article, we try to answer the question, if and how statistical methods were represented within the psychotherapeutical and psychological research. Therefore, we analyzed 46 Originals of a complete volume of the journal Psychotherapy, Psychosomatics, Psychological Medicine (PPmP). Within the volume, 28 different analyse methods were applied, from which 89 per cent were directly based upon statistics. To be able to write and critically read Originals as a backbone of research, presumes a high degree of statistical education. To ignore statistics means to ignore research and at least to reveal the own professional work to arbitrariness.

Applying Bayesian statistics to the study of psychological trauma: A suggestion for future research.

PubMed

Yalch, Matthew M

2016-03-01

Several contemporary researchers have noted the virtues of Bayesian methods of data analysis. Although debates continue about whether conventional or Bayesian statistics is the "better" approach for researchers in general, there are reasons why Bayesian methods may be well suited to the study of psychological trauma in particular. This article describes how Bayesian statistics offers practical solutions to the problems of data non-normality, small sample size, and missing data common in research on psychological trauma. After a discussion of these problems and the effects they have on trauma research, this article explains the basic philosophical and statistical foundations of Bayesian statistics and how it provides solutions to these problems using an applied example. Results of the literature review and the accompanying example indicates the utility of Bayesian statistics in addressing problems common in trauma research. Bayesian statistics provides a set of methodological tools and a broader philosophical framework that is useful for trauma researchers. Methodological resources are also provided so that interested readers can learn more. (c) 2016 APA, all rights reserved).

P-Value Club: Teaching Significance Level on the Dance Floor

ERIC Educational Resources Information Center

Gray, Jennifer

2010-01-01

Courses: Beginning research methods and statistics courses, as well as advanced communication courses that require reading research articles and completing research projects involving statistics. Objective: Students will understand the difference between significant and nonsignificant statistical results based on p-value.

Students' Perceptions of Statistics: An Exploration of Attitudes, Conceptualizations, and Content Knowledge of Statistics

ERIC Educational Resources Information Center

Bond, Marjorie E.; Perkins, Susan N.; Ramirez, Caroline

2012-01-01

Although statistics education research has focused on students' learning and conceptual understanding of statistics, researchers have only recently begun investigating students' perceptions of statistics. The term perception describes the overlap between cognitive and non-cognitive factors. In this mixed-methods study, undergraduate students…

An instrument to assess the statistical intensity of medical research papers.

PubMed

Nieminen, Pentti; Virtanen, Jorma I; Vähänikkilä, Hannu

2017-01-01

There is widespread evidence that statistical methods play an important role in original research articles, especially in medical research. The evaluation of statistical methods and reporting in journals suffers from a lack of standardized methods for assessing the use of statistics. The objective of this study was to develop and evaluate an instrument to assess the statistical intensity in research articles in a standardized way. A checklist-type measure scale was developed by selecting and refining items from previous reports about the statistical contents of medical journal articles and from published guidelines for statistical reporting. A total of 840 original medical research articles that were published between 2007-2015 in 16 journals were evaluated to test the scoring instrument. The total sum of all items was used to assess the intensity between sub-fields and journals. Inter-rater agreement was examined using a random sample of 40 articles. Four raters read and evaluated the selected articles using the developed instrument. The scale consisted of 66 items. The total summary score adequately discriminated between research articles according to their study design characteristics. The new instrument could also discriminate between journals according to their statistical intensity. The inter-observer agreement measured by the ICC was 0.88 between all four raters. Individual item analysis showed very high agreement between the rater pairs, the percentage agreement ranged from 91.7% to 95.2%. A reliable and applicable instrument for evaluating the statistical intensity in research papers was developed. It is a helpful tool for comparing the statistical intensity between sub-fields and journals. The novel instrument may be applied in manuscript peer review to identify papers in need of additional statistical review.

Reporting guidance considerations from a statistical perspective: overview of tools to enhance the rigour of reporting of randomised trials and systematic reviews.

PubMed

Hutton, Brian; Wolfe, Dianna; Moher, David; Shamseer, Larissa

2017-05-01

Research waste has received considerable attention from the biomedical community. One noteworthy contributor is incomplete reporting in research publications. When detailing statistical methods and results, ensuring analytic methods and findings are completely documented improves transparency. For publications describing randomised trials and systematic reviews, guidelines have been developed to facilitate complete reporting. This overview summarises aspects of statistical reporting in trials and systematic reviews of health interventions. A narrative approach to summarise features regarding statistical methods and findings from reporting guidelines for trials and reviews was taken. We aim to enhance familiarity of statistical details that should be reported in biomedical research among statisticians and their collaborators. We summarise statistical reporting considerations for trials and systematic reviews from guidance documents including the Consolidated Standards of Reporting Trials (CONSORT) Statement for reporting of trials, the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) Statement for trial protocols, the Statistical Analyses and Methods in the Published Literature (SAMPL) Guidelines for statistical reporting principles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement for systematic reviews and PRISMA for Protocols (PRISMA-P). Considerations regarding sharing of study data and statistical code are also addressed. Reporting guidelines provide researchers with minimum criteria for reporting. If followed, they can enhance research transparency and contribute improve quality of biomedical publications. Authors should employ these tools for planning and reporting of their research. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Making Social Work Count: A Curriculum Innovation to Teach Quantitative Research Methods and Statistical Analysis to Undergraduate Social Work Students in the United Kingdom

ERIC Educational Resources Information Center

Teater, Barbra; Roy, Jessica; Carpenter, John; Forrester, Donald; Devaney, John; Scourfield, Jonathan

2017-01-01

Students in the United Kingdom (UK) are found to lack knowledge and skills in quantitative research methods. To address this gap, a quantitative research method and statistical analysis curriculum comprising 10 individual lessons was developed, piloted, and evaluated at two universities The evaluation found that BSW students' (N = 81)…

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

Situating Qualitative Modes of Inquiry within the Discipline of Statistics Education Research

ERIC Educational Resources Information Center

Groth, Randall E.

2010-01-01

Qualitative methods have become common in statistics education research, but questions linger about their role in scholarship. Currently, influential policy documents lend credence to the notion that qualitative methods are inherently inferior to quantitative ones. In this paper, several of the questions about qualitative research raised in recent…

Predicting Acquisition of Learning Outcomes: A Comparison of Traditional and Activity-Based Instruction in an Introductory Statistics Course.

ERIC Educational Resources Information Center

Geske, Jenenne A.; Mickelson, William T.; Bandalos, Deborah L.; Jonson, Jessica; Smith, Russell W.

The bulk of experimental research related to reforms in the teaching of statistics concentrates on the effects of alternative teaching methods on statistics achievement. This study expands on that research by including an examination of the effects of instructor and the interaction between instructor and method on achievement as well as attitudes,…

Statistics used in current nursing research.

PubMed

Zellner, Kathleen; Boerst, Connie J; Tabb, Wil

2007-02-01

Undergraduate nursing research courses should emphasize the statistics most commonly used in the nursing literature to strengthen students' and beginning researchers' understanding of them. To determine the most commonly used statistics, we reviewed all quantitative research articles published in 13 nursing journals in 2000. The findings supported Beitz's categorization of kinds of statistics. Ten primary statistics used in 80% of nursing research published in 2000 were identified. We recommend that the appropriate use of those top 10 statistics be emphasized in undergraduate nursing education and that the nursing profession continue to advocate for the use of methods (e.g., power analysis, odds ratio) that may contribute to the advancement of nursing research.

Computational methods to extract meaning from text and advance theories of human cognition.

PubMed

McNamara, Danielle S

2011-01-01

Over the past two decades, researchers have made great advances in the area of computational methods for extracting meaning from text. This research has to a large extent been spurred by the development of latent semantic analysis (LSA), a method for extracting and representing the meaning of words using statistical computations applied to large corpora of text. Since the advent of LSA, researchers have developed and tested alternative statistical methods designed to detect and analyze meaning in text corpora. This research exemplifies how statistical models of semantics play an important role in our understanding of cognition and contribute to the field of cognitive science. Importantly, these models afford large-scale representations of human knowledge and allow researchers to explore various questions regarding knowledge, discourse processing, text comprehension, and language. This topic includes the latest progress by the leading researchers in the endeavor to go beyond LSA. Copyright © 2010 Cognitive Science Society, Inc.

Quantitative methods used in Australian health promotion research: a review of publications from 1992-2002.

PubMed

Smith, Ben J; Zehle, Katharina; Bauman, Adrian E; Chau, Josephine; Hawkshaw, Barbara; Frost, Steven; Thomas, Margaret

2006-04-01

This study examined the use of quantitative methods in Australian health promotion research in order to identify methodological trends and priorities for strengthening the evidence base for health promotion. Australian health promotion articles were identified by hand searching publications from 1992-2002 in six journals: Health Promotion Journal of Australia, Australian and New Zealand journal of Public Health, Health Promotion International, Health Education Research, Health Education and Behavior and the American Journal of Health Promotion. The study designs and statistical methods used in articles presenting quantitative research were recorded. 591 (57.7%) of the 1,025 articles used quantitative methods. Cross-sectional designs were used in the majority (54.3%) of studies with pre- and post-test (14.6%) and post-test only (9.5%) the next most common designs. Bivariate statistical methods were used in 45.9% of papers, multivariate methods in 27.1% and simple numbers and proportions in 25.4%. Few studies used higher-level statistical techniques. While most studies used quantitative methods, the majority were descriptive in nature. The study designs and statistical methods used provided limited scope for demonstrating intervention effects or understanding the determinants of change.

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics

PubMed Central

Allen, Peter J.; Dorozenko, Kate P.; Roberts, Lynne D.

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these “experts” were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an “answer.” Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities. PMID:26909064

Difficult Decisions: A Qualitative Exploration of the Statistical Decision Making Process from the Perspectives of Psychology Students and Academics.

PubMed

Allen, Peter J; Dorozenko, Kate P; Roberts, Lynne D

2016-01-01

Quantitative research methods are essential to the development of professional competence in psychology. They are also an area of weakness for many students. In particular, students are known to struggle with the skill of selecting quantitative analytical strategies appropriate for common research questions, hypotheses and data types. To begin understanding this apparent deficit, we presented nine psychology undergraduates (who had all completed at least one quantitative methods course) with brief research vignettes, and asked them to explicate the process they would follow to identify an appropriate statistical technique for each. Thematic analysis revealed that all participants found this task challenging, and even those who had completed several research methods courses struggled to articulate how they would approach the vignettes on more than a very superficial and intuitive level. While some students recognized that there is a systematic decision making process that can be followed, none could describe it clearly or completely. We then presented the same vignettes to 10 psychology academics with particular expertise in conducting research and/or research methods instruction. Predictably, these "experts" were able to describe a far more systematic, comprehensive, flexible, and nuanced approach to statistical decision making, which begins early in the research process, and pays consideration to multiple contextual factors. They were sensitive to the challenges that students experience when making statistical decisions, which they attributed partially to how research methods and statistics are commonly taught. This sensitivity was reflected in their pedagogic practices. When asked to consider the format and features of an aid that could facilitate the statistical decision making process, both groups expressed a preference for an accessible, comprehensive and reputable resource that follows a basic decision tree logic. For the academics in particular, this aid should function as a teaching tool, which engages the user with each choice-point in the decision making process, rather than simply providing an "answer." Based on these findings, we offer suggestions for tools and strategies that could be deployed in the research methods classroom to facilitate and strengthen students' statistical decision making abilities.

The statistical reporting quality of articles published in 2010 in five dental journals.

PubMed

Vähänikkilä, Hannu; Tjäderhane, Leo; Nieminen, Pentti

2015-01-01

Statistical methods play an important role in medical and dental research. In earlier studies it has been observed that current use of methods and reporting of statistics are responsible for some of the errors in the interpretation of results. The aim of this study was to investigate the quality of statistical reporting in dental research articles. A total of 200 articles published in 2010 were analysed covering five dental journals: Journal of Dental Research, Caries Research, Community Dentistry and Oral Epidemiology, Journal of Dentistry and Acta Odontologica Scandinavica. Each paper underwent careful scrutiny for the use of statistical methods and reporting. A paper with at least one poor reporting item has been classified as 'problems with reporting statistics' and a paper without any poor reporting item as 'acceptable'. The investigation showed that 18 (9%) papers were acceptable and 182 (91%) papers contained at least one poor reporting item. The proportion of at least one poor reporting item in this survey was high (91%). The authors of dental journals should be encouraged to improve the statistical section of their research articles and to present the results in such a way that it is in line with the policy and presentation of the leading dental journals.

Managing Clustered Data Using Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.

2012-01-01

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

[Prosthodontic research design from the standpoint of statistical analysis: learning and knowing the research design].

PubMed

Tanoue, Naomi

2007-10-01

For any kind of research, "Research Design" is the most important. The design is used to structure the research, to show how all of the major parts of the research project. It is necessary for all the researchers to begin the research after planning research design for what is the main theme, what is the background and reference, what kind of data is needed, and what kind of analysis is needed. It seems to be a roundabout route, but, in fact, it will be a shortcut. The research methods must be appropriate to the objectives of the study. Regarding the hypothesis-testing research that is the traditional style of the research, the research design based on statistics is undoubtedly necessary considering that the research basically proves "a hypothesis" with data and statistics theory. On the subject of the clinical trial, which is the clinical version of the hypothesis-testing research, the statistical method must be mentioned in a clinical trial planning. This report describes the basis of the research design for a prosthodontics study.

Truths, lies, and statistics.

PubMed

Thiese, Matthew S; Walker, Skyler; Lindsey, Jenna

2017-10-01

Distribution of valuable research discoveries are needed for the continual advancement of patient care. Publication and subsequent reliance of false study results would be detrimental for patient care. Unfortunately, research misconduct may originate from many sources. While there is evidence of ongoing research misconduct in all it's forms, it is challenging to identify the actual occurrence of research misconduct, which is especially true for misconduct in clinical trials. Research misconduct is challenging to measure and there are few studies reporting the prevalence or underlying causes of research misconduct among biomedical researchers. Reported prevalence estimates of misconduct are probably underestimates, and range from 0.3% to 4.9%. There have been efforts to measure the prevalence of research misconduct; however, the relatively few published studies are not freely comparable because of varying characterizations of research misconduct and the methods used for data collection. There are some signs which may point to an increased possibility of research misconduct, however there is a need for continued self-policing by biomedical researchers. There are existing resources to assist in ensuring appropriate statistical methods and preventing other types of research fraud. These included the "Statistical Analyses and Methods in the Published Literature", also known as the SAMPL guidelines, which help scientists determine the appropriate method of reporting various statistical methods; the "Strengthening Analytical Thinking for Observational Studies", or the STRATOS, which emphases on execution and interpretation of results; and the Committee on Publication Ethics (COPE), which was created in 1997 to deliver guidance about publication ethics. COPE has a sequence of views and strategies grounded in the values of honesty and accuracy.

The Preparedness of Preservice Secondary Mathematics Teachers to Teach Statistics: A Cross-Institutional Mixed Methods Study

ERIC Educational Resources Information Center

Lovett, Jennifer Nickell

2016-01-01

The purpose of this study is to provide researchers, mathematics educators, and statistics educators information about the current state of preservice secondary mathematics teachers' preparedness to teach statistics. To do so, this study employed an explanatory mixed methods design to quantitatively examine the statistical knowledge and statistics…

[Application of statistics on chronic-diseases-relating observational research papers].

PubMed

Hong, Zhi-heng; Wang, Ping; Cao, Wei-hua

2012-09-01

To study the application of statistics on Chronic-diseases-relating observational research papers which were recently published in the Chinese Medical Association Magazines, with influential index above 0.5. Using a self-developed criterion, two investigators individually participated in assessing the application of statistics on Chinese Medical Association Magazines, with influential index above 0.5. Different opinions reached an agreement through discussion. A total number of 352 papers from 6 magazines, including the Chinese Journal of Epidemiology, Chinese Journal of Oncology, Chinese Journal of Preventive Medicine, Chinese Journal of Cardiology, Chinese Journal of Internal Medicine and Chinese Journal of Endocrinology and Metabolism, were reviewed. The rate of clear statement on the following contents as: research objectives, t target audience, sample issues, objective inclusion criteria and variable definitions were 99.43%, 98.57%, 95.43%, 92.86% and 96.87%. The correct rates of description on quantitative and qualitative data were 90.94% and 91.46%, respectively. The rates on correctly expressing the results, on statistical inference methods related to quantitative, qualitative data and modeling were 100%, 95.32% and 87.19%, respectively. 89.49% of the conclusions could directly response to the research objectives. However, 69.60% of the papers did not mention the exact names of the study design, statistically, that the papers were using. 11.14% of the papers were in lack of further statement on the exclusion criteria. Percentage of the papers that could clearly explain the sample size estimation only taking up as 5.16%. Only 24.21% of the papers clearly described the variable value assignment. Regarding the introduction on statistical conduction and on database methods, the rate was only 24.15%. 18.75% of the papers did not express the statistical inference methods sufficiently. A quarter of the papers did not use 'standardization' appropriately. As for the aspect of statistical inference, the rate of description on statistical testing prerequisite was only 24.12% while 9.94% papers did not even employ the statistical inferential method that should be used. The main deficiencies on the application of Statistics used in papers related to Chronic-diseases-related observational research were as follows: lack of sample-size determination, variable value assignment description not sufficient, methods on statistics were not introduced clearly or properly, lack of consideration for pre-requisition regarding the use of statistical inferences.

Enhancing the Equating of Item Difficulty Metrics: Estimation of Reference Distribution. Research Report. ETS RR-14-07

ERIC Educational Resources Information Center

Ali, Usama S.; Walker, Michael E.

2014-01-01

Two methods are currently in use at Educational Testing Service (ETS) for equating observed item difficulty statistics. The first method involves the linear equating of item statistics in an observed sample to reference statistics on the same items. The second method, or the item response curve (IRC) method, involves the summation of conditional…

The change and development of statistical methods used in research articles in child development 1930-2010.

PubMed

Køppe, Simo; Dammeyer, Jesper

2014-09-01

The evolution of developmental psychology has been characterized by the use of different quantitative and qualitative methods and procedures. But how does the use of methods and procedures change over time? This study explores the change and development of statistical methods used in articles published in Child Development from 1930 to 2010. The methods used in every article in the first issue of every volume were categorized into four categories. Until 1980 relatively simple statistical methods were used. During the last 30 years there has been an explosive use of more advanced statistical methods employed. The absence of statistical methods or use of simple methods had been eliminated.

Analysis of Statistical Methods and Errors in the Articles Published in the Korean Journal of Pain

PubMed Central

Yim, Kyoung Hoon; Han, Kyoung Ah; Park, Soo Young

2010-01-01

Background Statistical analysis is essential in regard to obtaining objective reliability for medical research. However, medical researchers do not have enough statistical knowledge to properly analyze their study data. To help understand and potentially alleviate this problem, we have analyzed the statistical methods and errors of articles published in the Korean Journal of Pain (KJP), with the intention to improve the statistical quality of the journal. Methods All the articles, except case reports and editorials, published from 2004 to 2008 in the KJP were reviewed. The types of applied statistical methods and errors in the articles were evaluated. Results One hundred and thirty-nine original articles were reviewed. Inferential statistics and descriptive statistics were used in 119 papers and 20 papers, respectively. Only 20.9% of the papers were free from statistical errors. The most commonly adopted statistical method was the t-test (21.0%) followed by the chi-square test (15.9%). Errors of omission were encountered 101 times in 70 papers. Among the errors of omission, "no statistics used even though statistical methods were required" was the most common (40.6%). The errors of commission were encountered 165 times in 86 papers, among which "parametric inference for nonparametric data" was the most common (33.9%). Conclusions We found various types of statistical errors in the articles published in the KJP. This suggests that meticulous attention should be given not only in the applying statistical procedures but also in the reviewing process to improve the value of the article. PMID:20552071

Statistical Methods in Psychology Journals.

ERIC Educational Resources Information Center

Willkinson, Leland

1999-01-01

Proposes guidelines for revising the American Psychological Association (APA) publication manual or other APA materials to clarify the application of statistics in research reports. The guidelines are intended to induce authors and editors to recognize the thoughtless application of statistical methods. Contains 54 references. (SLD)

The Role of Statistics and Research Methods in the Academic Success of Psychology Majors: Do Performance and Enrollment Timing Matter?

ERIC Educational Resources Information Center

Freng, Scott; Webber, David; Blatter, Jamin; Wing, Ashley; Scott, Walter D.

2011-01-01

Comprehension of statistics and research methods is crucial to understanding psychology as a science (APA, 2007). However, psychology majors sometimes approach methodology courses with derision or anxiety (Onwuegbuzie & Wilson, 2003; Rajecki, Appleby, Williams, Johnson, & Jeschke, 2005); consequently, students may postpone…

Preparing and Presenting Effective Research Posters

PubMed Central

Miller, Jane E

2007-01-01

Objectives Posters are a common way to present results of a statistical analysis, program evaluation, or other project at professional conferences. Often, researchers fail to recognize the unique nature of the format, which is a hybrid of a published paper and an oral presentation. This methods note demonstrates how to design research posters to convey study objectives, methods, findings, and implications effectively to varied professional audiences. Methods A review of existing literature on research communication and poster design is used to identify and demonstrate important considerations for poster content and layout. Guidelines on how to write about statistical methods, results, and statistical significance are illustrated with samples of ineffective writing annotated to point out weaknesses, accompanied by concrete examples and explanations of improved presentation. A comparison of the content and format of papers, speeches, and posters is also provided. Findings Each component of a research poster about a quantitative analysis should be adapted to the audience and format, with complex statistical results translated into simplified charts, tables, and bulleted text to convey findings as part of a clear, focused story line. Conclusions Effective research posters should be designed around two or three key findings with accompanying handouts and narrative description to supply additional technical detail and encourage dialog with poster viewers. PMID:17355594

Conducting Simulation Studies in the R Programming Environment.

PubMed

Hallgren, Kevin A

2013-10-12

Simulation studies allow researchers to answer specific questions about data analysis, statistical power, and best-practices for obtaining accurate results in empirical research. Despite the benefits that simulation research can provide, many researchers are unfamiliar with available tools for conducting their own simulation studies. The use of simulation studies need not be restricted to researchers with advanced skills in statistics and computer programming, and such methods can be implemented by researchers with a variety of abilities and interests. The present paper provides an introduction to methods used for running simulation studies using the R statistical programming environment and is written for individuals with minimal experience running simulation studies or using R. The paper describes the rationale and benefits of using simulations and introduces R functions relevant for many simulation studies. Three examples illustrate different applications for simulation studies, including (a) the use of simulations to answer a novel question about statistical analysis, (b) the use of simulations to estimate statistical power, and (c) the use of simulations to obtain confidence intervals of parameter estimates through bootstrapping. Results and fully annotated syntax from these examples are provided.

Engaging Students in Survey Research Projects across Research Methods and Statistics Courses

ERIC Educational Resources Information Center

Lovekamp, William E.; Soboroff, Shane D.; Gillespie, Michael D.

2017-01-01

One innovative way to help students make sense of survey research has been to create a multifaceted, collaborative assignment that promotes critical thinking, comparative analysis, self-reflection, and statistical literacy. We use a short questionnaire adapted from the Higher Education Research Institute's Cooperative Institutional Research…

Content-Related Issues Pertaining to Teaching Statistics: Making Decisions about Educational Objectives in Statistics Courses.

ERIC Educational Resources Information Center

Bliss, Leonard B.; Tashakkori, Abbas

This paper discusses the objectives that would be appropriate for statistics classes for students who are not majoring in statistics, evaluation, or quantitative research design. These "non-majors" should be able to choose appropriate analytical methods for specific sets of data based on the research question and the nature of the data, and they…

Common method biases in behavioral research: a critical review of the literature and recommended remedies.

PubMed

Podsakoff, Philip M; MacKenzie, Scott B; Lee, Jeong-Yeon; Podsakoff, Nathan P

2003-10-01

Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.

Statistics in the pharmacy literature.

PubMed

Lee, Charlene M; Soin, Herpreet K; Einarson, Thomas R

2004-09-01

Research in statistical methods is essential for maintenance of high quality of the published literature. To update previous reports of the types and frequencies of statistical terms and procedures in research studies of selected professional pharmacy journals. We obtained all research articles published in 2001 in 6 journals: American Journal of Health-System Pharmacy, The Annals of Pharmacotherapy, Canadian Journal of Hospital Pharmacy, Formulary, Hospital Pharmacy, and Journal of the American Pharmaceutical Association. Two independent reviewers identified and recorded descriptive and inferential statistical terms/procedures found in the methods, results, and discussion sections of each article. Results were determined by tallying the total number of times, as well as the percentage, that each statistical term or procedure appeared in the articles. One hundred forty-four articles were included. Ninety-eight percent employed descriptive statistics; of these, 28% used only descriptive statistics. The most common descriptive statistical terms were percentage (90%), mean (74%), standard deviation (58%), and range (46%). Sixty-nine percent of the articles used inferential statistics, the most frequent being chi(2) (33%), Student's t-test (26%), Pearson's correlation coefficient r (18%), ANOVA (14%), and logistic regression (11%). Statistical terms and procedures were found in nearly all of the research articles published in pharmacy journals. Thus, pharmacy education should aim to provide current and future pharmacists with an understanding of the common statistical terms and procedures identified to facilitate the appropriate appraisal and consequential utilization of the information available in research articles.

Cluster detection methods applied to the Upper Cape Cod cancer data.

PubMed

Ozonoff, Al; Webster, Thomas; Vieira, Veronica; Weinberg, Janice; Ozonoff, David; Aschengrau, Ann

2005-09-15

A variety of statistical methods have been suggested to assess the degree and/or the location of spatial clustering of disease cases. However, there is relatively little in the literature devoted to comparison and critique of different methods. Most of the available comparative studies rely on simulated data rather than real data sets. We have chosen three methods currently used for examining spatial disease patterns: the M-statistic of Bonetti and Pagano; the Generalized Additive Model (GAM) method as applied by Webster; and Kulldorff's spatial scan statistic. We apply these statistics to analyze breast cancer data from the Upper Cape Cancer Incidence Study using three different latency assumptions. The three different latency assumptions produced three different spatial patterns of cases and controls. For 20 year latency, all three methods generally concur. However, for 15 year latency and no latency assumptions, the methods produce different results when testing for global clustering. The comparative analyses of real data sets by different statistical methods provides insight into directions for further research. We suggest a research program designed around examining real data sets to guide focused investigation of relevant features using simulated data, for the purpose of understanding how to interpret statistical methods applied to epidemiological data with a spatial component.

Statistical methods used in articles published by the Journal of Periodontal and Implant Science.

PubMed

Choi, Eunsil; Lyu, Jiyoung; Park, Jinyoung; Kim, Hae-Young

2014-12-01

The purposes of this study were to assess the trend of use of statistical methods including parametric and nonparametric methods and to evaluate the use of complex statistical methodology in recent periodontal studies. This study analyzed 123 articles published in the Journal of Periodontal & Implant Science (JPIS) between 2010 and 2014. Frequencies and percentages were calculated according to the number of statistical methods used, the type of statistical method applied, and the type of statistical software used. Most of the published articles considered (64.4%) used statistical methods. Since 2011, the percentage of JPIS articles using statistics has increased. On the basis of multiple counting, we found that the percentage of studies in JPIS using parametric methods was 61.1%. Further, complex statistical methods were applied in only 6 of the published studies (5.0%), and nonparametric statistical methods were applied in 77 of the published studies (38.9% of a total of 198 studies considered). We found an increasing trend towards the application of statistical methods and nonparametric methods in recent periodontal studies and thus, concluded that increased use of complex statistical methodology might be preferred by the researchers in the fields of study covered by JPIS.

Stats on the Cheap: Using Free and Inexpensive Internet Resources to Enhance the Teaching of Statistics and Research Methods

ERIC Educational Resources Information Center

Hartnett, Jessica L.

2013-01-01

The present article describes four free or inexpensive Internet-based activities that can be used to supplement statistics/research methods/general psychology classes. Each activity and subsequent homework assessment is described, as well as homework performance outcome and student opinion data for each activity. (Contains 1 table.)

Organization and Carrying out the Educational Experiment and Statistical Analysis of Its Results in IHL

ERIC Educational Resources Information Center

Sidorov, Oleg V.; Kozub, Lyubov' V.; Goferberg, Alexander V.; Osintseva, Natalya V.

2018-01-01

The article discusses the methodological approach to the technology of the educational experiment performance, the ways of the research data processing by means of research methods and methods of mathematical statistics. The article shows the integrated use of some effective approaches to the training of the students majoring in…

Demonstrating the Effectiveness of an Integrated and Intensive Research Methods and Statistics Course Sequence

ERIC Educational Resources Information Center

Pliske, Rebecca M.; Caldwell, Tracy L.; Calin-Jageman, Robert J.; Taylor-Ritzler, Tina

2015-01-01

We developed a two-semester series of intensive (six-contact hours per week) behavioral research methods courses with an integrated statistics curriculum. Our approach includes the use of team-based learning, authentic projects, and Excel and SPSS. We assessed the effectiveness of our approach by examining our students' content area scores on the…

Statistical Methods Used in "American Educational Research Journal,""Journal of Educational Psychology," and "Sociology of Education" from 1972 through 1987.

ERIC Educational Resources Information Center

Emmons, Nancy J.; And Others

The use of particular statistical methods over time was studied in a review of publications from the disciplines of education, psychology, and sociology. Publications studied were the: (1) "American Educational Research Journal"; (2) "Journal of Educational Psychology"; and (3) "Sociology of Education". A total of 221…

A Meta-Analytic Review of Studies of the Effectiveness of Small-Group Learning Methods on Statistics Achievement

ERIC Educational Resources Information Center

Kalaian, Sema A.; Kasim, Rafa M.

2014-01-01

This meta-analytic study focused on the quantitative integration and synthesis of the accumulated pedagogical research in undergraduate statistics education literature. These accumulated research studies compared the academic achievement of students who had been instructed using one of the various forms of small-group learning methods to those who…

Peer-Assisted Learning in Research Methods and Statistics

ERIC Educational Resources Information Center

Stone, Anna; Meade, Claire; Watling, Rosamond

2012-01-01

Feedback from students on a Level 1 Research Methods and Statistics module, studied as a core part of a BSc Psychology programme, highlighted demand for additional tutorials to help them to understand basic concepts. Students in their final year of study commonly request work experience to enhance their employability. All students on the Level 1…

A smoothed residual based goodness-of-fit statistic for nest-survival models

Treesearch

Rodney X. Sturdivant; Jay J. Rotella; Robin E. Russell

2008-01-01

Estimating nest success and identifying important factors related to nest-survival rates is an essential goal for many wildlife researchers interested in understanding avian population dynamics. Advances in statistical methods have led to a number of estimation methods and approaches to modeling this problem. Recently developed models allow researchers to include a...

Static Methods in the Design of Nonlinear Automatic Control Systems,

DTIC Science & Technology

1984-06-27

227 Chapter VI. Ways of Decrease of the Number of Statistical Nodes During the Research of Nonlinear Systems...at present occupies the central place. This region of research was called the statistical dynamics of nonlinear H automatic control systems...receives further development in the numerous research of Soviet and C foreign scientists. Special role in the development of the statistical dynamics of

[Again review of research design and statistical methods of Chinese Journal of Cardiology].

PubMed

Kong, Qun-yu; Yu, Jin-ming; Jia, Gong-xian; Lin, Fan-li

2012-11-01

To re-evaluate and compare the research design and the use of statistical methods in Chinese Journal of Cardiology. Summary the research design and statistical methods in all of the original papers in Chinese Journal of Cardiology all over the year of 2011, and compared the result with the evaluation of 2008. (1) There is no difference in the distribution of the design of researches of between the two volumes. Compared with the early volume, the use of survival regression and non-parameter test are increased, while decreased in the proportion of articles with no statistical analysis. (2) The proportions of articles in the later volume are significant lower than the former, such as 6(4%) with flaws in designs, 5(3%) with flaws in the expressions, 9(5%) with the incomplete of analysis. (3) The rate of correction of variance analysis has been increased, so as the multi-group comparisons and the test of normality. The error rate of usage has been decreased form 17% to 25% without significance in statistics due to the ignorance of the test of homogeneity of variance. Many improvements showed in Chinese Journal of Cardiology such as the regulation of the design and statistics. The homogeneity of variance should be paid more attention in the further application.

Handbook of Research Methods in Social and Personality Psychology

NASA Astrophysics Data System (ADS)

Reis, Harry T.; Judd, Charles M.

2000-03-01

This volume provides an overview of research methods in contemporary social psychology. Coverage includes conceptual issues in research design, methods of research, and statistical approaches. Because the range of research methods available for social psychology have expanded extensively in the past decade, both traditional and innovative methods are presented. The goal is to introduce new and established researchers alike to new methodological developments in the field.

Antecedents to Organizational Performance: Theoretical and Practical Implications for Aircraft Maintenance Officer Force Development

DTIC Science & Technology

2015-03-26

to my reader, Lieutenant Colonel Robert Overstreet, for helping solidify my research, coaching me through the statistical analysis, and positive...61  Descriptive Statistics .............................................................................................................. 61...common-method bias requires careful assessment of potential sources of bias and implementing procedural and statistical control methods. Podsakoff

Counting Better? An Examination of the Impact of Quantitative Method Teaching on Statistical Anxiety and Confidence

ERIC Educational Resources Information Center

Chamberlain, John Martyn; Hillier, John; Signoretta, Paola

2015-01-01

This article reports the results of research concerned with students' statistical anxiety and confidence to both complete and learn to complete statistical tasks. Data were collected at the beginning and end of a quantitative method statistics module. Students recognised the value of numeracy skills but felt they were not necessarily relevant for…

A Mixed Method Investigation of Social Science Graduate Students' Statistics Anxiety Conditions before and after the Introductory Statistics Course

ERIC Educational Resources Information Center

Huang, Liuli

2018-01-01

Research frequently uses the quantitative approach to explore undergraduate students' anxiety regarding statistics. However, few studies of adults' statistics anxiety use the qualitative method, or a sole focus on graduate students. Moreover, even fewer studies focus on a comparison of adults' anxiety levels before and after an introductory…

Deconstructing Statistical Analysis

ERIC Educational Resources Information Center

Snell, Joel

2014-01-01

Using a very complex statistical analysis and research method for the sake of enhancing the prestige of an article or making a new product or service legitimate needs to be monitored and questioned for accuracy. 1) The more complicated the statistical analysis, and research the fewer the number of learned readers can understand it. This adds a…

Reporting Practices and Use of Quantitative Methods in Canadian Journal Articles in Psychology.

PubMed

Counsell, Alyssa; Harlow, Lisa L

2017-05-01

With recent focus on the state of research in psychology, it is essential to assess the nature of the statistical methods and analyses used and reported by psychological researchers. To that end, we investigated the prevalence of different statistical procedures and the nature of statistical reporting practices in recent articles from the four major Canadian psychology journals. The majority of authors evaluated their research hypotheses through the use of analysis of variance (ANOVA), t -tests, and multiple regression. Multivariate approaches were less common. Null hypothesis significance testing remains a popular strategy, but the majority of authors reported a standardized or unstandardized effect size measure alongside their significance test results. Confidence intervals on effect sizes were infrequently employed. Many authors provided minimal details about their statistical analyses and less than a third of the articles presented on data complications such as missing data and violations of statistical assumptions. Strengths of and areas needing improvement for reporting quantitative results are highlighted. The paper concludes with recommendations for how researchers and reviewers can improve comprehension and transparency in statistical reporting.

Meta-analysis and The Cochrane Collaboration: 20 years of the Cochrane Statistical Methods Group

PubMed Central

2013-01-01

The Statistical Methods Group has played a pivotal role in The Cochrane Collaboration over the past 20 years. The Statistical Methods Group has determined the direction of statistical methods used within Cochrane reviews, developed guidance for these methods, provided training, and continued to discuss and consider new and controversial issues in meta-analysis. The contribution of Statistical Methods Group members to the meta-analysis literature has been extensive and has helped to shape the wider meta-analysis landscape. In this paper, marking the 20th anniversary of The Cochrane Collaboration, we reflect on the history of the Statistical Methods Group, beginning in 1993 with the identification of aspects of statistical synthesis for which consensus was lacking about the best approach. We highlight some landmark methodological developments that Statistical Methods Group members have contributed to in the field of meta-analysis. We discuss how the Group implements and disseminates statistical methods within The Cochrane Collaboration. Finally, we consider the importance of robust statistical methodology for Cochrane systematic reviews, note research gaps, and reflect on the challenges that the Statistical Methods Group faces in its future direction. PMID:24280020

What Good Are Statistics that Don't Generalize?

ERIC Educational Resources Information Center

Shaffer, David Williamson; Serlin, Ronald C.

2004-01-01

Quantitative and qualitative inquiry are sometimes portrayed as distinct and incompatible paradigms for research in education. Approaches to combining qualitative and quantitative research typically "integrate" the two methods by letting them co-exist independently within a single research study. Here we describe intra-sample statistical analysis…

Statistics corner: A guide to appropriate use of correlation coefficient in medical research.

PubMed

Mukaka, M M

2012-09-01

Correlation is a statistical method used to assess a possible linear association between two continuous variables. It is simple both to calculate and to interpret. However, misuse of correlation is so common among researchers that some statisticians have wished that the method had never been devised at all. The aim of this article is to provide a guide to appropriate use of correlation in medical research and to highlight some misuse. Examples of the applications of the correlation coefficient have been provided using data from statistical simulations as well as real data. Rule of thumb for interpreting size of a correlation coefficient has been provided.

The Effect of Cluster Sampling Design in Survey Research on the Standard Error Statistic.

ERIC Educational Resources Information Center

Wang, Lin; Fan, Xitao

Standard statistical methods are used to analyze data that is assumed to be collected using a simple random sampling scheme. These methods, however, tend to underestimate variance when the data is collected with a cluster design, which is often found in educational survey research. The purposes of this paper are to demonstrate how a cluster design…

Statistical Methods in Integrative Genomics

PubMed Central

Richardson, Sylvia; Tseng, George C.; Sun, Wei

2016-01-01

Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then review statistical methods of integrative genomics, with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions. PMID:27482531

Enhancing predictive accuracy and reproducibility in clinical evaluation research: Commentary on the special section of the Journal of Evaluation in Clinical Practice.

PubMed

Bryant, Fred B

2016-12-01

This paper introduces a special section of the current issue of the Journal of Evaluation in Clinical Practice that includes a set of 6 empirical articles showcasing a versatile, new machine-learning statistical method, known as optimal data (or discriminant) analysis (ODA), specifically designed to produce statistical models that maximize predictive accuracy. As this set of papers clearly illustrates, ODA offers numerous important advantages over traditional statistical methods-advantages that enhance the validity and reproducibility of statistical conclusions in empirical research. This issue of the journal also includes a review of a recently published book that provides a comprehensive introduction to the logic, theory, and application of ODA in empirical research. It is argued that researchers have much to gain by using ODA to analyze their data. © 2016 John Wiley & Sons, Ltd.

Current and future health care professionals attitudes toward and knowledge of statistics: How confidence influences learning

PubMed Central

Baghi, Heibatollah; Kornides, Melanie L.

2014-01-01

Background Health care professionals require some understanding of statistics to successfully implement evidence based practice. Developing competency in statistical reasoning is necessary for students training in health care administration, research, and clinical care. Recently, the interest in healthcare professional's attitudes toward statistics has increased substantially due to evidence that these attitudes can hinder professionalism developing an understanding of statistical concepts. Methods In this study, we analyzed pre- and post-instruction attitudes towards and knowledge of statistics obtained from health science graduate students, including nurses and nurse practitioners, enrolled in an introductory graduate course in statistics (n = 165). Results and Conclusions Results show that the students already held generally positive attitudes toward statistics at the beginning of course. However, these attitudes—along with the students’ statistical proficiency—improved after 10 weeks of instruction. The results have implications for curriculum design and delivery methods as well as for health professionals’ effective use of statistics in critically evaluating and utilizing research in their practices. PMID:25419256

SSD for R: A Comprehensive Statistical Package to Analyze Single-System Data

ERIC Educational Resources Information Center

Auerbach, Charles; Schudrich, Wendy Zeitlin

2013-01-01

The need for statistical analysis in single-subject designs presents a challenge, as analytical methods that are applied to group comparison studies are often not appropriate in single-subject research. "SSD for R" is a robust set of statistical functions with wide applicability to single-subject research. It is a comprehensive package…

Quality of Death Rates by Race and Hispanic Origin: A Summary of Current Research, 1999. Vital and Health Statistics. Series 2: Data Evaluation and Methods Research. No. 128.

ERIC Educational Resources Information Center

National Center for Health Statistics (DHHS/PHS), Hyattsville, MD.

This report summarizes current knowledge and research on the quality and reliability of death rates by race and Hispanic origin in official mortality statistics of the United States produced by the National Center for Health Statistics (NCHS). It provides a quantitative assessment of bias in death rates by race and Hispanic origin and identifies…

[Applications of mathematical statistics methods on compatibility researches of traditional Chinese medicines formulae].

PubMed

Mai, Lan-Yin; Li, Yi-Xuan; Chen, Yong; Xie, Zhen; Li, Jie; Zhong, Ming-Yu

2014-05-01

The compatibility of traditional Chinese medicines (TCMs) formulae containing enormous information, is a complex component system. Applications of mathematical statistics methods on the compatibility researches of traditional Chinese medicines formulae have great significance for promoting the modernization of traditional Chinese medicines and improving clinical efficacies and optimizations of formulae. As a tool for quantitative analysis, data inference and exploring inherent rules of substances, the mathematical statistics method can be used to reveal the working mechanisms of the compatibility of traditional Chinese medicines formulae in qualitatively and quantitatively. By reviewing studies based on the applications of mathematical statistics methods, this paper were summarized from perspective of dosages optimization, efficacies and changes of chemical components as well as the rules of incompatibility and contraindication of formulae, will provide the references for further studying and revealing the working mechanisms and the connotations of traditional Chinese medicines.

[Triple-type theory of statistics and its application in the scientific research of biomedicine].

PubMed

Hu, Liang-ping; Liu, Hui-gang

2005-07-20

To point out the crux of why so many people failed to grasp statistics and to bring forth a "triple-type theory of statistics" to solve the problem in a creative way. Based on the experience in long-time teaching and research in statistics, the "three-type theory" was raised and clarified. Examples were provided to demonstrate that the 3 types, i.e., expressive type, prototype and the standardized type are the essentials for people to apply statistics rationally both in theory and practice, and moreover, it is demonstrated by some instances that the "three types" are correlated with each other. It can help people to see the essence by interpreting and analyzing the problems of experimental designs and statistical analyses in medical research work. Investigations reveal that for some questions, the three types are mutually identical; for some questions, the prototype is their standardized type; however, for some others, the three types are distinct from each other. It has been shown that in some multifactor experimental researches, it leads to the nonexistence of the standardized type corresponding to the prototype at all, because some researchers have committed the mistake of "incomplete control" in setting experimental groups. This is a problem which should be solved by the concept and method of "division". Once the "triple-type" for each question is clarified, a proper experimental design and statistical method can be carried out easily. "Triple-type theory of statistics" can help people to avoid committing statistical mistakes or at least to decrease the misuse rate dramatically and improve the quality, level and speed of biomedical research during the process of applying statistics. It can also help people to improve the quality of statistical textbooks and the teaching effect of statistics and it has demonstrated how to advance biomedical statistics.

Trends in statistical methods in articles published in Archives of Plastic Surgery between 2012 and 2017.

PubMed

Han, Kyunghwa; Jung, Inkyung

2018-05-01

This review article presents an assessment of trends in statistical methods and an evaluation of their appropriateness in articles published in the Archives of Plastic Surgery (APS) from 2012 to 2017. We reviewed 388 original articles published in APS between 2012 and 2017. We categorized the articles that used statistical methods according to the type of statistical method, the number of statistical methods, and the type of statistical software used. We checked whether there were errors in the description of statistical methods and results. A total of 230 articles (59.3%) published in APS between 2012 and 2017 used one or more statistical method. Within these articles, there were 261 applications of statistical methods with continuous or ordinal outcomes, and 139 applications of statistical methods with categorical outcome. The Pearson chi-square test (17.4%) and the Mann-Whitney U test (14.4%) were the most frequently used methods. Errors in describing statistical methods and results were found in 133 of the 230 articles (57.8%). Inadequate description of P-values was the most common error (39.1%). Among the 230 articles that used statistical methods, 71.7% provided details about the statistical software programs used for the analyses. SPSS was predominantly used in the articles that presented statistical analyses. We found that the use of statistical methods in APS has increased over the last 6 years. It seems that researchers have been paying more attention to the proper use of statistics in recent years. It is expected that these positive trends will continue in APS.

Towards sound epistemological foundations of statistical methods for high-dimensional biology.

PubMed

Mehta, Tapan; Tanik, Murat; Allison, David B

2004-09-01

A sound epistemological foundation for biological inquiry comes, in part, from application of valid statistical procedures. This tenet is widely appreciated by scientists studying the new realm of high-dimensional biology, or 'omic' research, which involves multiplicity at unprecedented scales. Many papers aimed at the high-dimensional biology community describe the development or application of statistical techniques. The validity of many of these is questionable, and a shared understanding about the epistemological foundations of the statistical methods themselves seems to be lacking. Here we offer a framework in which the epistemological foundation of proposed statistical methods can be evaluated.

Bayesian Statistics in Educational Research: A Look at the Current State of Affairs

ERIC Educational Resources Information Center

König, Christoph; van de Schoot, Rens

2018-01-01

The ability of a scientific discipline to build cumulative knowledge depends on its predominant method of data analysis. A steady accumulation of knowledge requires approaches which allow researchers to consider results from comparable prior research. Bayesian statistics is especially relevant for establishing a cumulative scientific discipline,…

IMPLEMENTATION AND VALIDATION OF STATISTICAL TESTS IN RESEARCH'S SOFTWARE HELPING DATA COLLECTION AND PROTOCOLS ANALYSIS IN SURGERY.

PubMed

Kuretzki, Carlos Henrique; Campos, Antônio Carlos Ligocki; Malafaia, Osvaldo; Soares, Sandramara Scandelari Kusano de Paula; Tenório, Sérgio Bernardo; Timi, Jorge Rufino Ribas

2016-03-01

The use of information technology is often applied in healthcare. With regard to scientific research, the SINPE(c) - Integrated Electronic Protocols was created as a tool to support researchers, offering clinical data standardization. By the time, SINPE(c) lacked statistical tests obtained by automatic analysis. Add to SINPE(c) features for automatic realization of the main statistical methods used in medicine . The study was divided into four topics: check the interest of users towards the implementation of the tests; search the frequency of their use in health care; carry out the implementation; and validate the results with researchers and their protocols. It was applied in a group of users of this software in their thesis in the strict sensu master and doctorate degrees in one postgraduate program in surgery. To assess the reliability of the statistics was compared the data obtained both automatically by SINPE(c) as manually held by a professional in statistics with experience with this type of study. There was concern for the use of automatic statistical tests, with good acceptance. The chi-square, Mann-Whitney, Fisher and t-Student were considered as tests frequently used by participants in medical studies. These methods have been implemented and thereafter approved as expected. The incorporation of the automatic SINPE (c) Statistical Analysis was shown to be reliable and equal to the manually done, validating its use as a research tool for medical research.

Comparing Methods for Item Analysis: The Impact of Different Item-Selection Statistics on Test Difficulty

ERIC Educational Resources Information Center

Jones, Andrew T.

2011-01-01

Practitioners often depend on item analysis to select items for exam forms and have a variety of options available to them. These include the point-biserial correlation, the agreement statistic, the B index, and the phi coefficient. Although research has demonstrated that these statistics can be useful for item selection, no research as of yet has…

Person Fit Based on Statistical Process Control in an Adaptive Testing Environment. Research Report 98-13.

ERIC Educational Resources Information Center

van Krimpen-Stoop, Edith M. L. A.; Meijer, Rob R.

Person-fit research in the context of paper-and-pencil tests is reviewed, and some specific problems regarding person fit in the context of computerized adaptive testing (CAT) are discussed. Some new methods are proposed to investigate person fit in a CAT environment. These statistics are based on Statistical Process Control (SPC) theory. A…

The use and misuse of statistical methodologies in pharmacology research.

PubMed

Marino, Michael J

2014-01-01

Descriptive, exploratory, and inferential statistics are necessary components of hypothesis-driven biomedical research. Despite the ubiquitous need for these tools, the emphasis on statistical methods in pharmacology has become dominated by inferential methods often chosen more by the availability of user-friendly software than by any understanding of the data set or the critical assumptions of the statistical tests. Such frank misuse of statistical methodology and the quest to reach the mystical α<0.05 criteria has hampered research via the publication of incorrect analysis driven by rudimentary statistical training. Perhaps more critically, a poor understanding of statistical tools limits the conclusions that may be drawn from a study by divorcing the investigator from their own data. The net result is a decrease in quality and confidence in research findings, fueling recent controversies over the reproducibility of high profile findings and effects that appear to diminish over time. The recent development of "omics" approaches leading to the production of massive higher dimensional data sets has amplified these issues making it clear that new approaches are needed to appropriately and effectively mine this type of data. Unfortunately, statistical education in the field has not kept pace. This commentary provides a foundation for an intuitive understanding of statistics that fosters an exploratory approach and an appreciation for the assumptions of various statistical tests that hopefully will increase the correct use of statistics, the application of exploratory data analysis, and the use of statistical study design, with the goal of increasing reproducibility and confidence in the literature. Copyright © 2013. Published by Elsevier Inc.

The Profile of Creativity and Proposing Statistical Problem Quality Level Reviewed From Cognitive Style

NASA Astrophysics Data System (ADS)

Awi; Ahmar, A. S.; Rahman, A.; Minggi, I.; Mulbar, U.; Asdar; Ruslan; Upu, H.; Alimuddin; Hamda; Rosidah; Sutamrin; Tiro, M. A.; Rusli

2018-01-01

This research aims to reveal the profile about the level of creativity and the ability to propose statistical problem of students at Mathematics Education 2014 Batch in the State University of Makassar in terms of their cognitive style. This research uses explorative qualitative method by giving meta-cognitive scaffolding at the time of research. The hypothesis of research is that students who have field independent (FI) cognitive style in statistics problem posing from the provided information already able to propose the statistical problem that can be solved and create new data and the problem is already been included as a high quality statistical problem, while students who have dependent cognitive field (FD) commonly are still limited in statistics problem posing that can be finished and do not load new data and the problem is included as medium quality statistical problem.

Statistical methods used to test for agreement of medical instruments measuring continuous variables in method comparison studies: a systematic review.

PubMed

Zaki, Rafdzah; Bulgiba, Awang; Ismail, Roshidi; Ismail, Noor Azina

2012-01-01

Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future.

Statistical Methods Used to Test for Agreement of Medical Instruments Measuring Continuous Variables in Method Comparison Studies: A Systematic Review

PubMed Central

Zaki, Rafdzah; Bulgiba, Awang; Ismail, Roshidi; Ismail, Noor Azina

2012-01-01

Background Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. Methodology/Findings Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. Conclusions This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future. PMID:22662248

The Analysis of Organizational Diagnosis on Based Six Box Model in Universities

ERIC Educational Resources Information Center

Hamid, Rahimi; Siadat, Sayyed Ali; Reza, Hoveida; Arash, Shahin; Ali, Nasrabadi Hasan; Azizollah, Arbabisarjou

2011-01-01

Purpose: The analysis of organizational diagnosis on based six box model at universities. Research method: Research method was descriptive-survey. Statistical population consisted of 1544 faculty members of universities which through random strafed sampling method 218 persons were chosen as the sample. Research Instrument were organizational…

Infusing Active Learning into the Research Methods Unit

ERIC Educational Resources Information Center

Bluestone, Cheryl

2007-01-01

The research methods unit of survey psychology classes introduces important concepts of scientific reasoning and fluency, making it an ideal course in which to deliver enhanced curricula. To increase interest and engagement, the author developed an expanded research methods and statistics module to give students the opportunity to explore…

Research of facial feature extraction based on MMC

NASA Astrophysics Data System (ADS)

Xue, Donglin; Zhao, Jiufen; Tang, Qinhong; Shi, Shaokun

2017-07-01

Based on the maximum margin criterion (MMC), a new algorithm of statistically uncorrelated optimal discriminant vectors and a new algorithm of orthogonal optimal discriminant vectors for feature extraction were proposed. The purpose of the maximum margin criterion is to maximize the inter-class scatter while simultaneously minimizing the intra-class scatter after the projection. Compared with original MMC method and principal component analysis (PCA) method, the proposed methods are better in terms of reducing or eliminating the statistically correlation between features and improving recognition rate. The experiment results on Olivetti Research Laboratory (ORL) face database shows that the new feature extraction method of statistically uncorrelated maximum margin criterion (SUMMC) are better in terms of recognition rate and stability. Besides, the relations between maximum margin criterion and Fisher criterion for feature extraction were revealed.

Replicate This! Creating Individual-Level Data from Summary Statistics Using R

ERIC Educational Resources Information Center

Morse, Brendan J.

2013-01-01

Incorporating realistic data and research examples into quantitative (e.g., statistics and research methods) courses has been widely recommended for enhancing student engagement and comprehension. One way to achieve these ends is to use a data generator to emulate the data in published research articles. "MorseGen" is a free data generator that…

Learning Might Not Equal Liking: Research Methods Course Changes Knowledge But Not Attitudes

ERIC Educational Resources Information Center

Sizemore, O. J.; Lewandowski, Gary W., Jr.

2009-01-01

Students completed surveys at the beginning and end of a sophomore-level course on research and statistics. We hypothesized that the course would produce advances in knowledge of research and statistics and that those changes would be accompanied by more favorable attitudes toward the subject matter. Results showed that knowledge did increase…

The kappa statistic in rehabilitation research: an examination.

PubMed

Tooth, Leigh R; Ottenbacher, Kenneth J

2004-08-01

The number and sophistication of statistical procedures reported in medical rehabilitation research is increasing. Application of the principles and methods associated with evidence-based practice has contributed to the need for rehabilitation practitioners to understand quantitative methods in published articles. Outcomes measurement and determination of reliability are areas that have experienced rapid change during the past decade. In this study, distinctions between reliability and agreement are examined. Information is presented on analytical approaches for addressing reliability and agreement with the focus on the application of the kappa statistic. The following assumptions are discussed: (1) kappa should be used with data measured on a categorical scale, (2) the patients or objects categorized should be independent, and (3) the observers or raters must make their measurement decisions and judgments independently. Several issues related to using kappa in measurement studies are described, including use of weighted kappa, methods of reporting kappa, the effect of bias and prevalence on kappa, and sample size and power requirements for kappa. The kappa statistic is useful for assessing agreement among raters, and it is being used more frequently in rehabilitation research. Correct interpretation of the kappa statistic depends on meeting the required assumptions and accurate reporting.

Evaluation Using Sequential Trials Methods.

ERIC Educational Resources Information Center

Cohen, Mark E.; Ralls, Stephen A.

1986-01-01

Although dental school faculty as well as practitioners are interested in evaluating products and procedures used in clinical practice, research design and statistical analysis can sometimes pose problems. Sequential trials methods provide an analytical structure that is both easy to use and statistically valid. (Author/MLW)

Interpretation of correlations in clinical research.

PubMed

Hung, Man; Bounsanga, Jerry; Voss, Maren Wright

2017-11-01

Critically analyzing research is a key skill in evidence-based practice and requires knowledge of research methods, results interpretation, and applications, all of which rely on a foundation based in statistics. Evidence-based practice makes high demands on trained medical professionals to interpret an ever-expanding array of research evidence. As clinical training emphasizes medical care rather than statistics, it is useful to review the basics of statistical methods and what they mean for interpreting clinical studies. We reviewed the basic concepts of correlational associations, violations of normality, unobserved variable bias, sample size, and alpha inflation. The foundations of causal inference were discussed and sound statistical analyses were examined. We discuss four ways in which correlational analysis is misused, including causal inference overreach, over-reliance on significance, alpha inflation, and sample size bias. Recent published studies in the medical field provide evidence of causal assertion overreach drawn from correlational findings. The findings present a primer on the assumptions and nature of correlational methods of analysis and urge clinicians to exercise appropriate caution as they critically analyze the evidence before them and evaluate evidence that supports practice. Critically analyzing new evidence requires statistical knowledge in addition to clinical knowledge. Studies can overstate relationships, expressing causal assertions when only correlational evidence is available. Failure to account for the effect of sample size in the analyses tends to overstate the importance of predictive variables. It is important not to overemphasize the statistical significance without consideration of effect size and whether differences could be considered clinically meaningful.

Mixed-Methods Research in the Discipline of Nursing.

PubMed

Beck, Cheryl Tatano; Harrison, Lisa

2016-01-01

In this review article, we examined the prevalence and characteristics of 294 mixed-methods studies in the discipline of nursing. Creswell and Plano Clark's typology was most frequently used along with concurrent timing. Bivariate statistics was most often the highest level of statistics reported in the results. As for qualitative data analysis, content analysis was most frequently used. The majority of nurse researchers did not specifically address the purpose, paradigm, typology, priority, timing, interaction, or integration of their mixed-methods studies. Strategies are suggested for improving the design, conduct, and reporting of mixed-methods studies in the discipline of nursing.

Techniques in teaching statistics : linking research production and research use.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martinez-Moyano, I .; Smith, A.; Univ. of Massachusetts at Boston)

In the spirit of closing the 'research-practice gap,' the authors extend evidence-based principles to statistics instruction in social science graduate education. The authors employ a Delphi method to survey experienced statistics instructors to identify teaching techniques to overcome the challenges inherent in teaching statistics to students enrolled in practitioner-oriented master's degree programs. Among the teaching techniques identi?ed as essential are using real-life examples, requiring data collection exercises, and emphasizing interpretation rather than results. Building on existing research, preliminary interviews, and the ?ndings from the study, the authors develop a model describing antecedents to the strength of the link between researchmore » and practice.« less

Quantitative Skills, Critical Thinking, and Writing Mechanics in Blended versus Face-to-Face Versions of a Research Methods and Statistics Course

ERIC Educational Resources Information Center

Goode, Christopher T.; Lamoreaux, Marika; Atchison, Kristin J.; Jeffress, Elizabeth C.; Lynch, Heather L.; Sheehan, Elizabeth

2018-01-01

Hybrid or blended learning (BL) has been shown to be equivalent to or better than face-to-face (FTF) instruction in a broad variety of contexts. We randomly assigned students to either 50/50 BL or 100% FTF versions of a research methods and statistics in psychology course. Students who took the BL version of the course scored significantly lower…

Statistical methods for conducting agreement (comparison of clinical tests) and precision (repeatability or reproducibility) studies in optometry and ophthalmology.

PubMed

McAlinden, Colm; Khadka, Jyoti; Pesudovs, Konrad

2011-07-01

The ever-expanding choice of ocular metrology and imaging equipment has driven research into the validity of their measurements. Consequently, studies of the agreement between two instruments or clinical tests have proliferated in the ophthalmic literature. It is important that researchers apply the appropriate statistical tests in agreement studies. Correlation coefficients are hazardous and should be avoided. The 'limits of agreement' method originally proposed by Altman and Bland in 1983 is the statistical procedure of choice. Its step-by-step use and practical considerations in relation to optometry and ophthalmology are detailed in addition to sample size considerations and statistical approaches to precision (repeatability or reproducibility) estimates. Ophthalmic & Physiological Optics © 2011 The College of Optometrists.

Play It Again: Teaching Statistics with Monte Carlo Simulation

ERIC Educational Resources Information Center

Sigal, Matthew J.; Chalmers, R. Philip

2016-01-01

Monte Carlo simulations (MCSs) provide important information about statistical phenomena that would be impossible to assess otherwise. This article introduces MCS methods and their applications to research and statistical pedagogy using a novel software package for the R Project for Statistical Computing constructed to lessen the often steep…

Errors in statistical decision making Chapter 2 in Applied Statistics in Agricultural, Biological, and Environmental Sciences

USDA-ARS?s Scientific Manuscript database

Agronomic and Environmental research experiments result in data that are analyzed using statistical methods. These data are unavoidably accompanied by uncertainty. Decisions about hypotheses, based on statistical analyses of these data are therefore subject to error. This error is of three types,...

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

PubMed Central

van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B; Neyer, Franz J; van Aken, Marcel AG

2014-01-01

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter, the advantages and pitfalls of the specification of prior knowledge are discussed. To illustrate Bayesian methods explained in this study, in a second example a series of studies that examine the theoretical framework of dynamic interactionism are considered. In the Discussion the advantages and disadvantages of using Bayesian statistics are reviewed, and guidelines on how to report on Bayesian statistics are provided. PMID:24116396

Assessing the suitability of fractional polynomial methods in health services research: a perspective on the categorization epidemic.

PubMed

Williams, Jennifer Stewart

2011-07-01

To show how fractional polynomial methods can usefully replace the practice of arbitrarily categorizing data in epidemiology and health services research. A health service setting is used to illustrate a structured and transparent way of representing non-linear data without arbitrary grouping. When age is a regressor its effects on an outcome will be interpreted differently depending upon the placing of cutpoints or the use of a polynomial transformation. Although it is common practice, categorization comes at a cost. Information is lost, and accuracy and statistical power reduced, leading to spurious statistical interpretation of the data. The fractional polynomial method is widely supported by statistical software programs, and deserves greater attention and use.

Statistical methods used in the public health literature and implications for training of public health professionals

PubMed Central

Hayat, Matthew J.; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L.

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals. PMID:28591190

Statistical methods used in the public health literature and implications for training of public health professionals.

PubMed

Hayat, Matthew J; Powell, Amanda; Johnson, Tessa; Cadwell, Betsy L

2017-01-01

Statistical literacy and knowledge is needed to read and understand the public health literature. The purpose of this study was to quantify basic and advanced statistical methods used in public health research. We randomly sampled 216 published articles from seven top tier general public health journals. Studies were reviewed by two readers and a standardized data collection form completed for each article. Data were analyzed with descriptive statistics and frequency distributions. Results were summarized for statistical methods used in the literature, including descriptive and inferential statistics, modeling, advanced statistical techniques, and statistical software used. Approximately 81.9% of articles reported an observational study design and 93.1% of articles were substantively focused. Descriptive statistics in table or graphical form were reported in more than 95% of the articles, and statistical inference reported in more than 76% of the studies reviewed. These results reveal the types of statistical methods currently used in the public health literature. Although this study did not obtain information on what should be taught, information on statistical methods being used is useful for curriculum development in graduate health sciences education, as well as making informed decisions about continuing education for public health professionals.

Research Methodologies Explored for a Paradigm Shift in University Teaching.

ERIC Educational Resources Information Center

Venter, I. M.; Blignaut, R. J.; Stoltz, D.

2001-01-01

Innovative teaching methods such as collaborative learning, teamwork, and mind maps were introduced to teach computer science and statistics courses at a South African university. Soft systems methodology was adapted and used to manage the research process of evaluating the effectiveness of the teaching methods. This research method provided proof…

Vertical Enhancement of Second-Year Psychology Research

ERIC Educational Resources Information Center

Morys-Carter, Wakefield L.; Paltoglou, Aspasia E.; Davies, Emma L.

2015-01-01

Statistics and Research Methods modules are often unpopular with psychology students; however, at Oxford Brookes University the seminar component of the second-year research methods module tends to get very positive feedback. Over half of the seminars work towards the submission of a research-based experimental lab report. This article introduces…

Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force.

PubMed

Hauber, A Brett; González, Juan Marcos; Groothuis-Oudshoorn, Catharina G M; Prior, Thomas; Marshall, Deborah A; Cunningham, Charles; IJzerman, Maarten J; Bridges, John F P

2016-06-01

Conjoint analysis is a stated-preference survey method that can be used to elicit responses that reveal preferences, priorities, and the relative importance of individual features associated with health care interventions or services. Conjoint analysis methods, particularly discrete choice experiments (DCEs), have been increasingly used to quantify preferences of patients, caregivers, physicians, and other stakeholders. Recent consensus-based guidance on good research practices, including two recent task force reports from the International Society for Pharmacoeconomics and Outcomes Research, has aided in improving the quality of conjoint analyses and DCEs in outcomes research. Nevertheless, uncertainty regarding good research practices for the statistical analysis of data from DCEs persists. There are multiple methods for analyzing DCE data. Understanding the characteristics and appropriate use of different analysis methods is critical to conducting a well-designed DCE study. This report will assist researchers in evaluating and selecting among alternative approaches to conducting statistical analysis of DCE data. We first present a simplistic DCE example and a simple method for using the resulting data. We then present a pedagogical example of a DCE and one of the most common approaches to analyzing data from such a question format-conditional logit. We then describe some common alternative methods for analyzing these data and the strengths and weaknesses of each alternative. We present the ESTIMATE checklist, which includes a list of questions to consider when justifying the choice of analysis method, describing the analysis, and interpreting the results. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Statistical lamb wave localization based on extreme value theory

NASA Astrophysics Data System (ADS)

Harley, Joel B.

2018-04-01

Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

Bayes in biological anthropology.

PubMed

Konigsberg, Lyle W; Frankenberg, Susan R

2013-12-01

In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available. Copyright © 2013 Wiley Periodicals, Inc.

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting.

PubMed

Young, Robin L; Weinberg, Janice; Vieira, Verónica; Ozonoff, Al; Webster, Thomas F

2010-07-19

A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. The GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic.

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting

PubMed Central

2010-01-01

Background A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. Results This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. Conclusions The GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic. PMID:20642827

[Statistical prediction methods in violence risk assessment and its application].

PubMed

Liu, Yuan-Yuan; Hu, Jun-Mei; Yang, Min; Li, Xiao-Song

2013-06-01

It is an urgent global problem how to improve the violence risk assessment. As a necessary part of risk assessment, statistical methods have remarkable impacts and effects. In this study, the predicted methods in violence risk assessment from the point of statistics are reviewed. The application of Logistic regression as the sample of multivariate statistical model, decision tree model as the sample of data mining technique, and neural networks model as the sample of artificial intelligence technology are all reviewed. This study provides data in order to contribute the further research of violence risk assessment.

Three Strategies for the Critical Use of Statistical Methods in Psychological Research

ERIC Educational Resources Information Center

Campitelli, Guillermo; Macbeth, Guillermo; Ospina, Raydonal; Marmolejo-Ramos, Fernando

2017-01-01

We present three strategies to replace the null hypothesis statistical significance testing approach in psychological research: (1) visual representation of cognitive processes and predictions, (2) visual representation of data distributions and choice of the appropriate distribution for analysis, and (3) model comparison. The three strategies…

Guidelines for the Investigation of Mediating Variables in Business Research.

PubMed

MacKinnon, David P; Coxe, Stefany; Baraldi, Amanda N

2012-03-01

Business theories often specify the mediating mechanisms by which a predictor variable affects an outcome variable. In the last 30 years, investigations of mediating processes have become more widespread with corresponding developments in statistical methods to conduct these tests. The purpose of this article is to provide guidelines for mediation studies by focusing on decisions made prior to the research study that affect the clarity of conclusions from a mediation study, the statistical models for mediation analysis, and methods to improve interpretation of mediation results after the research study. Throughout this article, the importance of a program of experimental and observational research for investigating mediating mechanisms is emphasized.

[Adequate application of quantitative and qualitative statistic analytic methods in acupuncture clinical trials].

PubMed

Tan, Ming T; Liu, Jian-ping; Lao, Lixing

2012-08-01

Recently, proper use of the statistical methods in traditional Chinese medicine (TCM) randomized controlled trials (RCTs) has received increased attention. Statistical inference based on hypothesis testing is the foundation of clinical trials and evidence-based medicine. In this article, the authors described the methodological differences between literature published in Chinese and Western journals in the design and analysis of acupuncture RCTs and the application of basic statistical principles. In China, qualitative analysis method has been widely used in acupuncture and TCM clinical trials, while the between-group quantitative analysis methods on clinical symptom scores are commonly used in the West. The evidence for and against these analytical differences were discussed based on the data of RCTs assessing acupuncture for pain relief. The authors concluded that although both methods have their unique advantages, quantitative analysis should be used as the primary analysis while qualitative analysis can be a secondary criterion for analysis. The purpose of this paper is to inspire further discussion of such special issues in clinical research design and thus contribute to the increased scientific rigor of TCM research.

Challenge of Fetal Mortality

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Assessing Statistical Competencies in Clinical and Translational Science Education: One Size Does Not Fit All

PubMed Central

Lindsell, Christopher J.; Welty, Leah J.; Mazumdar, Madhu; Thurston, Sally W.; Rahbar, Mohammad H.; Carter, Rickey E.; Pollock, Bradley H.; Cucchiara, Andrew J.; Kopras, Elizabeth J.; Jovanovic, Borko D.; Enders, Felicity T.

2014-01-01

Abstract Introduction Statistics is an essential training component for a career in clinical and translational science (CTS). Given the increasing complexity of statistics, learners may have difficulty selecting appropriate courses. Our question was: what depth of statistical knowledge do different CTS learners require? Methods For three types of CTS learners (principal investigator, co‐investigator, informed reader of the literature), each with different backgrounds in research (no previous research experience, reader of the research literature, previous research experience), 18 experts in biostatistics, epidemiology, and research design proposed levels for 21 statistical competencies. Results Statistical competencies were categorized as fundamental, intermediate, or specialized. CTS learners who intend to become independent principal investigators require more specialized training, while those intending to become informed consumers of the medical literature require more fundamental education. For most competencies, less training was proposed for those with more research background. Discussion When selecting statistical coursework, the learner's research background and career goal should guide the decision. Some statistical competencies are considered to be more important than others. Baseline knowledge assessments may help learners identify appropriate coursework. Conclusion Rather than one size fits all, tailoring education to baseline knowledge, learner background, and future goals increases learning potential while minimizing classroom time. PMID:25212569

Cognition, comprehension and application of biostatistics in research by Indian postgraduate students in periodontics

PubMed Central

Swetha, Jonnalagadda Laxmi; Arpita, Ramisetti; Srikanth, Chintalapani; Nutalapati, Rajasekhar

2014-01-01

Background: Biostatistics is an integral part of research protocols. In any field of inquiry or investigation, data obtained is subsequently classified, analyzed and tested for accuracy by statistical methods. Statistical analysis of collected data, thus, forms the basis for all evidence-based conclusions. Aim: The aim of this study is to evaluate the cognition, comprehension and application of biostatistics in research among post graduate students in Periodontics, in India. Materials and Methods: A total of 391 post graduate students registered for a master's course in periodontics at various dental colleges across India were included in the survey. Data regarding the level of knowledge, understanding and its application in design and conduct of the research protocol was collected using a dichotomous questionnaire. A descriptive statistics was used for data analysis. Results: Nearly 79.2% students were aware of the importance of biostatistics in research, 55-65% were familiar with MS-EXCEL spreadsheet for graphical representation of data and with the statistical softwares available on the internet, 26.0% had biostatistics as mandatory subject in their curriculum, 9.5% tried to perform statistical analysis on their own while 3.0% were successful in performing statistical analysis of their studies on their own. Conclusion: Biostatistics should play a central role in planning, conduct, interim analysis, final analysis and reporting of periodontal research especially by the postgraduate students. Indian postgraduate students in periodontics are aware of the importance of biostatistics in research but the level of understanding and application is still basic and needs to be addressed. PMID:24744547

Overview of the SAMSI year-long program on Statistical, Mathematical and Computational Methods for Astronomy

NASA Astrophysics Data System (ADS)

Jogesh Babu, G.

2017-01-01

A year-long research (Aug 2016- May 2017) program on `Statistical, Mathematical and Computational Methods for Astronomy (ASTRO)’ is well under way at Statistical and Applied Mathematical Sciences Institute (SAMSI), a National Science Foundation research institute in Research Triangle Park, NC. This program has brought together astronomers, computer scientists, applied mathematicians and statisticians. The main aims of this program are: to foster cross-disciplinary activities; to accelerate the adoption of modern statistical and mathematical tools into modern astronomy; and to develop new tools needed for important astronomical research problems. The program provides multiple avenues for cross-disciplinary interactions, including several workshops, long-term visitors, and regular teleconferences, so participants can continue collaborations, even if they can only spend limited time in residence at SAMSI. The main program is organized around five working groups:i) Uncertainty Quantification and Astrophysical Emulationii) Synoptic Time Domain Surveysiii) Multivariate and Irregularly Sampled Time Seriesiv) Astrophysical Populationsv) Statistics, computation, and modeling in cosmology.A brief description of each of the work under way by these groups will be given. Overlaps among various working groups will also be highlighted. How the wider astronomy community can both participate and benefit from the activities, will be briefly mentioned.

Incorporating an Interactive Statistics Workshop into an Introductory Biology Course-Based Undergraduate Research Experience (CURE) Enhances Students’ Statistical Reasoning and Quantitative Literacy Skills †

PubMed Central

Olimpo, Jeffrey T.; Pevey, Ryan S.; McCabe, Thomas M.

2018-01-01

Course-based undergraduate research experiences (CUREs) provide an avenue for student participation in authentic scientific opportunities. Within the context of such coursework, students are often expected to collect, analyze, and evaluate data obtained from their own investigations. Yet, limited research has been conducted that examines mechanisms for supporting students in these endeavors. In this article, we discuss the development and evaluation of an interactive statistics workshop that was expressly designed to provide students with an open platform for graduate teaching assistant (GTA)-mentored data processing, statistical testing, and synthesis of their own research findings. Mixed methods analyses of pre/post-intervention survey data indicated a statistically significant increase in students’ reasoning and quantitative literacy abilities in the domain, as well as enhancement of student self-reported confidence in and knowledge of the application of various statistical metrics to real-world contexts. Collectively, these data reify an important role for scaffolded instruction in statistics in preparing emergent scientists to be data-savvy researchers in a globally expansive STEM workforce. PMID:29904549

Incorporating an Interactive Statistics Workshop into an Introductory Biology Course-Based Undergraduate Research Experience (CURE) Enhances Students' Statistical Reasoning and Quantitative Literacy Skills.

PubMed

Olimpo, Jeffrey T; Pevey, Ryan S; McCabe, Thomas M

2018-01-01

Course-based undergraduate research experiences (CUREs) provide an avenue for student participation in authentic scientific opportunities. Within the context of such coursework, students are often expected to collect, analyze, and evaluate data obtained from their own investigations. Yet, limited research has been conducted that examines mechanisms for supporting students in these endeavors. In this article, we discuss the development and evaluation of an interactive statistics workshop that was expressly designed to provide students with an open platform for graduate teaching assistant (GTA)-mentored data processing, statistical testing, and synthesis of their own research findings. Mixed methods analyses of pre/post-intervention survey data indicated a statistically significant increase in students' reasoning and quantitative literacy abilities in the domain, as well as enhancement of student self-reported confidence in and knowledge of the application of various statistical metrics to real-world contexts. Collectively, these data reify an important role for scaffolded instruction in statistics in preparing emergent scientists to be data-savvy researchers in a globally expansive STEM workforce.

A Unifying Framework for Teaching Nonparametric Statistical Tests

ERIC Educational Resources Information Center

Bargagliotti, Anna E.; Orrison, Michael E.

2014-01-01

Increased importance is being placed on statistics at both the K-12 and undergraduate level. Research divulging effective methods to teach specific statistical concepts is still widely sought after. In this paper, we focus on best practices for teaching topics in nonparametric statistics at the undergraduate level. To motivate the work, we…

Reducing Power Differentials in the Classroom Using Student-Based Quantitative Research Scenarios: Applications in Undergraduate and Graduate Research Methods Classrooms

ERIC Educational Resources Information Center

Morrow, Jennifer Ann; Kelly, Stephanie; Skolits, Gary

2013-01-01

Understanding and conducting research is a complex, integral skill that needs to be mastered by both undergraduate and graduate students. Yet many students are reluctant and often somewhat apprehensive about undertaking research and understanding the underlying statistical methods used to evaluate research (Dauphinee, Schau, & Stevens, 1997).…

The Use of Invariance and Bootstrap Procedures as a Method to Establish the Reliability of Research Results.

ERIC Educational Resources Information Center

Sandler, Andrew B.

Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…

Developing Investigative Entry Points: Exploring the Use of Quantitative Methods in English Education Research

ERIC Educational Resources Information Center

McGraner, Kristin L.; Robbins, Daniel

2010-01-01

Although many research questions in English education demand the use of qualitative methods, this paper will briefly explore how English education researchers and doctoral students may use statistics and quantitative methods to inform, complement, and/or deepen their inquiries. First, the authors will provide a general overview of the survey areas…

Teaching Bayesian Statistics in a Health Research Methodology Program

ERIC Educational Resources Information Center

Pullenayegum, Eleanor M.; Thabane, Lehana

2009-01-01

Despite the appeal of Bayesian methods in health research, they are not widely used. This is partly due to a lack of courses in Bayesian methods at an appropriate level for non-statisticians in health research. Teaching such a course can be challenging because most statisticians have been taught Bayesian methods using a mathematical approach, and…

Connecting Communities to Health Research: Development of the Project CONNECT Minority Research Registry

PubMed Central

Green, Melissa A.; Kim, Mimi M.; Barber, Sharrelle; Odulana, Abedowale A.; Godley, Paul A.; Howard, Daniel L.; Corbie-Smith, Giselle M.

2013-01-01

Introduction Prevention and treatment standards are based on evidence obtained in behavioral and clinical research. However, racial and ethnic minorities remain relatively absent from the science that develops these standards. While investigators have successfully recruited participants for individual studies using tailored recruitment methods, these strategies require considerable time and resources. Research registries, typically developed around a disease or condition, serve as a promising model for a targeted recruitment method to increase minority participation in health research. This study assessed the tailored recruitment methods used to populate a health research registry targeting African-American community members. Methods We describe six recruitment methods applied between September 2004 and October 2008 to recruit members into a health research registry. Recruitment included direct (existing studies, public databases, community outreach) and indirect methods (radio, internet, and email) targeting the general population, local universities, and African American communities. We conducted retrospective analysis of the recruitment by method using descriptive statistics, frequencies, and chi-square statistics. Results During the recruitment period, 608 individuals enrolled in the research registry. The majority of enrollees were African American, female, and in good health. Direct and indirect methods were identified as successful strategies for subgroups. Findings suggest significant associations between recruitment methods and age, presence of existing health condition, prior research participation, and motivation to join the registry. Conclusions A health research registry can be a successful tool to increase minority awareness of research opportunities. Multi-pronged recruitment approaches are needed to reach diverse subpopulations. PMID:23340183

Applied Behavior Analysis and Statistical Process Control?

ERIC Educational Resources Information Center

Hopkins, B. L.

1995-01-01

Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

Using Artificial Neural Networks in Educational Research: Some Comparisons with Linear Statistical Models.

ERIC Educational Resources Information Center

Everson, Howard T.; And Others

This paper explores the feasibility of neural computing methods such as artificial neural networks (ANNs) and abductory induction mechanisms (AIM) for use in educational measurement. ANNs and AIMS methods are contrasted with more traditional statistical techniques, such as multiple regression and discriminant function analyses, for making…

Robustness of S1 statistic with Hodges-Lehmann for skewed distributions

NASA Astrophysics Data System (ADS)

Ahad, Nor Aishah; Yahaya, Sharipah Soaad Syed; Yin, Lee Ping

2016-10-01

Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for more than two groups when the populations are normally distributed. ANOVA is highly inefficient under the influence of non- normal and heteroscedastic settings. When the assumptions are violated, researchers are looking for alternative such as Kruskal-Wallis under nonparametric or robust method. This study focused on flexible method, S1 statistic for comparing groups using median as the location estimator. S1 statistic was modified by substituting the median with Hodges-Lehmann and the default scale estimator with the variance of Hodges-Lehmann and MADn to produce two different test statistics for comparing groups. Bootstrap method was used for testing the hypotheses since the sampling distributions of these modified S1 statistics are unknown. The performance of the proposed statistic in terms of Type I error was measured and compared against the original S1 statistic, ANOVA and Kruskal-Wallis. The propose procedures show improvement compared to the original statistic especially under extremely skewed distribution.

Statistical Inference on Memory Structure of Processes and Its Applications to Information Theory

DTIC Science & Technology

2016-05-12

valued times series from a sample. (A practical algorithm to compute the estimator is a work in progress.) Third, finitely-valued spatial processes...ES) U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 mathematical statistics; time series ; Markov chains; random...proved. Second, a statistical method is developed to estimate the memory depth of discrete- time and continuously-valued times series from a sample. (A

Evaluating Current Status of MS Educational Technology Curriculum in Iran from Viewpoint of Experts and Professors in Order to Offering a Desirable Curriculum

ERIC Educational Resources Information Center

Rahmanpour, Mohammad; Liaghatdar, Mohammad-Javad; Sharifian, Fereydoon; Rezaee, Mehran

2016-01-01

The aim of this research is evaluating status of MS field of educational technology in Iran. This research is qualitative and it is conducted based on survey method. The statistical community of this research is expert professors in educational technology area. Accordingly, 15 persons were chosen among this statistical community as statistical…

Death in the United States, 2011

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Nigerian pharmacists’ self-perceived competence and confidence to plan and conduct pharmacy practice research

PubMed Central

Usman, Mohammad N.; Umar, Muhammad D.

2018-01-01

Background: Recent studies have revealed that pharmacists have interest in conducting research. However, lack of confidence is a major barrier. Objective: This study evaluated pharmacists’ self-perceived competence and confidence to plan and conduct health-related research. Method: This cross sectional study was conducted during the 89th Annual National Conference of the Pharmaceutical Society of Nigeria in November 2016. An adapted questionnaire was validated and administered to 200 pharmacist delegates during the conference. Result: Overall, 127 questionnaires were included in the analysis. At least 80% of the pharmacists had previous health-related research experience. Pharmacist’s competence and confidence scores were lowest for research skills such as: using software for statistical analysis, choosing and applying appropriate inferential statistical test and method, and outlining detailed statistical plan to be used in data analysis. Highest competence and confidence scores were observed for conception of research idea, literature search and critical appraisal of literature. Pharmacists with previous research experience had higher competence and confidence scores than those with no previous research experience (p<0.05). The only predictor of moderate-to-extreme self-competence and confidence was having at least one journal article publication during the last 5 years. Conclusion: Nigerian pharmacists indicated interest to participate in health-related research. However, self-competence and confidence to plan and conduct research were low. This was particularly so for skills related to statistical analysis. Training programs and building of Pharmacy Practice Research Network are recommended to enhance pharmacist’s research capacity. PMID:29619141

Content and Method in the Teaching of Marketing Research Revisited

ERIC Educational Resources Information Center

Wilson, Holt; Neeley, Concha; Niedzwiecki, Kelly

2009-01-01

This paper presents the findings from a survey of marketing research faculty. The study finds SPSS is the most used statistical software, that cross tabulation, single, independent, and dependent t-tests, and ANOVA are among the most important statistical tools according to respondents. Bivariate and multiple regression are also considered…

Assessing Statistical Change Indices in Selected Social Work Intervention Research Studies

ERIC Educational Resources Information Center

Ham, Amanda D.; Huggins-Hoyt, Kimberly Y.; Pettus, Joelle

2016-01-01

Objectives: This study examined how evaluation and intervention research (IR) studies assessed statistical change to ascertain effectiveness. Methods: Studies from six core social work journals (2009-2013) were reviewed (N = 1,380). Fifty-two evaluation (n= 27) and intervention (n = 25) studies met the inclusion criteria. These studies were…

University and student segmentation: multilevel latent-class analysis of students' attitudes towards research methods and statistics.

PubMed

Mutz, Rüdiger; Daniel, Hans-Dieter

2013-06-01

It is often claimed that psychology students' attitudes towards research methods and statistics affect course enrollment, persistence, achievement, and course climate. However, the inter-institutional variability has been widely neglected in the research on students' attitudes towards research methods and statistics, but it is important for didactic purposes (heterogeneity of the student population). The paper presents a scale based on findings of the social psychology of attitudes (polar and emotion-based concept) in conjunction with a method for capturing beginning university students' attitudes towards research methods and statistics and identifying the proportion of students having positive attitudes at the institutional level. The study based on a re-analysis of a nationwide survey in Germany in August 2000 of all psychology students that enrolled in fall 1999/2000 (N= 1,490) and N= 44 universities. Using multilevel latent-class analysis (MLLCA), the aim was to group students in different student attitude types and at the same time to obtain university segments based on the incidences of the different student attitude types. Four student latent clusters were found that can be ranked on a bipolar attitude dimension. Membership in a cluster was predicted by age, grade point average (GPA) on school-leaving exam, and personality traits. In addition, two university segments were found: universities with an average proportion of students with positive attitudes and universities with a high proportion of students with positive attitudes (excellent segment). As psychology students make up a very heterogeneous group, the use of multiple learning activities as opposed to the classical lecture course is required. © 2011 The British Psychological Society.

Connecting communities to health research: development of the Project CONNECT minority research registry.

PubMed

Green, Melissa A; Kim, Mimi M; Barber, Sharrelle; Odulana, Abedowale A; Godley, Paul A; Howard, Daniel L; Corbie-Smith, Giselle M

2013-05-01

Prevention and treatment standards are based on evidence obtained in behavioral and clinical research. However, racial and ethnic minorities remain relatively absent from the science that develops these standards. While investigators have successfully recruited participants for individual studies using tailored recruitment methods, these strategies require considerable time and resources. Research registries, typically developed around a disease or condition, serve as a promising model for a targeted recruitment method to increase minority participation in health research. This study assessed the tailored recruitment methods used to populate a health research registry targeting African-American community members. We describe six recruitment methods applied between September 2004 and October 2008 to recruit members into a health research registry. Recruitment included direct (existing studies, public databases, community outreach) and indirect methods (radio, internet, and email) targeting the general population, local universities, and African American communities. We conducted retrospective analysis of the recruitment by method using descriptive statistics, frequencies, and chi-square statistics. During the recruitment period, 608 individuals enrolled in the research registry. The majority of enrollees were African American, female, and in good health. Direct and indirect methods were identified as successful strategies for subgroups. Findings suggest significant associations between recruitment methods and age, presence of existing health condition, prior research participation, and motivation to join the registry. A health research registry can be a successful tool to increase minority awareness of research opportunities. Multi-pronged recruitment approaches are needed to reach diverse subpopulations. Copyright © 2013. Published by Elsevier Inc.

STRengthening analytical thinking for observational studies: the STRATOS initiative.

PubMed

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-12-30

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

Content and Citation Analyses of "Public Relations Review."

ERIC Educational Resources Information Center

Morton, Linda P.; Lin, Li-Yun

1995-01-01

Analyzes 161 cited and 177 uncited articles published in "Public Relations Review" (1975-93) to determine if 3 independent variables--research methods, type of statistics, and topics--influenced whether or not articles were cited in other research articles. Finds significant differences between quantitative and qualitative research methods but not…

Schools and Staffing Survey (SASS): 1995. Selected Papers Presented at the Meeting of the American Statistical Association (Orlando, Florida, August 13-17, 1996). Working Paper Series.

ERIC Educational Resources Information Center

National Center for Education Statistics (ED), Washington, DC.

The papers were presented at the Social Statistics Section, the Government Statistics Section, and the Section on Survey Research Methods. The following papers are included in the Social Statistics Section and Government Statistics Section, "Overcoming the Bureaucratic Paradigm: Memorial Session in Honor of Roger Herriot": "1995…

Guidelines for the Investigation of Mediating Variables in Business Research

PubMed Central

Coxe, Stefany; Baraldi, Amanda N.

2013-01-01

Business theories often specify the mediating mechanisms by which a predictor variable affects an outcome variable. In the last 30 years, investigations of mediating processes have become more widespread with corresponding developments in statistical methods to conduct these tests. The purpose of this article is to provide guidelines for mediation studies by focusing on decisions made prior to the research study that affect the clarity of conclusions from a mediation study, the statistical models for mediation analysis, and methods to improve interpretation of mediation results after the research study. Throughout this article, the importance of a program of experimental and observational research for investigating mediating mechanisms is emphasized. PMID:25237213

Overcoming Student Disengagement and Anxiety in Theory, Methods, and Statistics Courses by Building a Community of Learners

ERIC Educational Resources Information Center

Macheski, Ginger E.; Buhrmann, Jan; Lowney, Kathleen S.; Bush, Melanie E. L.

2008-01-01

Participants in the 2007 American Sociological Association teaching workshop, "Innovative Teaching Practices for Difficult Subjects," shared concerns about teaching statistics, research methods, and theory. Strategies for addressing these concerns center on building a community of learners by creating three processes throughout the course: 1) an…

Effectiveness of Project Based Learning in Statistics for Lower Secondary Schools

ERIC Educational Resources Information Center

Siswono, Tatag Yuli Eko; Hartono, Sugi; Kohar, Ahmad Wachidul

2018-01-01

Purpose: This study aimed at investigating the effectiveness of implementing Project Based Learning (PBL) on the topic of statistics at a lower secondary school in Surabaya city, Indonesia, indicated by examining student learning outcomes, student responses, and student activity. Research Methods: A quasi experimental method was conducted over two…

Detection of Test Collusion via Kullback-Leibler Divergence

ERIC Educational Resources Information Center

Belov, Dmitry I.

2013-01-01

The development of statistical methods for detecting test collusion is a new research direction in the area of test security. Test collusion may be described as large-scale sharing of test materials, including answers to test items. Current methods of detecting test collusion are based on statistics also used in answer-copying detection.…

Does bad inference drive out good?

PubMed

Marozzi, Marco

2015-07-01

The (mis)use of statistics in practice is widely debated, and a field where the debate is particularly active is medicine. Many scholars emphasize that a large proportion of published medical research contains statistical errors. It has been noted that top class journals like Nature Medicine and The New England Journal of Medicine publish a considerable proportion of papers that contain statistical errors and poorly document the application of statistical methods. This paper joins the debate on the (mis)use of statistics in the medical literature. Even though the validation process of a statistical result may be quite elusive, a careful assessment of underlying assumptions is central in medicine as well as in other fields where a statistical method is applied. Unfortunately, a careful assessment of underlying assumptions is missing in many papers, including those published in top class journals. In this paper, it is shown that nonparametric methods are good alternatives to parametric methods when the assumptions for the latter ones are not satisfied. A key point to solve the problem of the misuse of statistics in the medical literature is that all journals have their own statisticians to review the statistical method/analysis section in each submitted paper. © 2015 Wiley Publishing Asia Pty Ltd.

Analysis of data collected from right and left limbs: Accounting for dependence and improving statistical efficiency in musculoskeletal research.

PubMed

Stewart, Sarah; Pearson, Janet; Rome, Keith; Dalbeth, Nicola; Vandal, Alain C

2018-01-01

Statistical techniques currently used in musculoskeletal research often inefficiently account for paired-limb measurements or the relationship between measurements taken from multiple regions within limbs. This study compared three commonly used analysis methods with a mixed-models approach that appropriately accounted for the association between limbs, regions, and trials and that utilised all information available from repeated trials. Four analysis were applied to an existing data set containing plantar pressure data, which was collected for seven masked regions on right and left feet, over three trials, across three participant groups. Methods 1-3 averaged data over trials and analysed right foot data (Method 1), data from a randomly selected foot (Method 2), and averaged right and left foot data (Method 3). Method 4 used all available data in a mixed-effects regression that accounted for repeated measures taken for each foot, foot region and trial. Confidence interval widths for the mean differences between groups for each foot region were used as a criterion for comparison of statistical efficiency. Mean differences in pressure between groups were similar across methods for each foot region, while the confidence interval widths were consistently smaller for Method 4. Method 4 also revealed significant between-group differences that were not detected by Methods 1-3. A mixed effects linear model approach generates improved efficiency and power by producing more precise estimates compared to alternative approaches that discard information in the process of accounting for paired-limb measurements. This approach is recommended in generating more clinically sound and statistically efficient research outputs. Copyright © 2017 Elsevier B.V. All rights reserved.

Childbearing Differences among Three Generations of U.S. Women

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Descriptive and inferential statistical methods used in burns research.

PubMed

Al-Benna, Sammy; Al-Ajam, Yazan; Way, Benjamin; Steinstraesser, Lars

2010-05-01

Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals in the fields of biostatistics and epidemiology when using more advanced statistical techniques. Copyright 2009 Elsevier Ltd and ISBI. All rights reserved.

The Structure of Research Methodology Competency in Higher Education and the Role of Teaching Teams and Course Temporal Distance

ERIC Educational Resources Information Center

Schweizer, Karl; Steinwascher, Merle; Moosbrugger, Helfried; Reiss, Siegbert

2011-01-01

The development of research methodology competency is a major aim of the psychology curriculum at universities. Usually, three courses concentrating on basic statistics, advanced statistics and experimental methods, respectively, serve the achievement of this aim. However, this traditional curriculum-based course structure gives rise to the…

Quantitative Methods in Library and Information Science Literature: Descriptive vs. Inferential Statistics.

ERIC Educational Resources Information Center

Brattin, Barbara C.

Content analysis was performed on the top six core journals for 1990 in library and information science to determine the extent of research in the field. Articles (n=186) were examined for descriptive or inferential statistics and separately for the presence of mathematical models. Results show a marked (14%) increase in research for 1990,…

75 Years of Mortality in the United States, 1935-2010

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Caloric Intake from Fast Food among Adults: United States, 2007-2010

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

STATISTICAL SAMPLING AND DATA ANALYSIS

EPA Science Inventory

Research is being conducted to develop approaches to improve soil and sediment sampling techniques, measurement design and geostatistics, and data analysis via chemometric, environmetric, and robust statistical methods. Improvements in sampling contaminated soil and other hetero...

STRengthening Analytical Thinking for Observational Studies: the STRATOS initiative

PubMed Central

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-01-01

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even ‘standard’ analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. PMID:25074480

Resampling: A Marriage of Computers and Statistics. ERIC/TM Digest.

ERIC Educational Resources Information Center

Rudner, Lawrence M.; Shafer, Mary Morello

Advances in computer technology are making it possible for educational researchers to use simpler statistical methods to address a wide range of questions with smaller data sets and fewer, and less restrictive, assumptions. This digest introduces computationally intensive statistics, collectively called resampling techniques. Resampling is a…

Statistics in three biomedical journals.

PubMed

Pilcík, T

2003-01-01

In this paper we analyze the use of statistics and associated problems, in three Czech biological journals in the year 2000. We investigated 23 articles Folia Biologica, 60 articles in Folia Microbiologica, and 88 articles in Physiological Research. The highest frequency of publications with statistical content have used descriptive statistics and t-test. The most usual mistake concerns the absence of reference about the used statistical software and insufficient description of the data. We have compared our results with the results of similar studies in some other medical journals. The use of important statistical methods is comparable with those used in most medical journals, the proportion of articles, in which the applied method is described insufficiently is moderately low.

Statistical issues on the analysis of change in follow-up studies in dental research.

PubMed

Blance, Andrew; Tu, Yu-Kang; Baelum, Vibeke; Gilthorpe, Mark S

2007-12-01

To provide an overview to the problems in study design and associated analyses of follow-up studies in dental research, particularly addressing three issues: treatment-baselineinteractions; statistical power; and nonrandomization. Our previous work has shown that many studies purport an interacion between change (from baseline) and baseline values, which is often based on inappropriate statistical analyses. A priori power calculations are essential for randomized controlled trials (RCTs), but in the pre-test/post-test RCT design it is not well known to dental researchers that the choice of statistical method affects power, and that power is affected by treatment-baseline interactions. A common (good) practice in the analysis of RCT data is to adjust for baseline outcome values using ancova, thereby increasing statistical power. However, an important requirement for ancova is there to be no interaction between the groups and baseline outcome (i.e. effective randomization); the patient-selection process should not cause differences in mean baseline values across groups. This assumption is often violated for nonrandomized (observational) studies and the use of ancova is thus problematic, potentially giving biased estimates, invoking Lord's paradox and leading to difficulties in the interpretation of results. Baseline interaction issues can be overcome by use of statistical methods; not widely practiced in dental research: Oldham's method and multilevel modelling; the latter is preferred for its greater flexibility to deal with more than one follow-up occasion as well as additional covariates To illustrate these three key issues, hypothetical examples are considered from the fields of periodontology, orthodontics, and oral implantology. Caution needs to be exercised when considering the design and analysis of follow-up studies. ancova is generally inappropriate for nonrandomized studies and causal inferences from observational data should be avoided.

Network Data: Statistical Theory and New Models

DTIC Science & Technology

2016-02-17

SECURITY CLASSIFICATION OF: During this period of review, Bin Yu worked on many thrusts of high-dimensional statistical theory and methodologies. Her...research covered a wide range of topics in statistics including analysis and methods for spectral clustering for sparse and structured networks...2,7,8,21], sparse modeling (e.g. Lasso) [4,10,11,17,18,19], statistical guarantees for the EM algorithm [3], statistical analysis of algorithm leveraging

A critique of the usefulness of inferential statistics in applied behavior analysis

PubMed Central

Hopkins, B. L.; Cole, Brian L.; Mason, Tina L.

1998-01-01

Researchers continue to recommend that applied behavior analysts use inferential statistics in making decisions about effects of independent variables on dependent variables. In many other approaches to behavioral science, inferential statistics are the primary means for deciding the importance of effects. Several possible uses of inferential statistics are considered. Rather than being an objective means for making decisions about effects, as is often claimed, inferential statistics are shown to be subjective. It is argued that the use of inferential statistics adds nothing to the complex and admittedly subjective nonstatistical methods that are often employed in applied behavior analysis. Attacks on inferential statistics that are being made, perhaps with increasing frequency, by those who are not behavior analysts, are discussed. These attackers are calling for banning the use of inferential statistics in research publications and commonly recommend that behavioral scientists should switch to using statistics aimed at interval estimation or the method of confidence intervals. Interval estimation is shown to be contrary to the fundamental assumption of behavior analysis that only individuals behave. It is recommended that authors who wish to publish the results of inferential statistics be asked to justify them as a means for helping us to identify any ways in which they may be useful. PMID:22478304

Assessment of Problem-Based Learning in the Undergraduate Statistics Course

ERIC Educational Resources Information Center

Karpiak, Christie P.

2011-01-01

Undergraduate psychology majors (N = 51) at a mid-sized private university took a statistics examination on the first day of the research methods course, a course for which a grade of "C" or higher in statistics is a prerequisite. Students who had taken a problem-based learning (PBL) section of the statistics course (n = 15) were compared to those…

Cancer survival: an overview of measures, uses, and interpretation.

PubMed

Mariotto, Angela B; Noone, Anne-Michelle; Howlader, Nadia; Cho, Hyunsoon; Keel, Gretchen E; Garshell, Jessica; Woloshin, Steven; Schwartz, Lisa M

2014-11-01

Survival statistics are of great interest to patients, clinicians, researchers, and policy makers. Although seemingly simple, survival can be confusing: there are many different survival measures with a plethora of names and statistical methods developed to answer different questions. This paper aims to describe and disseminate different survival measures and their interpretation in less technical language. In addition, we introduce templates to summarize cancer survival statistic organized by their specific purpose: research and policy versus prognosis and clinical decision making. Published by Oxford University Press 2014.

Cancer Survival: An Overview of Measures, Uses, and Interpretation

PubMed Central

Noone, Anne-Michelle; Howlader, Nadia; Cho, Hyunsoon; Keel, Gretchen E.; Garshell, Jessica; Woloshin, Steven; Schwartz, Lisa M.

2014-01-01

Survival statistics are of great interest to patients, clinicians, researchers, and policy makers. Although seemingly simple, survival can be confusing: there are many different survival measures with a plethora of names and statistical methods developed to answer different questions. This paper aims to describe and disseminate different survival measures and their interpretation in less technical language. In addition, we introduce templates to summarize cancer survival statistic organized by their specific purpose: research and policy versus prognosis and clinical decision making. PMID:25417231

Trends in Out-of-Hospital Births in the United States, 1990-2012

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

State Variability in Supply of Office-based Primary Care Providers: United States, 2012

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Emergency Department Visits by Persons Aged 65 and Over: United States, 2009-2010

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

The Seismic risk perception in Italy deduced by a statistical sample

NASA Astrophysics Data System (ADS)

Crescimbene, Massimo; La Longa, Federica; Camassi, Romano; Pino, Nicola Alessandro; Pessina, Vera; Peruzza, Laura; Cerbara, Loredana; Crescimbene, Cristiana

2015-04-01

In 2014 EGU Assembly we presented the results of a web a survey on the perception of seismic risk in Italy. The data were derived from over 8,500 questionnaires coming from all Italian regions. Our questionnaire was built by using the semantic differential method (Osgood et al. 1957) with a seven points Likert scale. The questionnaire is inspired the main theoretical approaches of risk perception (psychometric paradigm, cultural theory, etc.) .The results were promising and seem to clearly indicate an underestimation of seismic risk by the italian population. Based on these promising results, the DPC has funded our research for the second year. In 2015 EGU Assembly we present the results of a new survey deduced by an italian statistical sample. The importance of statistical significance at national scale was also suggested by ISTAT (Italian Statistic Institute), considering the study as of national interest, accepted the "project on the perception of seismic risk" as a pilot study inside the National Statistical System (SISTAN), encouraging our RU to proceed in this direction. The survey was conducted by a company specialised in population surveys using the CATI method (computer assisted telephone interview). Preliminary results will be discussed. The statistical support was provided by the research partner CNR-IRPPS. This research is funded by Italian Civil Protection Department (DPC).

Modelling the Effects of Land-Use Changes on Climate: a Case Study on Yamula DAM

NASA Astrophysics Data System (ADS)

Köylü, Ü.; Geymen, A.

2016-10-01

Dams block flow of rivers and cause artificial water reservoirs which affect the climate and the land use characteristics of the river basin. In this research, the effect of the huge water body obtained by Yamula Dam in Kızılırmak Basin is analysed over surrounding spatial's land use and climate change. Mann Kendal non-parametrical statistical test, Theil&Sen Slope method, Inverse Distance Weighting (IDW), Soil Conservation Service-Curve Number (SCS-CN) methods are integrated for spatial and temporal analysis of the research area. For this research humidity, temperature, wind speed, precipitation observations which are collected in 16 weather stations nearby Kızılırmak Basin are analyzed. After that these statistical information is combined by GIS data over years. An application is developed for GIS analysis in Python Programming Language and integrated with ArcGIS software. Statistical analysis calculated in the R Project for Statistical Computing and integrated with developed application. According to the statistical analysis of extracted time series of meteorological parameters, statistical significant spatiotemporal trends are observed for climate change and land use characteristics. In this study, we indicated the effect of big dams in local climate on semi-arid Yamula Dam.

Study/experimental/research design: much more than statistics.

PubMed

Knight, Kenneth L

2010-01-01

The purpose of study, experimental, or research design in scientific manuscripts has changed significantly over the years. It has evolved from an explanation of the design of the experiment (ie, data gathering or acquisition) to an explanation of the statistical analysis. This practice makes "Methods" sections hard to read and understand. To clarify the difference between study design and statistical analysis, to show the advantages of a properly written study design on article comprehension, and to encourage authors to correctly describe study designs. The role of study design is explored from the introduction of the concept by Fisher through modern-day scientists and the AMA Manual of Style. At one time, when experiments were simpler, the study design and statistical design were identical or very similar. With the complex research that is common today, which often includes manipulating variables to create new variables and the multiple (and different) analyses of a single data set, data collection is very different than statistical design. Thus, both a study design and a statistical design are necessary. Scientific manuscripts will be much easier to read and comprehend. A proper experimental design serves as a road map to the study methods, helping readers to understand more clearly how the data were obtained and, therefore, assisting them in properly analyzing the results.

United States Census 2000 Population with Bridged Race Categories. Vital and Health Statistics. Data Evaluation and Methods Research.

ERIC Educational Resources Information Center

Ingram, Deborah D.; Parker, Jennifer D.; Schenker, Nathaniel; Weed, James A.; Hamilton, Brady; Arias, Elizabeth; Madans, Jennifer H.

This report documents the National Center for Health Statistics' (NCHS) methods for bridging the Census 2000 multiple-race resident population to single-race categories and describing bridged race resident population estimates. Data came from the pooled 1997-2000 National Health Interview Surveys. The bridging models included demographic and…

Appropriate Statistical Analysis for Two Independent Groups of Likert-Type Data

ERIC Educational Resources Information Center

Warachan, Boonyasit

2011-01-01

The objective of this research was to determine the robustness and statistical power of three different methods for testing the hypothesis that ordinal samples of five and seven Likert categories come from equal populations. The three methods are the two sample t-test with equal variances, the Mann-Whitney test, and the Kolmogorov-Smirnov test. In…

A review on the multivariate statistical methods for dimensional reduction studies

NASA Astrophysics Data System (ADS)

Aik, Lim Eng; Kiang, Lam Chee; Mohamed, Zulkifley Bin; Hong, Tan Wei

2017-05-01

In this research study we have discussed multivariate statistical methods for dimensional reduction, which has been done by various researchers. The reduction of dimensionality is valuable to accelerate algorithm progression, as well as really may offer assistance with the last grouping/clustering precision. A lot of boisterous or even flawed info information regularly prompts a not exactly alluring algorithm progression. Expelling un-useful or dis-instructive information segments may for sure help the algorithm discover more broad grouping locales and principles and generally speaking accomplish better exhibitions on new data set.

Assessment of Reliable Change Using 95% Credible Intervals for the Differences in Proportions: A Statistical Analysis for Case-Study Methodology.

PubMed

Unicomb, Rachael; Colyvas, Kim; Harrison, Elisabeth; Hewat, Sally

2015-06-01

Case-study methodology studying change is often used in the field of speech-language pathology, but it can be criticized for not being statistically robust. Yet with the heterogeneous nature of many communication disorders, case studies allow clinicians and researchers to closely observe and report on change. Such information is valuable and can further inform large-scale experimental designs. In this research note, a statistical analysis for case-study data is outlined that employs a modification to the Reliable Change Index (Jacobson & Truax, 1991). The relationship between reliable change and clinical significance is discussed. Example data are used to guide the reader through the use and application of this analysis. A method of analysis is detailed that is suitable for assessing change in measures with binary categorical outcomes. The analysis is illustrated using data from one individual, measured before and after treatment for stuttering. The application of this approach to assess change in categorical, binary data has potential application in speech-language pathology. It enables clinicians and researchers to analyze results from case studies for their statistical and clinical significance. This new method addresses a gap in the research design literature, that is, the lack of analysis methods for noncontinuous data (such as counts, rates, proportions of events) that may be used in case-study designs.

Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

NASA Astrophysics Data System (ADS)

McCray, Wilmon Wil L., Jr.

The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization model and dashboard that demonstrates the use of statistical methods, statistical process control, sensitivity analysis, quantitative and optimization techniques to establish a baseline and predict future customer satisfaction index scores (outcomes). The American Customer Satisfaction Index (ACSI) model and industry benchmarks were used as a framework for the simulation model.

A Comparison between the Effect of Cooperative Learning Teaching Method and Lecture Teaching Method on Students' Learning and Satisfaction Level

ERIC Educational Resources Information Center

Mohammadjani, Farzad; Tonkaboni, Forouzan

2015-01-01

The aim of the present research is to investigate a comparison between the effect of cooperative learning teaching method and lecture teaching method on students' learning and satisfaction level. The research population consisted of all the fourth grade elementary school students of educational district 4 in Shiraz. The statistical population…

An overview of the mathematical and statistical analysis component of RICIS

NASA Technical Reports Server (NTRS)

Hallum, Cecil R.

1987-01-01

Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.

Change Detection in Rough Time Series

DTIC Science & Technology

2014-09-01

Business Statistics : An Inferential Approach, Dellen: San Francisco. [18] Winston, W. (1997) Operations Research Applications and Algorithms, Duxbury...distribution that can present significant challenges to conventional statistical tracking techniques. To address this problem the proposed method...applies hybrid fuzzy statistical techniques to series granules instead of to individual measures. Three examples demonstrated the robust nature of the

Teaching Statistics in APA-Accredited Doctoral Programs in Clinical and Counseling Psychology: A Syllabi Review

ERIC Educational Resources Information Center

Ord, Anna S.; Ripley, Jennifer S.; Hook, Joshua; Erspamer, Tiffany

2016-01-01

Although statistical methods and research design are crucial areas of competency for psychologists, few studies explore how statistics are taught across doctoral programs in psychology in the United States. The present study examined 153 American Psychological Association-accredited doctoral programs in clinical and counseling psychology and aimed…

Interpreting “statistical hypothesis testing” results in clinical research

PubMed Central

Sarmukaddam, Sanjeev B.

2012-01-01

Difference between “Clinical Significance and Statistical Significance” should be kept in mind while interpreting “statistical hypothesis testing” results in clinical research. This fact is already known to many but again pointed out here as philosophy of “statistical hypothesis testing” is sometimes unnecessarily criticized mainly due to failure in considering such distinction. Randomized controlled trials are also wrongly criticized similarly. Some scientific method may not be applicable in some peculiar/particular situation does not mean that the method is useless. Also remember that “statistical hypothesis testing” is not for decision making and the field of “decision analysis” is very much an integral part of science of statistics. It is not correct to say that “confidence intervals have nothing to do with confidence” unless one understands meaning of the word “confidence” as used in context of confidence interval. Interpretation of the results of every study should always consider all possible alternative explanations like chance, bias, and confounding. Statistical tests in inferential statistics are, in general, designed to answer the question “How likely is the difference found in random sample(s) is due to chance” and therefore limitation of relying only on statistical significance in making clinical decisions should be avoided. PMID:22707861

Myths and Misconceptions about Using Qualitative Methods in Assessment

ERIC Educational Resources Information Center

Harper, Shaun R.; Kuh, George D.

2007-01-01

The value of qualitative assessment approaches has been underestimated primarily because they are often juxtaposed against long-standing quantitative traditions and the widely accepted premise that the best research produces generalizable and statistically significant findings. Institutional researchers avoid qualitative methods for at least three…

Results of the Verification of the Statistical Distribution Model of Microseismicity Emission Characteristics

NASA Astrophysics Data System (ADS)

Cianciara, Aleksander

2016-09-01

The paper presents the results of research aimed at verifying the hypothesis that the Weibull distribution is an appropriate statistical distribution model of microseismicity emission characteristics, namely: energy of phenomena and inter-event time. It is understood that the emission under consideration is induced by the natural rock mass fracturing. Because the recorded emission contain noise, therefore, it is subjected to an appropriate filtering. The study has been conducted using the method of statistical verification of null hypothesis that the Weibull distribution fits the empirical cumulative distribution function. As the model describing the cumulative distribution function is given in an analytical form, its verification may be performed using the Kolmogorov-Smirnov goodness-of-fit test. Interpretations by means of probabilistic methods require specifying the correct model describing the statistical distribution of data. Because in these methods measurement data are not used directly, but their statistical distributions, e.g., in the method based on the hazard analysis, or in that that uses maximum value statistics.

Multiple Chronic Conditions among Adults Aged 45 and Over: Trends Over the Past 10 Years

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Use and Characteristics of Electronic Health Record Systems among Office-Based Physician Practices: United States, ...

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Clinical trials, epidemiology, and public confidence.

PubMed

Seigel, Daniel

2003-11-15

Critics in the media have become wary of exaggerated research claims from clinical trials and epidemiological studies. Closer to home, reviews of published studies find a high frequency of poor quality in research methods, including those used for statistical analysis. The statistical literature has long recognized that questionable research findings can occur when investigators fail to set aside their own outcome preferences as they analyse and interpret data. These preferences can be related to financial interests, a concern for patients, peer recognition, and commitment to a hypothesis. Several analyses of published papers provide evidence of an association between financial conflicts of interest and reported results. If we are to regain professional and lay confidence in research findings some changes are required. Clinical journals need to develop more competence in the review of analytic methods and provide space for thorough discussion of published papers whose results are challenged. Graduate schools need to prepare students for the conflicting interests that surround the practice of statistics. Above all, each of us must recognize our responsibility to use analytic procedures that illuminate the research issues rather than those serving special interests. Copyright 2003 John Wiley & Sons, Ltd.

To What Extent Is Mathematical Ability Predictive of Performance in a Methodology and Statistics Course? Can an Action Research Approach Be Used to Understand the Relevance of Mathematical Ability in Psychology Undergraduates?

ERIC Educational Resources Information Center

Bourne, Victoria J.

2014-01-01

Research methods and statistical analysis is typically the least liked and most anxiety provoking aspect of a psychology undergraduate degree, in large part due to the mathematical component of the content. In this first cycle of a piece of action research, students' mathematical ability is examined in relation to their performance across…

Fulfilling the law of a single independent variable and improving the result of mathematical educational research

NASA Astrophysics Data System (ADS)

Pardimin, H.; Arcana, N.

2018-01-01

Many types of research in the field of mathematics education apply the Quasi-Experimental method and statistical analysis use t-test. Quasi-experiment has a weakness that is difficult to fulfil “the law of a single independent variable”. T-test also has a weakness that is a generalization of the conclusions obtained is less powerful. This research aimed to find ways to reduce the weaknesses of the Quasi-experimental method and improved the generalization of the research results. The method applied in the research was a non-interactive qualitative method, and the type was concept analysis. Concepts analysed are the concept of statistics, research methods of education, and research reports. The result represented a way to overcome the weaknesses of quasi-Experiments and T-test. In addition, the way was to apply a combination of Factorial Design and Balanced Design, which the authors refer to as Factorial-Balanced Design. The advantages of this design are: (1) almost fulfilling “the low of single independent variable” so no need to test the similarity of the academic ability, (2) the sample size of the experimental group and the control group became larger and equal; so it becomes robust to deal with violations of the assumptions of the ANOVA test.

A Selective Overview of Variable Selection in High Dimensional Feature Space

PubMed Central

Fan, Jianqing

2010-01-01

High dimensional statistical problems arise from diverse fields of scientific research and technological development. Variable selection plays a pivotal role in contemporary statistical learning and scientific discoveries. The traditional idea of best subset selection methods, which can be regarded as a specific form of penalized likelihood, is computationally too expensive for many modern statistical applications. Other forms of penalized likelihood methods have been successfully developed over the last decade to cope with high dimensionality. They have been widely applied for simultaneously selecting important variables and estimating their effects in high dimensional statistical inference. In this article, we present a brief account of the recent developments of theory, methods, and implementations for high dimensional variable selection. What limits of the dimensionality such methods can handle, what the role of penalty functions is, and what the statistical properties are rapidly drive the advances of the field. The properties of non-concave penalized likelihood and its roles in high dimensional statistical modeling are emphasized. We also review some recent advances in ultra-high dimensional variable selection, with emphasis on independence screening and two-scale methods. PMID:21572976

Enhancing health students' understanding of generic research concepts using a web-based video resource.

PubMed

Callaghan, Lynne; Lea, Susan J; Mutton, Lauren; Whittlesea, Emma

2011-11-01

This paper presents the development and evaluation of a set of innovative video resources aimed at enhancing health students' understanding and learning of generic research concepts. It is vital that health students achieve a solid foundation in research methods in order to support and inform evidence-based practice. Research concepts were identified through a stakeholder consultation with research methods teaching staff from a variety of health professions. Research concepts and processes included reliability, validity, statistical significance, descriptive statistics, qualitative and quantitative methods, sampling and population, research ethics and searching for and evaluating literature. Videos were produced, informed by a 3-component model, including: first, animated slides of concept definition, second, acted analogical scenarios of concepts and third, interviews with staff regarding the application of the concepts in their own research. Workshop-style focus groups were conducted with 27 students from midwifery, paramedicine and physiotherapy degree programmes. Overall, students perceived the resources as demystifying the topic of research methods through the clarification of definition and application of concepts and making sense of concepts through the analogical videos. Students evaluated the resources extremely positively in comparison with books and lectures and believed that the combination of audio and visual media benefited their learning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Publication Bias ( The "File-Drawer Problem") in Scientific Inference

NASA Technical Reports Server (NTRS)

Scargle, Jeffrey D.; DeVincenzi, Donald (Technical Monitor)

1999-01-01

Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always miss-estimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical combination can be trusted only if it is known with certainty that all studies that have been carried out are included. Such certainty is virtually impossible to achieve in literature surveys.

Comparative effectiveness research methodology using secondary data: A starting user's guide.

PubMed

Sun, Maxine; Lipsitz, Stuart R

2018-04-01

The use of secondary data, such as claims or administrative data, in comparative effectiveness research has grown tremendously in recent years. We believe that the current review can help investigators relying on secondary data to (1) gain insight into both the methodologies and statistical methods, (2) better understand the necessity of a rigorous planning before initiating a comparative effectiveness investigation, and (3) optimize the quality of their investigations. Specifically, we review concepts of adjusted analyses and confounders, methods of propensity score analyses, and instrumental variable analyses, risk prediction models (logistic and time-to-event), decision-curve analysis, as well as the interpretation of the P value and hypothesis testing. Overall, we hope that the current review article can help research investigators relying on secondary data to perform comparative effectiveness research better understand the necessity of a rigorous planning before study start, and gain better insight in the choice of statistical methods so as to optimize the quality of the research study. Copyright © 2017 Elsevier Inc. All rights reserved.

Uncertainties in Estimates of Fleet Average Fuel Economy : A Statistical Evaluation

DOT National Transportation Integrated Search

1977-01-01

Research was performed to assess the current Federal procedure for estimating the average fuel economy of each automobile manufacturer's new car fleet. Test vehicle selection and fuel economy estimation methods were characterized statistically and so...

Diagnostic History and Treatment of School-Aged Children with Autism Spectrum Disorder and Special Health Care Needs

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Electronic Health Record Systems and Intent to Apply for Meaningful Use Incentives among Office-based Physician ...

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care Utilization and Expenditure Survey Clearinghouse on Health Indexes Statistical Notes for Health ...

Likert scales, levels of measurement and the "laws" of statistics.

PubMed

Norman, Geoff

2010-12-01

Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The data are from Likert scales, which are ordinal, so parametric statistics cannot be used. In this paper, I dissect these arguments, and show that many studies, dating back to the 1930s consistently show that parametric statistics are robust with respect to violations of these assumptions. Hence, challenges like those above are unfounded, and parametric methods can be utilized without concern for "getting the wrong answer".

Age Difference in Research Course Satisfaction in a Blended Ed.D. Program: A Moderated Mediation Model of the Effects of Internet Self-Efficacy and Statistics Anxiety

ERIC Educational Resources Information Center

Liu, Lu; Haque, M. D.

2017-01-01

This study identified the moderated mediation relationship among age, Internet self-efficacy, and statistics anxiety on student satisfaction after controlling for demographics and technology experiences in research methods courses in a blended professional doctoral program. One hundred and thirty-one students in a three-year Ed.D. Program…

A data recipient centered de-identification method to retain statistical attributes.

PubMed

Gal, Tamas S; Tucker, Thomas C; Gangopadhyay, Aryya; Chen, Zhiyuan

2014-08-01

Privacy has always been a great concern of patients and medical service providers. As a result of the recent advances in information technology and the government's push for the use of Electronic Health Record (EHR) systems, a large amount of medical data is collected and stored electronically. This data needs to be made available for analysis but at the same time patient privacy has to be protected through de-identification. Although biomedical researchers often describe their research plans when they request anonymized data, most existing anonymization methods do not use this information when de-identifying the data. As a result, the anonymized data may not be useful for the planned research project. This paper proposes a data recipient centered approach to tailor the de-identification method based on input from the recipient of the data. We demonstrate our approach through an anonymization project for biomedical researchers with specific goals to improve the utility of the anonymized data for statistical models used for their research project. The selected algorithm improves a privacy protection method called Condensation by Aggarwal et al. Our methods were tested and validated on real cancer surveillance data provided by the Kentucky Cancer Registry. Copyright © 2014 Elsevier Inc. All rights reserved.

Evaluating statistical and clinical significance of intervention effects in single-case experimental designs: an SPSS method to analyze univariate data.

PubMed

Maric, Marija; de Haan, Else; Hogendoorn, Sanne M; Wolters, Lidewij H; Huizenga, Hilde M

2015-03-01

Single-case experimental designs are useful methods in clinical research practice to investigate individual client progress. Their proliferation might have been hampered by methodological challenges such as the difficulty applying existing statistical procedures. In this article, we describe a data-analytic method to analyze univariate (i.e., one symptom) single-case data using the common package SPSS. This method can help the clinical researcher to investigate whether an intervention works as compared with a baseline period or another intervention type, and to determine whether symptom improvement is clinically significant. First, we describe the statistical method in a conceptual way and show how it can be implemented in SPSS. Simulation studies were performed to determine the number of observation points required per intervention phase. Second, to illustrate this method and its implications, we present a case study of an adolescent with anxiety disorders treated with cognitive-behavioral therapy techniques in an outpatient psychotherapy clinic, whose symptoms were regularly assessed before each session. We provide a description of the data analyses and results of this case study. Finally, we discuss the advantages and shortcomings of the proposed method. Copyright © 2014. Published by Elsevier Ltd.

Statistics in the Workplace: A Survey of Use by Recent Graduates with Higher Degrees

ERIC Educational Resources Information Center

Harraway, John A.; Barker, Richard J.

2005-01-01

A postal survey was conducted regarding statistical techniques, research methods and software used in the workplace by 913 graduates with PhD and Masters degrees in the biological sciences, psychology, business, economics, and statistics. The study identified gaps between topics and techniques learned at university and those used in the workplace,…

A clinical research analytics toolkit for cohort study.

PubMed

Yu, Yiqin; Zhu, Yu; Sun, Xingzhi; Tao, Ying; Zhang, Shuo; Xu, Linhao; Pan, Yue

2012-01-01

This paper presents a clinical informatics toolkit that can assist physicians to conduct cohort studies effectively and efficiently. The toolkit has three key features: 1) support of procedures defined in epidemiology, 2) recommendation of statistical methods in data analysis, and 3) automatic generation of research reports. On one hand, our system can help physicians control research quality by leveraging the integrated knowledge of epidemiology and medical statistics; on the other hand, it can improve productivity by reducing the complexities for physicians during their cohort studies.

Current and future health care professionals attitudes toward and knowledge of statistics: How confidence influences learning.

PubMed

Baghi, Heibatollah; Kornides, Melanie L

2013-01-01

Health care professionals require some understanding of statistics to successfully implement evidence based practice. Developing competency in statistical reasoning is necessary for students training in health care administration, research, and clinical care. Recently, the interest in healthcare professional's attitudes toward statistics has increased substantially due to evidence that these attitudes can hinder professionalism developing an understanding of statistical concepts. In this study, we analyzed pre- and post-instruction attitudes towards and knowledge of statistics obtained from health science graduate students, including nurses and nurse practitioners, enrolled in an introductory graduate course in statistics (n = 165). Results show that the students already held generally positive attitudes toward statistics at the beginning of course. However, these attitudes-along with the students' statistical proficiency-improved after 10 weeks of instruction. The results have implications for curriculum design and delivery methods as well as for health professionals' effective use of statistics in critically evaluating and utilizing research in their practices.

A review of empirical research related to the use of small quantitative samples in clinical outcome scale development.

PubMed

Houts, Carrie R; Edwards, Michael C; Wirth, R J; Deal, Linda S

2016-11-01

There has been a notable increase in the advocacy of using small-sample designs as an initial quantitative assessment of item and scale performance during the scale development process. This is particularly true in the development of clinical outcome assessments (COAs), where Rasch analysis has been advanced as an appropriate statistical tool for evaluating the developing COAs using a small sample. We review the benefits such methods are purported to offer from both a practical and statistical standpoint and detail several problematic areas, including both practical and statistical theory concerns, with respect to the use of quantitative methods, including Rasch-consistent methods, with small samples. The feasibility of obtaining accurate information and the potential negative impacts of misusing large-sample statistical methods with small samples during COA development are discussed.

Reliability and Validity of the Research Methods Skills Assessment

ERIC Educational Resources Information Center

Smith, Tamarah; Smith, Samantha

2018-01-01

The Research Methods Skills Assessment (RMSA) was created to measure psychology majors' statistics knowledge and skills. The American Psychological Association's Guidelines for the Undergraduate Major in Psychology (APA, 2007, 2013) served as a framework for development. Results from a Rasch analysis with data from n = 330 undergraduates showed…

Virtualising the Quantitative Research Methods Course: An Island-Based Approach

ERIC Educational Resources Information Center

Baglin, James; Reece, John; Baker, Jenalle

2015-01-01

Many recent improvements in pedagogical practice have been enabled by the rapid development of innovative technologies, particularly for teaching quantitative research methods and statistics. This study describes the design, implementation, and evaluation of a series of specialised computer laboratory sessions. The sessions combined the use of an…

Quantitative Research Methods Training in Education Leadership and Administration Preparation Programs as Disciplined Inquiry for Building School Improvement Capacity

ERIC Educational Resources Information Center

Bowers, Alex J.

2017-01-01

The quantitative research methods course is a staple of graduate programs in education leadership and administration. Historically, these courses serve to train aspiring district and school leaders in fundamental statistical research topics. This article argues for programs to focus as well in these courses on helping aspiring leaders develop…

[Application of chemometrics in composition-activity relationship research of traditional Chinese medicine].

PubMed

Han, Sheng-Nan

2014-07-01

Chemometrics is a new branch of chemistry which is widely applied to various fields of analytical chemistry. Chemometrics can use theories and methods of mathematics, statistics, computer science and other related disciplines to optimize the chemical measurement process and maximize access to acquire chemical information and other information on material systems by analyzing chemical measurement data. In recent years, traditional Chinese medicine has attracted widespread attention. In the research of traditional Chinese medicine, it has been a key problem that how to interpret the relationship between various chemical components and its efficacy, which seriously restricts the modernization of Chinese medicine. As chemometrics brings the multivariate analysis methods into the chemical research, it has been applied as an effective research tool in the composition-activity relationship research of Chinese medicine. This article reviews the applications of chemometrics methods in the composition-activity relationship research in recent years. The applications of multivariate statistical analysis methods (such as regression analysis, correlation analysis, principal component analysis, etc. ) and artificial neural network (such as back propagation artificial neural network, radical basis function neural network, support vector machine, etc. ) are summarized, including the brief fundamental principles, the research contents and the advantages and disadvantages. Finally, the existing main problems and prospects of its future researches are proposed.

Total Quality Management: Statistics and Graphics III - Experimental Design and Taguchi Methods. AIR 1993 Annual Forum Paper.

ERIC Educational Resources Information Center

Schwabe, Robert A.

Interest in Total Quality Management (TQM) at institutions of higher education has been stressed in recent years as an important area of activity for institutional researchers. Two previous AIR Forum papers have presented some of the statistical and graphical methods used for TQM. This paper, the third in the series, first discusses some of the…

Computational Electromagnetics Application to Small Geometric Anomalies and Associated Ucertainty Evaluation

DTIC Science & Technology

2010-02-28

implemented a fast method to enable the statistical characterization of electromagnetic interference and compatibility (EMI/EMC) phenomena on electrically...higher accuracy is needed, e.g., to compute higher moment statistics . To address this problem, we have developed adaptive stochastic collocation methods ...SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) AF OFFICE OF SCIENTIFIC RESEARCH 875 N. RANDOLPH ST. ROOM 3112 ARLINGTON VA 22203 UA

Installing a Practical Research Project and Interpreting Research Results

Treesearch

Kasten R. Dumroese; David L. Wenny

2003-01-01

The basic concepts of the scientific method and research process are reviewed. An example from a bareroot nursery demonstrates how a practical research project can be done at any type of nursery, meshing sound statistical principles with the limitations of busy nursery managers.

Examining the Reproducibility of 6 Published Studies in Public Health Services and Systems Research.

PubMed

Harris, Jenine K; B Wondmeneh, Sarah; Zhao, Yiqiang; Leider, Jonathon P

2018-02-23

Research replication, or repeating a study de novo, is the scientific standard for building evidence and identifying spurious results. While replication is ideal, it is often expensive and time consuming. Reproducibility, or reanalysis of data to verify published findings, is one proposed minimum alternative standard. While a lack of research reproducibility has been identified as a serious and prevalent problem in biomedical research and a few other fields, little work has been done to examine the reproducibility of public health research. We examined reproducibility in 6 studies from the public health services and systems research subfield of public health research. Following the methods described in each of the 6 papers, we computed the descriptive and inferential statistics for each study. We compared our results with the original study results and examined the percentage differences in descriptive statistics and differences in effect size, significance, and precision of inferential statistics. All project work was completed in 2017. We found consistency between original and reproduced results for each paper in at least 1 of the 4 areas examined. However, we also found some inconsistency. We identified incorrect transcription of results and omitting detail about data management and analyses as the primary contributors to the inconsistencies. Increasing reproducibility, or reanalysis of data to verify published results, can improve the quality of science. Researchers, journals, employers, and funders can all play a role in improving the reproducibility of science through several strategies including publishing data and statistical code, using guidelines to write clear and complete methods sections, conducting reproducibility reviews, and incentivizing reproducible science.

Introducing StatHand: A Cross-Platform Mobile Application to Support Students' Statistical Decision Making.

PubMed

Allen, Peter J; Roberts, Lynne D; Baughman, Frank D; Loxton, Natalie J; Van Rooy, Dirk; Rock, Adam J; Finlay, James

2016-01-01

Although essential to professional competence in psychology, quantitative research methods are a known area of weakness for many undergraduate psychology students. Students find selecting appropriate statistical tests and procedures for different types of research questions, hypotheses and data types particularly challenging, and these skills are not often practiced in class. Decision trees (a type of graphic organizer) are known to facilitate this decision making process, but extant trees have a number of limitations. Furthermore, emerging research suggests that mobile technologies offer many possibilities for facilitating learning. It is within this context that we have developed StatHand, a free cross-platform application designed to support students' statistical decision making. Developed with the support of the Australian Government Office for Learning and Teaching, StatHand guides users through a series of simple, annotated questions to help them identify a statistical test or procedure appropriate to their circumstances. It further offers the guidance necessary to run these tests and procedures, then interpret and report their results. In this Technology Report we will overview the rationale behind StatHand, before describing the feature set of the application. We will then provide guidelines for integrating StatHand into the research methods curriculum, before concluding by outlining our road map for the ongoing development and evaluation of StatHand.

Evaluation of trauma care using TRISS method: the role of adjusted misclassification rate and adjusted w-statistic.

PubMed

Llullaku, Sadik S; Hyseni, Nexhmi Sh; Bytyçi, Cen I; Rexhepi, Sylejman K

2009-01-15

Major trauma is a leading cause of death worldwide. Evaluation of trauma care using Trauma Injury and Injury Severity Score (TRISS) method is focused in trauma outcome (deaths and survivors). For testing TRISS method TRISS misclassification rate is used. Calculating w-statistic, as a difference between observed and TRISS expected survivors, we compare our trauma care results with the TRISS standard. The aim of this study is to analyze interaction between misclassification rate and w-statistic and to adjust these parameters to be closer to the truth. Analysis of components of TRISS misclassification rate and w-statistic and actual trauma outcome. The component of false negative (FN) (by TRISS method unexpected deaths) has two parts: preventable (Pd) and non-preventable (nonPd) trauma deaths. Pd represents inappropriate trauma care of an institution; otherwise nonpreventable trauma deaths represents errors in TRISS method. Removing patients with preventable trauma deaths we get an Adjusted misclassification rate: (FP + FN - Pd)/N or (b+c-Pd)/N. Substracting nonPd from FN value in w-statistic formula we get an Adjusted w-statistic: [FP-(FN - nonPd)]/N, respectively (FP-Pd)/N, or (b-Pd)/N). Because adjusted formulas clean method from inappropriate trauma care, and clean trauma care from the methods error, TRISS adjusted misclassification rate and adjusted w-statistic gives more realistic results and may be used in researches of trauma outcome.

Analysis of Coastal Dunes: A Remote Sensing and Statistical Approach.

ERIC Educational Resources Information Center

Jones, J. Richard

1985-01-01

Remote sensing analysis and statistical methods were used to analyze the coastal dunes of Plum Island, Massachusetts. The research methodology used provides an example of a student project for remote sensing, geomorphology, or spatial analysis courses at the university level. (RM)

Applied statistics in agricultural, biological, and environmental sciences.

USDA-ARS?s Scientific Manuscript database

Agronomic research often involves measurement and collection of multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate statistical methods encompass the simultaneous analysis of all random variables measured on each experimental or s...

Two Paradoxes in Linear Regression Analysis.

PubMed

Feng, Ge; Peng, Jing; Tu, Dongke; Zheng, Julia Z; Feng, Changyong

2016-12-25

Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection.

Compendium of Abstracts on Statistical Applications in Geotechnical Engineering.

DTIC Science & Technology

1983-09-01

research in the application of probabilistic and statistical methods to soil mechanics, rock mechanics, and engineering geology problems have grown markedly...probability, statistics, soil mechanics, rock mechanics, and engineering geology. 2. The purpose of this report is to make available to the U. S...Deformation Dynamic Response Analysis Seepage, Soil Permeability and Piping Earthquake Engineering, Seismology, Settlement and Heave Seismic Risk Analysis

The Effect of Project Based Learning on the Statistical Literacy Levels of Student 8th Grade

ERIC Educational Resources Information Center

Koparan, Timur; Güven, Bülent

2014-01-01

This study examines the effect of project based learning on 8th grade students' statistical literacy levels. A performance test was developed for this aim. Quasi-experimental research model was used in this article. In this context, the statistics were taught with traditional method in the control group and it was taught using project based…

The Effect on the 8th Grade Students' Attitude towards Statistics of Project Based Learning

ERIC Educational Resources Information Center

Koparan, Timur; Güven, Bülent

2014-01-01

This study investigates the effect of the project based learning approach on 8th grade students' attitude towards statistics. With this aim, an attitude scale towards statistics was developed. Quasi-experimental research model was used in this study. Following this model in the control group the traditional method was applied to teach statistics…

Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies.

PubMed

Vieira, Rute; McDonald, Suzanne; Araújo-Soares, Vera; Sniehotta, Falko F; Henderson, Robin

2017-09-01

N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.

Linguistic Alternatives to Quantitative Research Strategies. Part One: How Linguistic Mechanisms Advance Research Outcomes

ERIC Educational Resources Information Center

Yeager, Joseph; Sommer, Linda

2007-01-01

Combining psycholinguistic technologies and systems analysis created advances in motivational profiling and numerous new behavioral engineering applications. These advances leapfrog many mainstream statistical research methods, producing superior research results via cause-effect language mechanisms. Entire industries explore motives ranging from…

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

ERIC Educational Resources Information Center

van de Schoot, Rens; Kaplan, David; Denissen, Jaap; Asendorpf, Jens B.; Neyer, Franz J.; van Aken, Marcel A. G.

2014-01-01

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are…

Assessing Person-Centered Outcomes in Practice Research: A Latent Transition Profile Framework

ERIC Educational Resources Information Center

Thompson, Aaron M.; Macy, Rebecca J.; Fraser, Mark W.

2011-01-01

Advances in statistics provide new methods for analyzing practice data. These advances include person-centered methods (PCMs) that identify subgroups of research participants with similar characteristics. PCMs derive from a frame of reference that is similar to the risk factor perspective in practice. In practice, the delivery of services is often…

Clinical relevance vs. statistical significance: Using neck outcomes in patients with temporomandibular disorders as an example.

PubMed

Armijo-Olivo, Susan; Warren, Sharon; Fuentes, Jorge; Magee, David J

2011-12-01

Statistical significance has been used extensively to evaluate the results of research studies. Nevertheless, it offers only limited information to clinicians. The assessment of clinical relevance can facilitate the interpretation of the research results into clinical practice. The objective of this study was to explore different methods to evaluate the clinical relevance of the results using a cross-sectional study as an example comparing different neck outcomes between subjects with temporomandibular disorders and healthy controls. Subjects were compared for head and cervical posture, maximal cervical muscle strength, endurance of the cervical flexor and extensor muscles, and electromyographic activity of the cervical flexor muscles during the CranioCervical Flexion Test (CCFT). The evaluation of clinical relevance of the results was performed based on the effect size (ES), minimal important difference (MID), and clinical judgement. The results of this study show that it is possible to have statistical significance without having clinical relevance, to have both statistical significance and clinical relevance, to have clinical relevance without having statistical significance, or to have neither statistical significance nor clinical relevance. The evaluation of clinical relevance in clinical research is crucial to simplify the transfer of knowledge from research into practice. Clinical researchers should present the clinical relevance of their results. Copyright © 2011 Elsevier Ltd. All rights reserved.

The HCUP SID Imputation Project: Improving Statistical Inferences for Health Disparities Research by Imputing Missing Race Data.

PubMed

Ma, Yan; Zhang, Wei; Lyman, Stephen; Huang, Yihe

2018-06-01

To identify the most appropriate imputation method for missing data in the HCUP State Inpatient Databases (SID) and assess the impact of different missing data methods on racial disparities research. HCUP SID. A novel simulation study compared four imputation methods (random draw, hot deck, joint multiple imputation [MI], conditional MI) for missing values for multiple variables, including race, gender, admission source, median household income, and total charges. The simulation was built on real data from the SID to retain their hierarchical data structures and missing data patterns. Additional predictive information from the U.S. Census and American Hospital Association (AHA) database was incorporated into the imputation. Conditional MI prediction was equivalent or superior to the best performing alternatives for all missing data structures and substantially outperformed each of the alternatives in various scenarios. Conditional MI substantially improved statistical inferences for racial health disparities research with the SID. © Health Research and Educational Trust.

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

PubMed

Crown, William; Chang, Jessica; Olson, Melvin; Kahler, Kristijan; Swindle, Jason; Buzinec, Paul; Shah, Nilay; Borah, Bijan

2015-09-01

Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

Statistical and Machine Learning forecasting methods: Concerns and ways forward

PubMed Central

Makridakis, Spyros; Assimakopoulos, Vassilios

2018-01-01

Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions. PMID:29584784

Reconciling statistical and systems science approaches to public health.

PubMed

Ip, Edward H; Rahmandad, Hazhir; Shoham, David A; Hammond, Ross; Huang, Terry T-K; Wang, Youfa; Mabry, Patricia L

2013-10-01

Although systems science has emerged as a set of innovative approaches to study complex phenomena, many topically focused researchers including clinicians and scientists working in public health are somewhat befuddled by this methodology that at times appears to be radically different from analytic methods, such as statistical modeling, to which the researchers are accustomed. There also appears to be conflicts between complex systems approaches and traditional statistical methodologies, both in terms of their underlying strategies and the languages they use. We argue that the conflicts are resolvable, and the sooner the better for the field. In this article, we show how statistical and systems science approaches can be reconciled, and how together they can advance solutions to complex problems. We do this by comparing the methods within a theoretical framework based on the work of population biologist Richard Levins. We present different types of models as representing different tradeoffs among the four desiderata of generality, realism, fit, and precision.

Reconciling Statistical and Systems Science Approaches to Public Health

PubMed Central

Ip, Edward H.; Rahmandad, Hazhir; Shoham, David A.; Hammond, Ross; Huang, Terry T.-K.; Wang, Youfa; Mabry, Patricia L.

2016-01-01

Although systems science has emerged as a set of innovative approaches to study complex phenomena, many topically focused researchers including clinicians and scientists working in public health are somewhat befuddled by this methodology that at times appears to be radically different from analytic methods, such as statistical modeling, to which the researchers are accustomed. There also appears to be conflicts between complex systems approaches and traditional statistical methodologies, both in terms of their underlying strategies and the languages they use. We argue that the conflicts are resolvable, and the sooner the better for the field. In this article, we show how statistical and systems science approaches can be reconciled, and how together they can advance solutions to complex problems. We do this by comparing the methods within a theoretical framework based on the work of population biologist Richard Levins. We present different types of models as representing different tradeoffs among the four desiderata of generality, realism, fit, and precision. PMID:24084395

Detecting the contagion effect in mass killings; a constructive example of the statistical advantages of unbinned likelihood methods

PubMed Central

Mubayi, Anuj; Castillo-Chavez, Carlos

2018-01-01

Background When attempting to statistically distinguish between a null and an alternative hypothesis, many researchers in the life and social sciences turn to binned statistical analysis methods, or methods that are simply based on the moments of a distribution (such as the mean, and variance). These methods have the advantage of simplicity of implementation, and simplicity of explanation. However, when null and alternative hypotheses manifest themselves in subtle differences in patterns in the data, binned analysis methods may be insensitive to these differences, and researchers may erroneously fail to reject the null hypothesis when in fact more sensitive statistical analysis methods might produce a different result when the null hypothesis is actually false. Here, with a focus on two recent conflicting studies of contagion in mass killings as instructive examples, we discuss how the use of unbinned likelihood methods makes optimal use of the information in the data; a fact that has been long known in statistical theory, but perhaps is not as widely appreciated amongst general researchers in the life and social sciences. Methods In 2015, Towers et al published a paper that quantified the long-suspected contagion effect in mass killings. However, in 2017, Lankford & Tomek subsequently published a paper, based upon the same data, that claimed to contradict the results of the earlier study. The former used unbinned likelihood methods, and the latter used binned methods, and comparison of distribution moments. Using these analyses, we also discuss how visualization of the data can aid in determination of the most appropriate statistical analysis methods to distinguish between a null and alternate hypothesis. We also discuss the importance of assessment of the robustness of analysis results to methodological assumptions made (for example, arbitrary choices of number of bins and bin widths when using binned methods); an issue that is widely overlooked in the literature, but is critical to analysis reproducibility and robustness. Conclusions When an analysis cannot distinguish between a null and alternate hypothesis, care must be taken to ensure that the analysis methodology itself maximizes the use of information in the data that can distinguish between the two hypotheses. The use of binned methods by Lankford & Tomek (2017), that examined how many mass killings fell within a 14 day window from a previous mass killing, substantially reduced the sensitivity of their analysis to contagion effects. The unbinned likelihood methods used by Towers et al (2015) did not suffer from this problem. While a binned analysis might be favorable for simplicity and clarity of presentation, unbinned likelihood methods are preferable when effects might be somewhat subtle. PMID:29742115

Models of dyadic social interaction.

PubMed Central

Griffin, Dale; Gonzalez, Richard

2003-01-01

We discuss the logic of research designs for dyadic interaction and present statistical models with parameters that are tied to psychologically relevant constructs. Building on Karl Pearson's classic nineteenth-century statistical analysis of within-organism similarity, we describe several approaches to indexing dyadic interdependence and provide graphical methods for visualizing dyadic data. We also describe several statistical and conceptual solutions to the 'levels of analytic' problem in analysing dyadic data. These analytic strategies allow the researcher to examine and measure psychological questions of interdependence and social influence. We provide illustrative data from casually interacting and romantic dyads. PMID:12689382

Methods for Evaluating Mammography Imaging Techniques

DTIC Science & Technology

1999-06-01

Distribution Unlimited 12b. DIS5TRIBUTION CODE 13. ABSTRACT (Maximum 200 words) This Department of Defense Breast Cancer Research Program Career...Development Award is enabling Dr. Rütter to develop bio’statistical methods for breast cancer research. Dr. Rutter is focusing on methods for...evaluating the accuracy of breast cancer screening. This four year program includes advanced training in the epidemiology of breast cancer , training in

Reporting and Interpreting Effect Size in Quantitative Agricultural Education Research

ERIC Educational Resources Information Center

Kotrlik, Joe W.; Williams, Heather A.; Jabor, M. Khata

2011-01-01

The Journal of Agricultural Education (JAE) requires authors to follow the guidelines stated in the Publication Manual of the American Psychological Association [APA] (2009) in preparing research manuscripts, and to utilize accepted research and statistical methods in conducting quantitative research studies. The APA recommends the reporting of…

Two Paradoxes in Linear Regression Analysis

PubMed Central

FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong

2016-01-01

Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214

An attribute-driven statistics generator for use in a G.I.S. environment

NASA Technical Reports Server (NTRS)

Thomas, R. W.; Ritter, P. R.; Kaugars, A.

1984-01-01

When performing research using digital geographic information it is often useful to produce quantitative characterizations of the data, usually within some constraints. In the research environment the different combinations of required data and constraints can often become quite complex. This paper describes a technique that gives the researcher a powerful and flexible way to set up many possible combinations of data and constraints without having to perform numerous intermediate steps or create temporary data bands. This method provides an efficient way to produce descriptive statistics in such situations.

Detecting the contagion effect in mass killings; a constructive example of the statistical advantages of unbinned likelihood methods.

PubMed

Towers, Sherry; Mubayi, Anuj; Castillo-Chavez, Carlos

2018-01-01

When attempting to statistically distinguish between a null and an alternative hypothesis, many researchers in the life and social sciences turn to binned statistical analysis methods, or methods that are simply based on the moments of a distribution (such as the mean, and variance). These methods have the advantage of simplicity of implementation, and simplicity of explanation. However, when null and alternative hypotheses manifest themselves in subtle differences in patterns in the data, binned analysis methods may be insensitive to these differences, and researchers may erroneously fail to reject the null hypothesis when in fact more sensitive statistical analysis methods might produce a different result when the null hypothesis is actually false. Here, with a focus on two recent conflicting studies of contagion in mass killings as instructive examples, we discuss how the use of unbinned likelihood methods makes optimal use of the information in the data; a fact that has been long known in statistical theory, but perhaps is not as widely appreciated amongst general researchers in the life and social sciences. In 2015, Towers et al published a paper that quantified the long-suspected contagion effect in mass killings. However, in 2017, Lankford & Tomek subsequently published a paper, based upon the same data, that claimed to contradict the results of the earlier study. The former used unbinned likelihood methods, and the latter used binned methods, and comparison of distribution moments. Using these analyses, we also discuss how visualization of the data can aid in determination of the most appropriate statistical analysis methods to distinguish between a null and alternate hypothesis. We also discuss the importance of assessment of the robustness of analysis results to methodological assumptions made (for example, arbitrary choices of number of bins and bin widths when using binned methods); an issue that is widely overlooked in the literature, but is critical to analysis reproducibility and robustness. When an analysis cannot distinguish between a null and alternate hypothesis, care must be taken to ensure that the analysis methodology itself maximizes the use of information in the data that can distinguish between the two hypotheses. The use of binned methods by Lankford & Tomek (2017), that examined how many mass killings fell within a 14 day window from a previous mass killing, substantially reduced the sensitivity of their analysis to contagion effects. The unbinned likelihood methods used by Towers et al (2015) did not suffer from this problem. While a binned analysis might be favorable for simplicity and clarity of presentation, unbinned likelihood methods are preferable when effects might be somewhat subtle.

Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

NASA Technical Reports Server (NTRS)

Calkins, D. S.

1998-01-01

When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

Statistical Methods for Generalized Linear Models with Covariates Subject to Detection Limits.

PubMed

Bernhardt, Paul W; Wang, Huixia J; Zhang, Daowen

2015-05-01

Censored observations are a common occurrence in biomedical data sets. Although a large amount of research has been devoted to estimation and inference for data with censored responses, very little research has focused on proper statistical procedures when predictors are censored. In this paper, we consider statistical methods for dealing with multiple predictors subject to detection limits within the context of generalized linear models. We investigate and adapt several conventional methods and develop a new multiple imputation approach for analyzing data sets with predictors censored due to detection limits. We establish the consistency and asymptotic normality of the proposed multiple imputation estimator and suggest a computationally simple and consistent variance estimator. We also demonstrate that the conditional mean imputation method often leads to inconsistent estimates in generalized linear models, while several other methods are either computationally intensive or lead to parameter estimates that are biased or more variable compared to the proposed multiple imputation estimator. In an extensive simulation study, we assess the bias and variability of different approaches within the context of a logistic regression model and compare variance estimation methods for the proposed multiple imputation estimator. Lastly, we apply several methods to analyze the data set from a recently-conducted GenIMS study.

Identifying Minefields and Verifying Clearance: Adapting Statistical Methods for UXO Target Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilbert, Richard O.; O'Brien, Robert F.; Wilson, John E.

2003-09-01

It may not be feasible to completely survey large tracts of land suspected of containing minefields. It is desirable to develop a characterization protocol that will confidently identify minefields within these large land tracts if they exist. Naturally, surveying areas of greatest concern and most likely locations would be necessary but will not provide the needed confidence that an unknown minefield had not eluded detection. Once minefields are detected, methods are needed to bound the area that will require detailed mine detection surveys. The US Department of Defense Strategic Environmental Research and Development Program (SERDP) is sponsoring the development ofmore » statistical survey methods and tools for detecting potential UXO targets. These methods may be directly applicable to demining efforts. Statistical methods are employed to determine the optimal geophysical survey transect spacing to have confidence of detecting target areas of a critical size, shape, and anomaly density. Other methods under development determine the proportion of a land area that must be surveyed to confidently conclude that there are no UXO present. Adaptive sampling schemes are also being developed as an approach for bounding the target areas. These methods and tools will be presented and the status of relevant research in this area will be discussed.« less

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

DOE PAGES

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

2017-10-29

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Comparing multiple statistical methods for inverse prediction in nuclear forensics applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, John R.; Zhang, Adah; Anderson-Cook, Christine Michaela

Forensic science seeks to predict source characteristics using measured observables. Statistically, this objective can be thought of as an inverse problem where interest is in the unknown source characteristics or factors ( X) of some underlying causal model producing the observables or responses (Y = g ( X) + error). Here, this paper reviews several statistical methods for use in inverse problems and demonstrates that comparing results from multiple methods can be used to assess predictive capability. Motivation for assessing inverse predictions comes from the desired application to historical and future experiments involving nuclear material production for forensics research inmore » which inverse predictions, along with an assessment of predictive capability, are desired.« less

Statistical procedures for analyzing mental health services data.

PubMed

Elhai, Jon D; Calhoun, Patrick S; Ford, Julian D

2008-08-15

In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.

LAKE DATA ANALYSIS AND NUTRIENT BUDGET MODELING

EPA Science Inventory

Several quantitative methods that may be useful for lake trophic quality management planning are discussed and illustrated. An emphasis is placed on scientific methods in research, data analysis, and modeling. Proper use of statistical methods is also stressed, along with conside...

Public and patient involvement in quantitative health research: A statistical perspective.

PubMed

Hannigan, Ailish

2018-06-19

The majority of studies included in recent reviews of impact for public and patient involvement (PPI) in health research had a qualitative design. PPI in solely quantitative designs is underexplored, particularly its impact on statistical analysis. Statisticians in practice have a long history of working in both consultative (indirect) and collaborative (direct) roles in health research, yet their perspective on PPI in quantitative health research has never been explicitly examined. To explore the potential and challenges of PPI from a statistical perspective at distinct stages of quantitative research, that is sampling, measurement and statistical analysis, distinguishing between indirect and direct PPI. Statistical analysis is underpinned by having a representative sample, and a collaborative or direct approach to PPI may help achieve that by supporting access to and increasing participation of under-represented groups in the population. Acknowledging and valuing the role of lay knowledge of the context in statistical analysis and in deciding what variables to measure may support collective learning and advance scientific understanding, as evidenced by the use of participatory modelling in other disciplines. A recurring issue for quantitative researchers, which reflects quantitative sampling methods, is the selection and required number of PPI contributors, and this requires further methodological development. Direct approaches to PPI in quantitative health research may potentially increase its impact, but the facilitation and partnership skills required may require further training for all stakeholders, including statisticians. © 2018 The Authors Health Expectations published by John Wiley & Sons Ltd.

Cognition, comprehension and application of biostatistics in research by Indian postgraduate students in periodontics.

PubMed

Swetha, Jonnalagadda Laxmi; Arpita, Ramisetti; Srikanth, Chintalapani; Nutalapati, Rajasekhar

2014-01-01

Biostatistics is an integral part of research protocols. In any field of inquiry or investigation, data obtained is subsequently classified, analyzed and tested for accuracy by statistical methods. Statistical analysis of collected data, thus, forms the basis for all evidence-based conclusions. The aim of this study is to evaluate the cognition, comprehension and application of biostatistics in research among post graduate students in Periodontics, in India. A total of 391 post graduate students registered for a master's course in periodontics at various dental colleges across India were included in the survey. Data regarding the level of knowledge, understanding and its application in design and conduct of the research protocol was collected using a dichotomous questionnaire. A descriptive statistics was used for data analysis. Nearly 79.2% students were aware of the importance of biostatistics in research, 55-65% were familiar with MS-EXCEL spreadsheet for graphical representation of data and with the statistical softwares available on the internet, 26.0% had biostatistics as mandatory subject in their curriculum, 9.5% tried to perform statistical analysis on their own while 3.0% were successful in performing statistical analysis of their studies on their own. Biostatistics should play a central role in planning, conduct, interim analysis, final analysis and reporting of periodontal research especially by the postgraduate students. Indian postgraduate students in periodontics are aware of the importance of biostatistics in research but the level of understanding and application is still basic and needs to be addressed.

A Response to White and Gorard: Against Inferential Statistics: How and Why Current Statistics Teaching Gets It Wrong

ERIC Educational Resources Information Center

Nicholson, James; Ridgway, Jim

2017-01-01

White and Gorard make important and relevant criticisms of some of the methods commonly used in social science research, but go further by criticising the logical basis for inferential statistical tests. This paper comments briefly on matters we broadly agree on with them and more fully on matters where we disagree. We agree that too little…

Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results

PubMed Central

Wicherts, Jelte M.; Bakker, Marjan; Molenaar, Dylan

2011-01-01

Background The widespread reluctance to share published research data is often hypothesized to be due to the authors' fear that reanalysis may expose errors in their work or may produce conclusions that contradict their own. However, these hypotheses have not previously been studied systematically. Methods and Findings We related the reluctance to share research data for reanalysis to 1148 statistically significant results reported in 49 papers published in two major psychology journals. We found the reluctance to share data to be associated with weaker evidence (against the null hypothesis of no effect) and a higher prevalence of apparent errors in the reporting of statistical results. The unwillingness to share data was particularly clear when reporting errors had a bearing on statistical significance. Conclusions Our findings on the basis of psychological papers suggest that statistical results are particularly hard to verify when reanalysis is more likely to lead to contrasting conclusions. This highlights the importance of establishing mandatory data archiving policies. PMID:22073203

Rasch fit statistics and sample size considerations for polytomous data

PubMed Central

Smith, Adam B; Rush, Robert; Fallowfield, Lesley J; Velikova, Galina; Sharpe, Michael

2008-01-01

Background Previous research on educational data has demonstrated that Rasch fit statistics (mean squares and t-statistics) are highly susceptible to sample size variation for dichotomously scored rating data, although little is known about this relationship for polytomous data. These statistics help inform researchers about how well items fit to a unidimensional latent trait, and are an important adjunct to modern psychometrics. Given the increasing use of Rasch models in health research the purpose of this study was therefore to explore the relationship between fit statistics and sample size for polytomous data. Methods Data were collated from a heterogeneous sample of cancer patients (n = 4072) who had completed both the Patient Health Questionnaire – 9 and the Hospital Anxiety and Depression Scale. Ten samples were drawn with replacement for each of eight sample sizes (n = 25 to n = 3200). The Rating and Partial Credit Models were applied and the mean square and t-fit statistics (infit/outfit) derived for each model. Results The results demonstrated that t-statistics were highly sensitive to sample size, whereas mean square statistics remained relatively stable for polytomous data. Conclusion It was concluded that mean square statistics were relatively independent of sample size for polytomous data and that misfit to the model could be identified using published recommended ranges. PMID:18510722

Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.

PubMed

Wolfe, Katie; Dickenson, Tammiee S; Miller, Bridget; McGrath, Kathleen V

2018-04-01

A growing number of statistical analyses are being developed for single-case research. One important factor in evaluating these methods is the extent to which each corresponds to visual analysis. Few studies have compared statistical and visual analysis, and information about more recently developed statistics is scarce. Therefore, our purpose was to evaluate the agreement between visual analysis and four statistical analyses: improvement rate difference (IRD); Tau-U; Hedges, Pustejovsky, Shadish (HPS) effect size; and between-case standardized mean difference (BC-SMD). Results indicate that IRD and BC-SMD had the strongest overall agreement with visual analysis. Although Tau-U had strong agreement with visual analysis on raw values, it had poorer agreement when those values were dichotomized to represent the presence or absence of a functional relation. Overall, visual analysis appeared to be more conservative than statistical analysis, but further research is needed to evaluate the nature of these disagreements.

[A Review on the Use of Effect Size in Nursing Research].

PubMed

Kang, Hyuncheol; Yeon, Kyupil; Han, Sang Tae

2015-10-01

The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

Citation of previous meta-analyses on the same topic: a clue to perpetuation of incorrect methods?

PubMed

Li, Tianjing; Dickersin, Kay

2013-06-01

Systematic reviews and meta-analyses serve as a basis for decision-making and clinical practice guidelines and should be carried out using appropriate methodology to avoid incorrect inferences. We describe the characteristics, statistical methods used for meta-analyses, and citation patterns of all 21 glaucoma systematic reviews we identified pertaining to the effectiveness of prostaglandin analog eye drops in treating primary open-angle glaucoma, published between December 2000 and February 2012. We abstracted data, assessed whether appropriate statistical methods were applied in meta-analyses, and examined citation patterns of included reviews. We identified two forms of problematic statistical analyses in 9 of the 21 systematic reviews examined. Except in 1 case, none of the 9 reviews that used incorrect statistical methods cited a previously published review that used appropriate methods. Reviews that used incorrect methods were cited 2.6 times more often than reviews that used appropriate statistical methods. We speculate that by emulating the statistical methodology of previous systematic reviews, systematic review authors may have perpetuated incorrect approaches to meta-analysis. The use of incorrect statistical methods, perhaps through emulating methods described in previous research, calls conclusions of systematic reviews into question and may lead to inappropriate patient care. We urge systematic review authors and journal editors to seek the advice of experienced statisticians before undertaking or accepting for publication a systematic review and meta-analysis. The author(s) have no proprietary or commercial interest in any materials discussed in this article. Copyright © 2013 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

`New insight into statistical hydrology' preface to the special issue

NASA Astrophysics Data System (ADS)

Kochanek, Krzysztof

2018-04-01

Statistical methods are still the basic tool for investigating random, extreme events occurring in hydrosphere. On 21-22 September 2017, in Warsaw (Poland) the international workshop of the Statistical Hydrology (StaHy) 2017 took place under the auspices of the International Association of Hydrological Sciences. The authors of the presentations proposed to publish their research results in the Special Issue of the Acta Geophysica-`New Insight into Statistical Hydrology'. Five papers were selected for publication, touching on the most crucial issues of statistical methodology in hydrology.

Basic statistics (the fundamental concepts).

PubMed

Lim, Eric

2014-12-01

An appreciation and understanding of statistics is import to all practising clinicians, not simply researchers. This is because mathematics is the fundamental basis to which we base clinical decisions, usually with reference to the benefit in relation to risk. Unless a clinician has a basic understanding of statistics, he or she will never be in a position to question healthcare management decisions that have been handed down from generation to generation, will not be able to conduct research effectively nor evaluate the validity of published evidence (usually making an assumption that most published work is either all good or all bad). This article provides a brief introduction to basic statistical methods and illustrates its use in common clinical scenarios. In addition, pitfalls of incorrect usage have been highlighted. However, it is not meant to be a substitute for formal training or consultation with a qualified and experienced medical statistician prior to starting any research project.

A glossary for big data in population and public health: discussion and commentary on terminology and research methods.

PubMed

Fuller, Daniel; Buote, Richard; Stanley, Kevin

2017-11-01

The volume and velocity of data are growing rapidly and big data analytics are being applied to these data in many fields. Population and public health researchers may be unfamiliar with the terminology and statistical methods used in big data. This creates a barrier to the application of big data analytics. The purpose of this glossary is to define terms used in big data and big data analytics and to contextualise these terms. We define the five Vs of big data and provide definitions and distinctions for data mining, machine learning and deep learning, among other terms. We provide key distinctions between big data and statistical analysis methods applied to big data. We contextualise the glossary by providing examples where big data analysis methods have been applied to population and public health research problems and provide brief guidance on how to learn big data analysis methods. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Development of a Self-Rated Mixed Methods Skills Assessment: The National Institutes of Health Mixed Methods Research Training Program for the Health Sciences.

PubMed

Guetterman, Timothy C; Creswell, John W; Wittink, Marsha; Barg, Fran K; Castro, Felipe G; Dahlberg, Britt; Watkins, Daphne C; Deutsch, Charles; Gallo, Joseph J

2017-01-01

Demand for training in mixed methods is high, with little research on faculty development or assessment in mixed methods. We describe the development of a self-rated mixed methods skills assessment and provide validity evidence. The instrument taps six research domains: "Research question," "Design/approach," "Sampling," "Data collection," "Analysis," and "Dissemination." Respondents are asked to rate their ability to define or explain concepts of mixed methods under each domain, their ability to apply the concepts to problems, and the extent to which they need to improve. We administered the questionnaire to 145 faculty and students using an internet survey. We analyzed descriptive statistics and performance characteristics of the questionnaire using the Cronbach alpha to assess reliability and an analysis of variance that compared a mixed methods experience index with assessment scores to assess criterion relatedness. Internal consistency reliability was high for the total set of items (0.95) and adequate (≥0.71) for all but one subscale. Consistent with establishing criterion validity, respondents who had more professional experiences with mixed methods (eg, published a mixed methods article) rated themselves as more skilled, which was statistically significant across the research domains. This self-rated mixed methods assessment instrument may be a useful tool to assess skills in mixed methods for training programs. It can be applied widely at the graduate and faculty level. For the learner, assessment may lead to enhanced motivation to learn and training focused on self-identified needs. For faculty, the assessment may improve curriculum and course content planning.

Power of Statistical Tests Used to Address Nonresponse Error in the "Journal of Agricultural Education"

ERIC Educational Resources Information Center

Johnson, Donald M.; Shoulders, Catherine W.

2017-01-01

As members of a profession committed to the dissemination of rigorous research pertaining to agricultural education, authors publishing in the Journal of Agricultural Education (JAE) must seek methods to evaluate and, when necessary, improve their research methods. The purpose of this study was to describe how authors of manuscripts published in…

Integration of Marine Mammal Movement and Behavior into the Effects of Sound on the Marine Environment

DTIC Science & Technology

2011-09-30

capability to emulate the dive and movement behavior of marine mammals provides a significant advantage to modeling environmental impact than do historic...approaches used in Navy environmental assessments (EA) and impact statements (EIS). Many previous methods have been statistical or pseudo-statistical...Siderius. 2011. Comparison of methods used for computing the impact of sound on the marine environment, Marine Environmental Research, 71:342-350. [published

[Research & development on computer expert system for forensic bones estimation].

PubMed

Zhao, Jun-ji; Zhang, Jan-zheng; Liu, Nin-guo

2005-08-01

To build an expert system for forensic bones estimation. By using the object oriented method, employing statistical data of forensic anthropology, combining the statistical data frame knowledge representation with productions and also using the fuzzy matching and DS evidence theory method. Software for forensic estimation of sex, age and height with opened knowledge base was designed. This system is reliable and effective, and it would be a good assistant of the forensic technician.

Statistical process control in nursing research.

PubMed

Polit, Denise F; Chaboyer, Wendy

2012-02-01

In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected over time. SPC, like traditional statistical methods, is a tool for understanding variation and involves the construction of control charts that distinguish between normal, random fluctuations (common cause variation), and statistically significant special cause variation that can result from an innovation. The purpose of this article is to provide an overview of SPC and to illustrate its use in a study of a nursing practice improvement intervention. Copyright © 2011 Wiley Periodicals, Inc.

Transportation safety data and analysis : Volume 1, Analyzing the effectiveness of safety measures using Bayesian methods.

DOT National Transportation Integrated Search

2010-12-01

Recent research suggests that traditional safety evaluation methods may be inadequate in accurately determining the effectiveness of roadway safety measures. In recent years, advanced statistical methods are being utilized in traffic safety studies t...

Monte Carlo Simulation for Perusal and Practice.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.

The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…

Constructing Sample Space with Combinatorial Reasoning: A Mixed Methods Study

ERIC Educational Resources Information Center

McGalliard, William A., III.

2012-01-01

Recent curricular developments suggest that students at all levels need to be statistically literate and able to efficiently and accurately make probabilistic decisions. Furthermore, statistical literacy is a requirement to being a well-informed citizen of society. Research also recognizes that the ability to reason probabilistically is supported…

Statistical Significance vs. Practical Significance: An Exploration through Health Education

ERIC Educational Resources Information Center

Rosen, Brittany L.; DeMaria, Andrea L.

2012-01-01

The purpose of this paper is to examine the differences between statistical and practical significance, including strengths and criticisms of both methods, as well as provide information surrounding the application of various effect sizes and confidence intervals within health education research. Provided are recommendations, explanations and…

A Primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

Applications of statistical physics methods in economics: Current state and perspectives

NASA Astrophysics Data System (ADS)

Lux, Thomas

2016-12-01

This note discusses the development of applications of statistical physics to economics since the beginning of the `econophysics' movement about twenty years ago. I attempt to assess which of these applications appear particularly valuable and successful, and where important overlaps exist between research conducted by economist and `econophysicists'.

Statistical methodologies for tree-ring research to understand the climate-growth relationships over time and space

EPA Science Inventory

The International Tree-Ring Database is a valuable resource for studying climate change and its effects on terrestrial ecosystems over time and space. We examine the statistical methods in current use in dendroclimatology and dendroecology to process the tree-ring data and make ...

The Use of Citation Counting to Identify Research Trends

ERIC Educational Resources Information Center

Rothman, Harry; Woodhead, Michael

1971-01-01

The analysis and application of manpower statistics to identify some long-term international research trends in economic entomology and pest conrol are described. Movements in research interests, particularly towards biological methods of control, correlations between these sectors, and the difficulties encountered in the construction of a…

76 FR 67463 - Pediatric Medical Devices; Public Workshop; Request for Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-01

... use, existing scientific research data to determine pediatric effectiveness based on a similar course... research data, and C. The methods to overcome the pitfalls and data gaps, including statistical approaches... announcing a public workshop entitled ``Using Scientific Research Data to Support Pediatric Medical Device...

Basic Research in Information Science in France.

ERIC Educational Resources Information Center

Chambaud, S.; Le Coadic, Y. F.

1987-01-01

Discusses the goals of French academic research policy in the field of information science, emphasizing the interdisciplinary nature of the field. Areas of research highlighted include communication, telecommunications, co-word analysis in scientific and technical documents, media, and statistical methods for the study of social sciences. (LRW)

A Course Model for Teaching Research Evaluation in Colleges of Pharmacy.

ERIC Educational Resources Information Center

Draugalis, JoLaine R.; Slack, Marion K.

1992-01-01

A University of Arizona undergraduate pharmacy course designed to develop student skills in evaluation of research has five parts: introduction to the scientific method; statistical techniques/data analysis review; research design; fundamentals of clinical studies; and practical applications. Prerequisites include biostatistics and drug…

A guide to missing data for the pediatric nephrologist.

PubMed

Larkins, Nicholas G; Craig, Jonathan C; Teixeira-Pinto, Armando

2018-03-13

Missing data is an important and common source of bias in clinical research. Readers should be alert to and consider the impact of missing data when reading studies. Beyond preventing missing data in the first place, through good study design and conduct, there are different strategies available to handle data containing missing observations. Complete case analysis is often biased unless data are missing completely at random. Better methods of handling missing data include multiple imputation and models using likelihood-based estimation. With advancing computing power and modern statistical software, these methods are within the reach of clinician-researchers under guidance of a biostatistician. As clinicians reading papers, we need to continue to update our understanding of statistical methods, so that we understand the limitations of these techniques and can critically interpret literature.

Statistical Methods Applied to Gamma-ray Spectroscopy Algorithms in Nuclear Security Missions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fagan, Deborah K.; Robinson, Sean M.; Runkle, Robert C.

2012-10-01

In a wide range of nuclear security missions, gamma-ray spectroscopy is a critical research and development priority. One particularly relevant challenge is the interdiction of special nuclear material for which gamma-ray spectroscopy supports the goals of detecting and identifying gamma-ray sources. This manuscript examines the existing set of spectroscopy methods, attempts to categorize them by the statistical methods on which they rely, and identifies methods that have yet to be considered. Our examination shows that current methods effectively estimate the effect of counting uncertainty but in many cases do not address larger sources of decision uncertainty—ones that are significantly moremore » complex. We thus explore the premise that significantly improving algorithm performance requires greater coupling between the problem physics that drives data acquisition and statistical methods that analyze such data. Untapped statistical methods, such as Bayes Modeling Averaging and hierarchical and empirical Bayes methods have the potential to reduce decision uncertainty by more rigorously and comprehensively incorporating all sources of uncertainty. We expect that application of such methods will demonstrate progress in meeting the needs of nuclear security missions by improving on the existing numerical infrastructure for which these analyses have not been conducted.« less

The ethical dimension in published animal research in critical care: the public face of science.

PubMed

Bara, Meredith; Joffe, Ari R

2014-01-14

The ethical quality of animal research is important for many reasons, including for maintaining public support. We aimed to determine the reported attention to the ethical dimensions of the 3Rs (Refinement, Reduction, and Replacement) in critical care animal research published in 2012. A data-collection form and instruction manual were created based on published recommendations, and completed for all consecutive critical care animal research (using mammals) publications from January to June 2012 in three critical care journals. Predefined subgroups were by journal, sepsis model, and animal age, compared by using the χ2 statistic, with statistical significance accepted at P < 0.05. In total, 77 consecutive animal research publications were reviewed. Most studies did not report monitoring the level of anesthesia during invasive procedures, even when muscle paralytics were used, nor monitoring or treatment of expected pain. When euthanasia was used, the method was often not stated, and when stated, most methods were not appropriate for the species. A sample-size calculation was rarely used, and animal numbers were often poorly described. No studies performed a systematic review to ensure that the animal research would be useful and not simple repetition. Seventeen (22%) publications met the composite outcome of, if indicated, using anesthesia and pain control, and stating the method of euthanasia. Most studies were funded with public funds (foundation or government funding). Sepsis models less often met the composite outcome of, if indicated, using anesthesia and pain control, and stating the method of euthanasia (2 (7%) of 27 versus 15 (30%) of 50; P = 0.023). No other statistically significant differences were found in reporting of any criterion by animal age, sepsis model, or journal. Reported (although not necessarily actual) ethical quality of animal research in three high-impact critical care journals during 6 months of 2012 was poor. This has important implications for the practice of critical care animal research.

[Research of Odo Bujwid (1857-1942) concerning the vaccine against rabies-historical characterisation].

PubMed

Wasiewicz, Barbara

2016-01-01

The present article refers to the historical characterisation of Odo Bujwid's (1857-1942) research concerning the vaccine against rabies. The introduction refers to the treatment methods applied before Ludwik Pasteur's discovery. The following part refers to Odo Bujwid's own research including diagnostics, characterisation of the symptoms of disease, modification of the original Ludwik Pasteur's method and statistical information. The resume emphasizes that Odo Bujwid's scientific research was the introduction and generalisation the worldwide microbiology knowledge at the polish lands.

Attitude of teaching faculty towards statistics at a medical university in Karachi, Pakistan.

PubMed

Khan, Nazeer; Mumtaz, Yasmin

2009-01-01

Statistics is mainly used in biological research to verify the clinicians and researchers findings and feelings, and gives scientific validity for their inferences. In Pakistan, the educational curriculum is developed in such a way that the students who are interested in entering in the field of biological sciences do not study mathematics after grade 10. Therefore, due to their fragile background of mathematical skills, the Pakistani medical professionals feel that they do not have adequate base to understand the basic concepts of statistical techniques when they try to use it in their research or read a scientific article. The aim of the study was to assess the attitude of medical faculty towards statistics. A questionnaire containing 42 close-ended and 4 open-ended questions, related to the attitude and knowledge of statistics, was distributed among the teaching faculty of Dow University of Health Sciences (DUHS). One hundred and sixty-seven filled questionnaires were returned from 374 faculty members (response rate 44.7%). Forty-three percent of the respondents claimed that they had 'introductive' level of statistics courses, 63% of the respondents strongly agreed that a good researcher must have some training in statistics, 82% of the faculty was in favour (strongly agreed or agreed) that statistics was really useful for research. Only 17% correctly stated that statistics is the science of uncertainty. Half of the respondents accepted that they have problem of writing the statistical section of the article. 64% of the subjects indicated that statistical teaching methods were the main reasons for the impression of its difficulties. 53% of the faculty indicated that the co-authorship of the statistician should depend upon his/her contribution in the study. Gender did not show any significant difference among the responses. However, senior faculty showed higher level of the importance for the use of statistics and difficulties of writing result section of articles as compared to junior faculty. The study showed a low level of knowledge, but high level of the awareness for the use of statistical techniques in research and exhibited a good level of motivation for further training.

Small sample mediation testing: misplaced confidence in bootstrapped confidence intervals.

PubMed

Koopman, Joel; Howe, Michael; Hollenbeck, John R; Sin, Hock-Peng

2015-01-01

Bootstrapping is an analytical tool commonly used in psychology to test the statistical significance of the indirect effect in mediation models. Bootstrapping proponents have particularly advocated for its use for samples of 20-80 cases. This advocacy has been heeded, especially in the Journal of Applied Psychology, as researchers are increasingly utilizing bootstrapping to test mediation with samples in this range. We discuss reasons to be concerned with this escalation, and in a simulation study focused specifically on this range of sample sizes, we demonstrate not only that bootstrapping has insufficient statistical power to provide a rigorous hypothesis test in most conditions but also that bootstrapping has a tendency to exhibit an inflated Type I error rate. We then extend our simulations to investigate an alternative empirical resampling method as well as a Bayesian approach and demonstrate that they exhibit comparable statistical power to bootstrapping in small samples without the associated inflated Type I error. Implications for researchers testing mediation hypotheses in small samples are presented. For researchers wishing to use these methods in their own research, we have provided R syntax in the online supplemental materials. (c) 2015 APA, all rights reserved.

Modeling Psychological Contract Violation using Dual Regime Models: An Event-based Approach.

PubMed

Hofmans, Joeri

2017-01-01

A good understanding of the dynamics of psychological contract violation requires theories, research methods and statistical models that explicitly recognize that violation feelings follow from an event that violates one's acceptance limits, after which interpretative processes are set into motion, determining the intensity of these violation feelings. Whereas theories-in the form of the dynamic model of the psychological contract-and research methods-in the form of daily diary research and experience sampling research-are available by now, the statistical tools to model such a two-stage process are still lacking. The aim of the present paper is to fill this gap in the literature by introducing two statistical models-the Zero-Inflated model and the Hurdle model-that closely mimic the theoretical process underlying the elicitation violation feelings via two model components: a binary distribution that models whether violation has occurred or not, and a count distribution that models how severe the negative impact is. Moreover, covariates can be included for both model components separately, which yields insight into their unique and shared antecedents. By doing this, the present paper offers a methodological-substantive synergy, showing how sophisticated methodology can be used to examine an important substantive issue.

Statistical software applications used in health services research: analysis of published studies in the U.S

PubMed Central

2011-01-01

Background This study aims to identify the statistical software applications most commonly employed for data analysis in health services research (HSR) studies in the U.S. The study also examines the extent to which information describing the specific analytical software utilized is provided in published articles reporting on HSR studies. Methods Data were extracted from a sample of 1,139 articles (including 877 original research articles) published between 2007 and 2009 in three U.S. HSR journals, that were considered to be representative of the field based upon a set of selection criteria. Descriptive analyses were conducted to categorize patterns in statistical software usage in those articles. The data were stratified by calendar year to detect trends in software use over time. Results Only 61.0% of original research articles in prominent U.S. HSR journals identified the particular type of statistical software application used for data analysis. Stata and SAS were overwhelmingly the most commonly used software applications employed (in 46.0% and 42.6% of articles respectively). However, SAS use grew considerably during the study period compared to other applications. Stratification of the data revealed that the type of statistical software used varied considerably by whether authors were from the U.S. or from other countries. Conclusions The findings highlight a need for HSR investigators to identify more consistently the specific analytical software used in their studies. Knowing that information can be important, because different software packages might produce varying results, owing to differences in the software's underlying estimation methods. PMID:21977990

Wait Time for Treatment in Hospital Emergency Departments: 2009

MedlinePlus

... on Vital and Health Statistics Annual Reports Health Survey Research Methods Conference Reports from the National Medical Care ... SOURCE: CDC/NCHS, National Hospital Ambulatory Medical Care ... with previous research, longer wait time for treatment was associated with ...

An Intelligent Model for Pairs Trading Using Genetic Algorithms.

PubMed

Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

An Intelligent Model for Pairs Trading Using Genetic Algorithms

PubMed Central

Hsu, Chi-Jen; Chen, Chi-Chung; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice. PMID:26339236

Phase Transitions in Combinatorial Optimization Problems: Basics, Algorithms and Statistical Mechanics

NASA Astrophysics Data System (ADS)

Hartmann, Alexander K.; Weigt, Martin

2005-10-01

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field.

Applications of Operations Research Techniques in Tufts University Libraries.

ERIC Educational Resources Information Center

Rouse, William B., Ed.

This collection of papers is based on projects done in conjunction with a senior level/graduate course, "Applications of Operations Research Techniques in Systems Engineering." These seven papers describe research studies which utilized user surveys and/or statistical methods to analyze various library operations. The papers are…

Medical history and epidemiology: their contribution to the development of public health nursing.

PubMed

Earl, Catherine E

2009-01-01

The nursing profession historically has been involved in data collection in research efforts notably from the time of the Framingham Tuberculosis Project (1914-1923). Over the past century, nurses have become more sophisticated in their abilities to design, conduct, and analyze data. This article discusses the contributions of medicine and epidemiology to the development of public health nursing and the use of statistical methods by nurses in the United States in the 19th and 20th centuries. Knowledge acquired from this article will inform educators and researchers about the importance of using quantitative analysis, evidenced-based knowledge, and statistical methods when teaching students in all health professions.

Using genetic data to strengthen causal inference in observational research.

PubMed

Pingault, Jean-Baptiste; O'Reilly, Paul F; Schoeler, Tabea; Ploubidis, George B; Rijsdijk, Frühling; Dudbridge, Frank

2018-06-05

Causal inference is essential across the biomedical, behavioural and social sciences.By progressing from confounded statistical associations to evidence of causal relationships, causal inference can reveal complex pathways underlying traits and diseases and help to prioritize targets for intervention. Recent progress in genetic epidemiology - including statistical innovation, massive genotyped data sets and novel computational tools for deep data mining - has fostered the intense development of methods exploiting genetic data and relatedness to strengthen causal inference in observational research. In this Review, we describe how such genetically informed methods differ in their rationale, applicability and inherent limitations and outline how they should be integrated in the future to offer a rich causal inference toolbox.

History and Development of the Schmidt-Hunter Meta-Analysis Methods

ERIC Educational Resources Information Center

Schmidt, Frank L.

2015-01-01

In this article, I provide answers to the questions posed by Will Shadish about the history and development of the Schmidt-Hunter methods of meta-analysis. In the 1970s, I headed a research program on personnel selection at the US Office of Personnel Management (OPM). After our research showed that validity studies have low statistical power, OPM…

Reflecting on the Postgraduate Experience: Teaching Research Methods and Statistics: Review of the DART-P Sponsored Workshop at PsyPAG 2013

ERIC Educational Resources Information Center

Jackson, Emma J.; Davies, Emma. L.

2014-01-01

Following the success of last year's teaching and career development workshop, this year's DART-P sponsored workshop at the Psychology Postgraduate Affairs Group (PsyPAG) Annual Conference held at Lancaster University focused on postgraduate's experiences of teaching research methods. This article provides a review of the invited speakers…

Development of a Self-Rated Mixed Methods Skills Assessment: The NIH Mixed Methods Research Training Program for the Health Sciences

PubMed Central

Guetterman, Timothy C.; Creswell, John W.; Wittink, Marsha; Barg, Fran K.; Castro, Felipe G.; Dahlberg, Britt; Watkins, Daphne C.; Deutsch, Charles; Gallo, Joseph J.

2017-01-01

Introduction Demand for training in mixed methods is high, with little research on faculty development or assessment in mixed methods. We describe the development of a Self-Rated Mixed Methods Skills Assessment and provide validity evidence. The instrument taps six research domains: “Research question,” “Design/approach,” “Sampling,” “Data collection,” “Analysis,” and “Dissemination.” Respondents are asked to rate their ability to define or explain concepts of mixed methods under each domain, their ability to apply the concepts to problems, and the extent to which they need to improve. Methods We administered the questionnaire to 145 faculty and students using an internet survey. We analyzed descriptive statistics and performance characteristics of the questionnaire using Cronbach’s alpha to assess reliability and an ANOVA that compared a mixed methods experience index with assessment scores to assess criterion-relatedness. Results Internal consistency reliability was high for the total set of items (.95) and adequate (>=.71) for all but one subscale. Consistent with establishing criterion validity, respondents who had more professional experiences with mixed methods (e.g., published a mixed methods paper) rated themselves as more skilled, which was statistically significant across the research domains. Discussion This Self-Rated Mixed Methods Assessment instrument may be a useful tool to assess skills in mixed methods for training programs. It can be applied widely at the graduate and faculty level. For the learner, assessment may lead to enhanced motivation to learn and training focused on self-identified needs. For faculty, the assessment may improve curriculum and course content planning. PMID:28562495

Quantifying, displaying and accounting for heterogeneity in the meta-analysis of RCTs using standard and generalised Q statistics

PubMed Central

2011-01-01

Background Clinical researchers have often preferred to use a fixed effects model for the primary interpretation of a meta-analysis. Heterogeneity is usually assessed via the well known Q and I2 statistics, along with the random effects estimate they imply. In recent years, alternative methods for quantifying heterogeneity have been proposed, that are based on a 'generalised' Q statistic. Methods We review 18 IPD meta-analyses of RCTs into treatments for cancer, in order to quantify the amount of heterogeneity present and also to discuss practical methods for explaining heterogeneity. Results Differing results were obtained when the standard Q and I2 statistics were used to test for the presence of heterogeneity. The two meta-analyses with the largest amount of heterogeneity were investigated further, and on inspection the straightforward application of a random effects model was not deemed appropriate. Compared to the standard Q statistic, the generalised Q statistic provided a more accurate platform for estimating the amount of heterogeneity in the 18 meta-analyses. Conclusions Explaining heterogeneity via the pre-specification of trial subgroups, graphical diagnostic tools and sensitivity analyses produced a more desirable outcome than an automatic application of the random effects model. Generalised Q statistic methods for quantifying and adjusting for heterogeneity should be incorporated as standard into statistical software. Software is provided to help achieve this aim. PMID:21473747

Conceptual and statistical issues in couples observational research: Rationale and methods for design decisions.

PubMed

Baucom, Brian R W; Leo, Karena; Adamo, Colin; Georgiou, Panayiotis; Baucom, Katherine J W

2017-12-01

Observational behavioral coding methods are widely used for the study of relational phenomena. There are numerous guidelines for the development and implementation of these methods that include principles for creating new and adapting existing coding systems as well as principles for creating coding teams. While these principles have been successfully implemented in research on relational phenomena, the ever expanding array of phenomena being investigated with observational methods calls for a similar expansion of these principles. Specifically, guidelines are needed for decisions that arise in current areas of emphasis in couple research including observational investigation of related outcomes (e.g., relationship distress and psychological symptoms), the study of change in behavior over time, and the study of group similarities and differences in the enactment and perception of behavior. This article describes conceptual and statistical considerations involved in these 3 areas of research and presents principle- and empirically based rationale for design decisions related to these issues. A unifying principle underlying these guidelines is the need for careful consideration of fit between theory, research questions, selection of coding systems, and creation of coding teams. Implications of (mis)fit for the advancement of theory are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

[Statistical analysis of German radiologic periodicals: developmental trends in the last 10 years].

PubMed

Golder, W

1999-09-01

To identify which statistical tests are applied in German radiological publications, to what extent their use has changed during the last decade, and which factors might be responsible for this development. The major articles published in "ROFO" and "DER RADIOLOGE" during 1988, 1993 and 1998 were reviewed for statistical content. The contributions were classified by principal focus and radiological subspecialty. The methods used were assigned to descriptive, basal and advanced statistics. Sample size, significance level and power were established. The use of experts' assistance was monitored. Finally, we calculated the so-called cumulative accessibility of the publications. 525 contributions were found to be eligible. In 1988, 87% used descriptive statistics only, 12.5% basal, and 0.5% advanced statistics. The corresponding figures in 1993 and 1998 are 62 and 49%, 32 and 41%, and 6 and 10%, respectively. Statistical techniques were most likely to be used in research on musculoskeletal imaging and articles dedicated to MRI. Six basic categories of statistical methods account for the complete statistical analysis appearing in 90% of the articles. ROC analysis is the single most common advanced technique. Authors make increasingly use of statistical experts' opinion and programs. During the last decade, the use of statistical methods in German radiological journals has fundamentally improved, both quantitatively and qualitatively. Presently, advanced techniques account for 20% of the pertinent statistical tests. This development seems to be promoted by the increasing availability of statistical analysis software.

CORSSA: The Community Online Resource for Statistical Seismicity Analysis

USGS Publications Warehouse

Michael, Andrew J.; Wiemer, Stefan

2010-01-01

Statistical seismology is the application of rigorous statistical methods to earthquake science with the goal of improving our knowledge of how the earth works. Within statistical seismology there is a strong emphasis on the analysis of seismicity data in order to improve our scientific understanding of earthquakes and to improve the evaluation and testing of earthquake forecasts, earthquake early warning, and seismic hazards assessments. Given the societal importance of these applications, statistical seismology must be done well. Unfortunately, a lack of educational resources and available software tools make it difficult for students and new practitioners to learn about this discipline. The goal of the Community Online Resource for Statistical Seismicity Analysis (CORSSA) is to promote excellence in statistical seismology by providing the knowledge and resources necessary to understand and implement the best practices, so that the reader can apply these methods to their own research. This introduction describes the motivation for and vision of CORRSA. It also describes its structure and contents.

An Empirical Consideration of a Balanced Amalgamation of Learning Strategies in Graduate Introductory Statistics Classes

ERIC Educational Resources Information Center

Vaughn, Brandon K.

2009-01-01

This study considers the effectiveness of a "balanced amalgamated" approach to teaching graduate level introductory statistics. Although some research stresses replacing traditional lectures with more active learning methods, the approach of this study is to combine effective lecturing with active learning and team projects. The results of this…

Difficulties in Learning and Teaching Statistics: Teacher Views

ERIC Educational Resources Information Center

Koparan, Timur

2015-01-01

The purpose of this study is to define teacher views about the difficulties in learning and teaching middle school statistics subjects. To serve this aim, a number of interviews were conducted with 10 middle school maths teachers in 2011-2012 school year in the province of Trabzon. Of the qualitative descriptive research methods, the…

A Computer-Assisted Instruction in Teaching Abstract Statistics to Public Affairs Undergraduates

ERIC Educational Resources Information Center

Ozturk, Ali Osman

2012-01-01

This article attempts to demonstrate the applicability of a computer-assisted instruction supported with simulated data in teaching abstract statistical concepts to political science and public affairs students in an introductory research methods course. The software is called the Elaboration Model Computer Exercise (EMCE) in that it takes a great…

Virginia ridesharing statistics : methodologies for determining carpooler and vanpool average life bases and the average fuel economy of commuter vehicles.

DOT National Transportation Integrated Search

1985-01-01

The objective of this research was to investigate methods of computing average life values for carpoolers and vanpools in Virginia. These statistics are to be used by the Rail and Public Transportation Division in evaluating the efficiency and cost-e...

Cluster size statistic and cluster mass statistic: two novel methods for identifying changes in functional connectivity between groups or conditions.

PubMed

Ing, Alex; Schwarzbauer, Christian

2014-01-01

Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.

Cluster Size Statistic and Cluster Mass Statistic: Two Novel Methods for Identifying Changes in Functional Connectivity Between Groups or Conditions

PubMed Central

Ing, Alex; Schwarzbauer, Christian

2014-01-01

Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods – the cluster size statistic (CSS) and cluster mass statistic (CMS) – are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity. PMID:24906136

Data Model Performance in Data Warehousing

NASA Astrophysics Data System (ADS)

Rorimpandey, G. C.; Sangkop, F. I.; Rantung, V. P.; Zwart, J. P.; Liando, O. E. S.; Mewengkang, A.

2018-02-01

Data Warehouses have increasingly become important in organizations that have large amount of data. It is not a product but a part of a solution for the decision support system in those organizations. Data model is the starting point for designing and developing of data warehouses architectures. Thus, the data model needs stable interfaces and consistent for a longer period of time. The aim of this research is to know which data model in data warehousing has the best performance. The research method is descriptive analysis, which has 3 main tasks, such as data collection and organization, analysis of data and interpretation of data. The result of this research is discussed in a statistic analysis method, represents that there is no statistical difference among data models used in data warehousing. The organization can utilize four data model proposed when designing and developing data warehouse.

Assessing the Development of Educational Research Literacy: The Effect of Courses on Research Methods in Studies of Educational Science

ERIC Educational Resources Information Center

Groß Ophoff, Jana; Schladitz, Sandra; Leuders, Juliane; Leuders, Timo; Wirtz, Markus A.

2015-01-01

The ability to purposefully access, reflect, and use evidence from educational research (Educational Research Literacy) is expected of future professionals in educational practice. Based on the presented conceptual framework, a test instrument was developed to assess the different competency aspects: Information Literacy, Statistical Literacy, and…

Bridging the Gap: Cognitive and Social Approaches to Research in Second Language Learning and Teaching

ERIC Educational Resources Information Center

Hulstijn, Jan H.; Young, Richard F.; Ortega, Lourdes; Bigelow, Martha; DeKeyser, Robert; Ellis, Nick C.; Lantolf, James P.; Mackey, Alison; Talmy, Steven

2014-01-01

For some, research in learning and teaching of a second language (L2) runs the risk of disintegrating into irreconcilable approaches to L2 learning and use. On the one side, we find researchers investigating linguistic-cognitive issues, often using quantitative research methods including inferential statistics; on the other side, we find…

[Effect sizes, statistical power and sample sizes in "the Japanese Journal of Psychology"].

PubMed

Suzukawa, Yumi; Toyoda, Hideki

2012-04-01

This study analyzed the statistical power of research studies published in the "Japanese Journal of Psychology" in 2008 and 2009. Sample effect sizes and sample statistical powers were calculated for each statistical test and analyzed with respect to the analytical methods and the fields of the studies. The results show that in the fields like perception, cognition or learning, the effect sizes were relatively large, although the sample sizes were small. At the same time, because of the small sample sizes, some meaningful effects could not be detected. In the other fields, because of the large sample sizes, meaningless effects could be detected. This implies that researchers who could not get large enough effect sizes would use larger samples to obtain significant results.

The changing landscape of astrostatistics and astroinformatics

NASA Astrophysics Data System (ADS)

Feigelson, Eric D.

2017-06-01

The history and current status of the cross-disciplinary fields of astrostatistics and astroinformatics are reviewed. Astronomers need a wide range of statistical methods for both data reduction and science analysis. With the proliferation of high-throughput telescopes, efficient large scale computational methods are also becoming essential. However, astronomers receive only weak training in these fields during their formal education. Interest in the fields is rapidly growing with conferences organized by scholarly societies, textbooks and tutorial workshops, and research studies pushing the frontiers of methodology. R, the premier language of statistical computing, can provide an important software environment for the incorporation of advanced statistical and computational methodology into the astronomical community.

Embedding Evidence-based Practice Education into a Post-graduate Physiotherapy Program: Eight Years of pre-Post Course Evaluations.

PubMed

Perraton, L; Machotka, Z; Grimmer, K; Gibbs, C; Mahar, C; Kennedy, K

2017-04-01

Little has been published about the effectiveness of training postgraduate physiotherapy coursework students in research methods and evidence-based practice (EBP) theory. Graduate qualities in most universities include lifelong learning. Inclusion of EBP in post-graduate coursework students' training is one way for students to develop the knowledge and skills needed to implement current best evidence in their clinical practice after graduation, thereby facilitating lifelong learning. This paper reports on change in confidence and anxiety in knowledge of statistical terminology and concepts related to research design and EBP in eight consecutive years of post-graduate physiotherapy students at one Australian university. Pre-survey/post-survey instruments were administered to students in an intensive 3-week post-graduate course, which taught health research methods, biostatistics and EBP. This course was embedded into a post-graduate physiotherapy programme from 2007 to 2014. The organization and delivery of the course was based on best pedagogical evidence for effectively teaching adult physiotherapists. The course was first delivered each year in the programme, and no other course was delivered concurrently. There were significant improvements in confidence, significantly decreased anxiety and improvements in knowledge of statistical terminology and concepts related to research design and EBP, at course completion. Age, gender and country of origin were not confounders on learning outcomes, although there was a (non-significant) trend that years of practice negatively impacted on learning outcomes (p = 0.09). There was a greater improvement in confidence in statistical terminology than in concepts related to research design and EBP. An intensive teaching programme in health research methods and biostatistics and EBP, based on best practice adult physiotherapy learning principles, is effective immediately post-course, in decreasing anxiety and increasing confidence in the terminology used in research methods and EBP. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Preparing for the first meeting with a statistician.

PubMed

De Muth, James E

2008-12-15

Practical statistical issues that should be considered when performing data collection and analysis are reviewed. The meeting with a statistician should take place early in the research development before any study data are collected. The process of statistical analysis involves establishing the research question, formulating a hypothesis, selecting an appropriate test, sampling correctly, collecting data, performing tests, and making decisions. Once the objectives are established, the researcher can determine the characteristics or demographics of the individuals required for the study, how to recruit volunteers, what type of data are needed to answer the research question(s), and the best methods for collecting the required information. There are two general types of statistics: descriptive and inferential. Presenting data in a more palatable format for the reader is called descriptive statistics. Inferential statistics involve making an inference or decision about a population based on results obtained from a sample of that population. In order for the results of a statistical test to be valid, the sample should be representative of the population from which it is drawn. When collecting information about volunteers, researchers should only collect information that is directly related to the study objectives. Important information that a statistician will require first is an understanding of the type of variables involved in the study and which variables can be controlled by researchers and which are beyond their control. Data can be presented in one of four different measurement scales: nominal, ordinal, interval, or ratio. Hypothesis testing involves two mutually exclusive and exhaustive statements related to the research question. Statisticians should not be replaced by computer software, and they should be consulted before any research data are collected. When preparing to meet with a statistician, the pharmacist researcher should be familiar with the steps of statistical analysis and consider several questions related to the study to be conducted.

Geomatic Methods for the Analysis of Data in the Earth Sciences: Lecture Notes in Earth Sciences, Vol. 95

NASA Astrophysics Data System (ADS)

Pavlis, Nikolaos K.

Geomatics is a trendy term that has been used in recent years to describe academic departments that teach and research theories, methods, algorithms, and practices used in processing and analyzing data related to the Earth and other planets. Naming trends aside, geomatics could be considered as the mathematical and statistical “toolbox” that allows Earth scientists to extract information about physically relevant parameters from the available data and accompany such information with some measure of its reliability. This book is an attempt to present the mathematical-statistical methods used in data analysis within various disciplines—geodesy, geophysics, photogrammetry and remote sensing—from a unifying perspective that inverse problem formalism permits. At the same time, it allows us to stretch the relevance of statistical methods in achieving an optimal solution.

Statistical loads data for Boeing 737-400 aircraft in commercial operations

DOT National Transportation Integrated Search

1998-08-01

The primary objective of this research is to support the FAA Airborne Data Monitoring Systems Research Program by developing new and improved methods and criteria for processing and presenting large commercial transport airplane flight and ground loa...

Statistical loads data for BE-1900D aircraft in commuter operations

DOT National Transportation Integrated Search

2000-04-01

The primary objective of this research is to support the FAA Airborne Data Monitoring Systems Research Program by developing new and improved methods and criteria for processing and presenting commuter airplane flight and ground loads usage data. The...

Translational Research for Occupational Therapy: Using SPRE in Hippotherapy for Children with Developmental Disabilities.

PubMed

Weissman-Miller, Deborah; Miller, Rosalie J; Shotwell, Mary P

2017-01-01

Translational research is redefined in this paper using a combination of methods in statistics and data science to enhance the understanding of outcomes and practice in occupational therapy. These new methods are applied, using larger data and smaller single-subject data, to a study in hippotherapy for children with developmental disabilities (DD). The Centers for Disease Control and Prevention estimates DD affects nearly 10 million children, aged 2-19, where diagnoses may be comorbid. Hippotherapy is defined here as a treatment strategy in occupational therapy using equine movement to achieve functional outcomes. Semiparametric ratio estimator (SPRE), a single-subject statistical and small data science model, is used to derive a "change point" indicating where the participant adapts to treatment, from which predictions are made. Data analyzed here is from an institutional review board approved pilot study using the Hippotherapy Evaluation and Assessment Tool measure, where outcomes are given separately for each of four measured domains and the total scores of each participant. Analysis with SPRE, using statistical methods to predict a "change point" and data science graphical interpretations of data, shows the translational comparisons between results from larger mean values and the very different results from smaller values for each HEAT domain in terms of relationships and statistical probabilities.

Translational Research for Occupational Therapy: Using SPRE in Hippotherapy for Children with Developmental Disabilities

PubMed Central

Miller, Rosalie J.; Shotwell, Mary P.

2017-01-01

Translational research is redefined in this paper using a combination of methods in statistics and data science to enhance the understanding of outcomes and practice in occupational therapy. These new methods are applied, using larger data and smaller single-subject data, to a study in hippotherapy for children with developmental disabilities (DD). The Centers for Disease Control and Prevention estimates DD affects nearly 10 million children, aged 2–19, where diagnoses may be comorbid. Hippotherapy is defined here as a treatment strategy in occupational therapy using equine movement to achieve functional outcomes. Semiparametric ratio estimator (SPRE), a single-subject statistical and small data science model, is used to derive a “change point” indicating where the participant adapts to treatment, from which predictions are made. Data analyzed here is from an institutional review board approved pilot study using the Hippotherapy Evaluation and Assessment Tool measure, where outcomes are given separately for each of four measured domains and the total scores of each participant. Analysis with SPRE, using statistical methods to predict a “change point” and data science graphical interpretations of data, shows the translational comparisons between results from larger mean values and the very different results from smaller values for each HEAT domain in terms of relationships and statistical probabilities. PMID:29097962

Statistical testing of association between menstruation and migraine.

PubMed

Barra, Mathias; Dahl, Fredrik A; Vetvik, Kjersti G

2015-02-01

To repair and refine a previously proposed method for statistical analysis of association between migraine and menstruation. Menstrually related migraine (MRM) affects about 20% of female migraineurs in the general population. The exact pathophysiological link from menstruation to migraine is hypothesized to be through fluctuations in female reproductive hormones, but the exact mechanisms remain unknown. Therefore, the main diagnostic criterion today is concurrency of migraine attacks with menstruation. Methods aiming to exclude spurious associations are wanted, so that further research into these mechanisms can be performed on a population with a true association. The statistical method is based on a simple two-parameter null model of MRM (which allows for simulation modeling), and Fisher's exact test (with mid-p correction) applied to standard 2 × 2 contingency tables derived from the patients' headache diaries. Our method is a corrected version of a previously published flawed framework. To our best knowledge, no other published methods for establishing a menstruation-migraine association by statistical means exist today. The probabilistic methodology shows good performance when subjected to receiver operator characteristic curve analysis. Quick reference cutoff values for the clinical setting were tabulated for assessing association given a patient's headache history. In this paper, we correct a proposed method for establishing association between menstruation and migraine by statistical methods. We conclude that the proposed standard of 3-cycle observations prior to setting an MRM diagnosis should be extended with at least one perimenstrual window to obtain sufficient information for statistical processing. © 2014 American Headache Society.

Directions for new developments on statistical design and analysis of small population group trials.

PubMed

Hilgers, Ralf-Dieter; Roes, Kit; Stallard, Nigel

2016-06-14

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions. Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible. The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations. The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

Objective forensic analysis of striated, quasi-striated and impressed toolmarks

NASA Astrophysics Data System (ADS)

Spotts, Ryan E.

Following the 1993 Daubert v. Merrell Dow Pharmaceuticals, Inc. court case and continuing to the 2010 National Academy of Sciences report, comparative forensic toolmark examination has received many challenges to its admissibility in court cases and its scientific foundations. Many of these challenges deal with the subjective nature in determining whether toolmarks are identifiable. This questioning of current identification methods has created a demand for objective methods of identification - "objective" implying known error rates and statistically reliability. The demand for objective methods has resulted in research that created a statistical algorithm capable of comparing toolmarks to determine their statistical similarity, and thus the ability to separate matching and nonmatching toolmarks. This was expanded to the creation of virtual toolmarking (characterization of a tool to predict the toolmark it will create). The statistical algorithm, originally designed for two-dimensional striated toolmarks, had been successfully applied to striated screwdriver and quasi-striated plier toolmarks. Following this success, a blind study was conducted to validate the virtual toolmarking capability using striated screwdriver marks created at various angles of incidence. Work was also performed to optimize the statistical algorithm by implementing means to ensure the algorithm operations were constrained to logical comparison regions (e.g. the opposite ends of two toolmarks do not need to be compared because they do not coincide with each other). This work was performed on quasi-striated shear cut marks made with pliers - a previously tested, more difficult application of the statistical algorithm that could demonstrate the difference in results due to optimization. The final research conducted was performed with pseudostriated impression toolmarks made with chisels. Impression marks, which are more complex than striated marks, were analyzed using the algorithm to separate matching and nonmatching toolmarks. Results of the conducted research are presented as well as evidence of the primary assumption of forensic toolmark examination; all tools can create identifiably unique toolmarks.

A spatial scan statistic for compound Poisson data.

PubMed

Rosychuk, Rhonda J; Chang, Hsing-Ming

2013-12-20

The topic of spatial cluster detection gained attention in statistics during the late 1980s and early 1990s. Effort has been devoted to the development of methods for detecting spatial clustering of cases and events in the biological sciences, astronomy and epidemiology. More recently, research has examined detecting clusters of correlated count data associated with health conditions of individuals. Such a method allows researchers to examine spatial relationships of disease-related events rather than just incident or prevalent cases. We introduce a spatial scan test that identifies clusters of events in a study region. Because an individual case may have multiple (repeated) events, we base the test on a compound Poisson model. We illustrate our method for cluster detection on emergency department visits, where individuals may make multiple disease-related visits. Copyright © 2013 John Wiley & Sons, Ltd.

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

NASA Astrophysics Data System (ADS)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

The Legacy of Florence Nightingale's Environmental Theory: Nursing Research Focusing on the Impact of Healthcare Environments.

PubMed

Zborowsky, Terri

2014-01-01

The purpose of this paper is to explore nursing research that is focused on the impact of healthcare environments and that has resonance with the aspects of Florence Nightingale's environmental theory. Nurses have a unique ability to apply their observational skills to understand the role of the designed environment to enable healing in their patients. This affords nurses the opportunity to engage in research studies that have immediate impact on the act of nursing. Descriptive statistics were performed on 67 healthcare design-related research articles from 25 nursing journals to discover the topical areas of interest of nursing research today. Data were also analyzed to reveal the research designs, research methods, and research settings. These data are part of an ongoing study. Descriptive statistics reveal that topics and settings most frequently cited are in keeping with the current healthcare foci of patient care quality and safety in acute and intensive care environments. Research designs and methods most frequently cited are in keeping with the early progression of a knowledge area. A few assertions can be made as a result of this study. First, education is important to continue the knowledge development in this area. Second, multiple method research studies should continue to be considered as important to healthcare research. Finally, bedside nurses are in the best position possible to begin to help us all, through research, understand how the design environment impacts patients during the act of nursing. Evidence-based design, literature review, nursing.

A review of downscaling procedures - a contribution to the research on climate change impacts at city scale

NASA Astrophysics Data System (ADS)

Smid, Marek; Costa, Ana; Pebesma, Edzer; Granell, Carlos; Bhattacharya, Devanjan

2016-04-01

Human kind is currently predominantly urban based, and the majority of ever continuing population growth will take place in urban agglomerations. Urban systems are not only major drivers of climate change, but also the impact hot spots. Furthermore, climate change impacts are commonly managed at city scale. Therefore, assessing climate change impacts on urban systems is a very relevant subject of research. Climate and its impacts on all levels (local, meso and global scale) and also the inter-scale dependencies of those processes should be a subject to detail analysis. While global and regional projections of future climate are currently available, local-scale information is lacking. Hence, statistical downscaling methodologies represent a potentially efficient way to help to close this gap. In general, the methodological reviews of downscaling procedures cover the various methods according to their application (e.g. downscaling for the hydrological modelling). Some of the most recent and comprehensive studies, such as the ESSEM COST Action ES1102 (VALUE), use the concept of Perfect Prog and MOS. Other examples of classification schemes of downscaling techniques consider three main categories: linear methods, weather classifications and weather generators. Downscaling and climate modelling represent a multidisciplinary field, where researchers from various backgrounds intersect their efforts, resulting in specific terminology, which may be somewhat confusing. For instance, the Polynomial Regression (also called the Surface Trend Analysis) is a statistical technique. In the context of the spatial interpolation procedures, it is commonly classified as a deterministic technique, and kriging approaches are classified as stochastic. Furthermore, the terms "statistical" and "stochastic" (frequently used as names of sub-classes in downscaling methodological reviews) are not always considered as synonymous, even though both terms could be seen as identical since they are referring to methods handling input modelling factors as variables with certain probability distributions. In addition, the recent development is going towards multi-step methodologies containing deterministic and stochastic components. This evolution leads to the introduction of new terms like hybrid or semi-stochastic approaches, which makes the efforts to systematically classifying downscaling methods to the previously defined categories even more challenging. This work presents a review of statistical downscaling procedures, which classifies the methods in two steps. In the first step, we describe several techniques that produce a single climatic surface based on observations. The methods are classified into two categories using an approximation to the broadest consensual statistical terms: linear and non-linear methods. The second step covers techniques that use simulations to generate alternative surfaces, which correspond to different realizations of the same processes. Those simulations are essential because there is a limited number of real observational data, and such procedures are crucial for modelling extremes. This work emphasises the link between statistical downscaling methods and the research of climate change impacts at city scale.

Statistical relationships between journal use and research output at academic institutions in South Korea.

PubMed

Jung, Youngim; Kim, Jayhoon; So, Minho; Kim, Hwanmin

In this study, we analysed the statistical association between e-journal use and research output at the institution level in South Korea by performing comparative and diachronic analyses, as well as the analysis by field. The datasets were compiled from four different sources: national reports on research output indicators in science fields, two statistics databases on higher education institutions open to the public, and e-journal usage statistics generated by 47 major publishers. Due to the different data sources utilized, a considerable number of missing values appeared in our datasets and various mapping issues required corrections prior to the analysis. Two techniques for handling missing data were applied and the impact of each technique was discussed. In order to compile the institutional data by field, journals were first mapped, and then the statistics were summarized according to subject field. We observed that e-journal use exhibited stronger correlations with the number of publications and the times cited, in contrast to the number of undergraduates, graduates, faculty members and the amount of research funds, and this was the case regardless of the NA handling method or author type. The difference between the maximum correlation for the amount of external research funding with two average indicators and that of the correlation for e-journal use were not significant. Statistically, the accountability of e-journal use for the average times cited per article and the average JIF was quite similar with external research funds. It was found that the number of e-journal articles used had a strong positive correlation (Pearson's correlation coefficients of r  > 0.9, p  < 0.05) with the number of articles published in SCI(E) journals and the times cited regardless of the author type, NA handling method or time period. We also observed that the top-five institutions in South Korea, with respect to the number of publications in SCI(E) journals, were generally across a balanced range of academic activities, while producing significant research output and using published material. Finally, we confirmed that the association of e-journal use with the two quantitative research indicators is strongly positive, even for the analyses by field, with the exception of the Arts and Humanities.

Specialized Finite Set Statistics (FISST)-Based Estimation Methods to Enhance Space Situational Awareness in Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO)

DTIC Science & Technology

2016-08-17

Research Laboratory AFRL /RVSV Space Vehicles Directorate 3550 Aberdeen Ave, SE 11. SPONSOR/MONITOR’S REPORT Kirtland AFB, NM 87117-5776 NUMBER(S) AFRL -RV...1 cy AFRL /RVIL Kirtland AFB, NM 87117-5776 2 cys Official Record Copy AFRL /RVSV/Richard S. Erwin 1 cy... AFRL -RV-PS- AFRL -RV-PS- TR-2016-0114 TR-2016-0114 SPECIALIZED FINITE SET STATISTICS (FISST)- BASED ESTIMATION METHODS TO ENHANCE SPACE SITUATIONAL

Methodological reporting in qualitative, quantitative, and mixed methods health services research articles.

PubMed

Wisdom, Jennifer P; Cavaleri, Mary A; Onwuegbuzie, Anthony J; Green, Carla A

2012-04-01

Methodologically sound mixed methods research can improve our understanding of health services by providing a more comprehensive picture of health services than either method can alone. This study describes the frequency of mixed methods in published health services research and compares the presence of methodological components indicative of rigorous approaches across mixed methods, qualitative, and quantitative articles. All empirical articles (n = 1,651) published between 2003 and 2007 from four top-ranked health services journals. All mixed methods articles (n = 47) and random samples of qualitative and quantitative articles were evaluated to identify reporting of key components indicating rigor for each method, based on accepted standards for evaluating the quality of research reports (e.g., use of p-values in quantitative reports, description of context in qualitative reports, and integration in mixed method reports). We used chi-square tests to evaluate differences between article types for each component. Mixed methods articles comprised 2.85 percent (n = 47) of empirical articles, quantitative articles 90.98 percent (n = 1,502), and qualitative articles 6.18 percent (n = 102). There was a statistically significant difference (χ(2) (1) = 12.20, p = .0005, Cramer's V = 0.09, odds ratio = 1.49 [95% confidence interval = 1,27, 1.74]) in the proportion of quantitative methodological components present in mixed methods compared to quantitative papers (21.94 versus 47.07 percent, respectively) but no statistically significant difference (χ(2) (1) = 0.02, p = .89, Cramer's V = 0.01) in the proportion of qualitative methodological components in mixed methods compared to qualitative papers (21.34 versus 25.47 percent, respectively). Few published health services research articles use mixed methods. The frequency of key methodological components is variable. Suggestions are provided to increase the transparency of mixed methods studies and the presence of key methodological components in published reports. © Health Research and Educational Trust.

Using DIF Dissection Method to Assess Effects of Item Deletion. Research Report No. 2005-10. ETS RR-05-23

ERIC Educational Resources Information Center

Zhang, Yanling; Dorans, Neil J.; Matthews-López, Joy L.

2005-01-01

Statistical procedures for detecting differential item functioning (DIF) are often used as an initial step to screen items for construct irrelevant variance. This research applies a DIF dissection method and a two-way classification scheme to SAT Reasoning Test™ verbal section data and explores the effects of deleting sizable DIF items on reported…

Experiencing the Research Process in a Single Class Period

ERIC Educational Resources Information Center

Cook, Kathleen E.

2008-01-01

Books and courses on research methods, statistics, or both, often necessarily focus on one topic at a time. This compartmentalized approach prevents students from seeing the big picture. To address this shortcoming, I developed an exercise through which students experience the whole research process in a single class period. From posing a…

Binary recursive partitioning: background, methods, and application to psychology.

PubMed

Merkle, Edgar C; Shaffer, Victoria A

2011-02-01

Binary recursive partitioning (BRP) is a computationally intensive statistical method that can be used in situations where linear models are often used. Instead of imposing many assumptions to arrive at a tractable statistical model, BRP simply seeks to accurately predict a response variable based on values of predictor variables. The method outputs a decision tree depicting the predictor variables that were related to the response variable, along with the nature of the variables' relationships. No significance tests are involved, and the tree's 'goodness' is judged based on its predictive accuracy. In this paper, we describe BRP methods in a detailed manner and illustrate their use in psychological research. We also provide R code for carrying out the methods.

Geospatial methods and data analysis for assessing distribution of grazing livestock

USDA-ARS?s Scientific Manuscript database

Free-ranging livestock research must begin with a well conceived problem statement and employ appropriate data acquisition tools and analytical techniques to accomplish the research objective. These requirements are especially critical in addressing animal distribution. Tools and statistics used t...

Statistical Considerations of Food Allergy Prevention Studies.

PubMed

Bahnson, Henry T; du Toit, George; Lack, Gideon

Clinical studies to prevent the development of food allergy have recently helped reshape public policy recommendations on the early introduction of allergenic foods. These trials are also prompting new research, and it is therefore important to address the unique design and analysis challenges of prevention trials. We highlight statistical concepts and give recommendations that clinical researchers may wish to adopt when designing future study protocols and analysis plans for prevention studies. Topics include selecting a study sample, addressing internal and external validity, improving statistical power, choosing alpha and beta, analysis innovations to address dilution effects, and analysis methods to deal with poor compliance, dropout, and missing data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies.

PubMed

Shardell, Michelle; Harris, Anthony D; El-Kamary, Samer S; Furuno, Jon P; Miller, Ram R; Perencevich, Eli N

2007-10-01

Quasi-experimental study designs are frequently used to assess interventions that aim to limit the emergence of antimicrobial-resistant pathogens. However, previous studies using these designs have often used suboptimal statistical methods, which may result in researchers making spurious conclusions. Methods used to analyze quasi-experimental data include 2-group tests, regression analysis, and time-series analysis, and they all have specific assumptions, data requirements, strengths, and limitations. An example of a hospital-based intervention to reduce methicillin-resistant Staphylococcus aureus infection rates and reduce overall length of stay is used to explore these methods.

Quantitative naturalistic methods for detecting change points in psychotherapy research: an illustration with alliance ruptures.

PubMed

Eubanks-Carter, Catherine; Gorman, Bernard S; Muran, J Christopher

2012-01-01

Analysis of change points in psychotherapy process could increase our understanding of mechanisms of change. In particular, naturalistic change point detection methods that identify turning points or breakpoints in time series data could enhance our ability to identify and study alliance ruptures and resolutions. This paper presents four categories of statistical methods for detecting change points in psychotherapy process: criterion-based methods, control chart methods, partitioning methods, and regression methods. Each method's utility for identifying shifts in the alliance is illustrated using a case example from the Beth Israel Psychotherapy Research program. Advantages and disadvantages of the various methods are discussed.

Review of research designs and statistical methods employed in dental postgraduate dissertations.

PubMed

Shirahatti, Ravi V; Hegde-Shetiya, Sahana

2015-01-01

There is a need to evaluate the quality of postgraduate dissertations of dentistry submitted to university in the light of the international standards of reporting. We conducted the review with an objective to document the use of sampling methods, measurement standardization, blinding, methods to eliminate bias, appropriate use of statistical tests, appropriate use of data presentation in postgraduate dental research and suggest and recommend modifications. The public access database of the dissertations from Rajiv Gandhi University of Health Sciences was reviewed. Three hundred and thirty-three eligible dissertations underwent preliminary evaluation followed by detailed evaluation of 10% of randomly selected dissertations. The dissertations were assessed based on international reporting guidelines such as strengthening the reporting of observational studies in epidemiology (STROBE), consolidated standards of reporting trials (CONSORT), and other scholarly resources. The data were compiled using MS Excel and SPSS 10.0. Numbers and percentages were used for describing the data. The "in vitro" studies were the most common type of research (39%), followed by observational (32%) and experimental studies (29%). The disciplines conservative dentistry (92%) and prosthodontics (75%) reported high numbers of in vitro research. Disciplines oral surgery (80%) and periodontics (67%) had conducted experimental studies as a major share of their research. Lacunae in the studies included observational studies not following random sampling (70%), experimental studies not following random allocation (75%), not mentioning about blinding, confounding variables and calibrations in measurements, misrepresenting the data by inappropriate data presentation, errors in reporting probability values and not reporting confidence intervals. Few studies showed grossly inappropriate choice of statistical tests and many studies needed additional tests. Overall observations indicated the need to comply with standard guidelines of reporting research.

VALUE - Validating and Integrating Downscaling Methods for Climate Change Research

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Benestad, Rasmus; Kotlarski, Sven; Huth, Radan; Hertig, Elke; Wibig, Joanna; Gutierrez, Jose

2013-04-01

Our understanding of global climate change is mainly based on General Circulation Models (GCMs) with a relatively coarse resolution. Since climate change impacts are mainly experienced on regional scales, high-resolution climate change scenarios need to be derived from GCM simulations by downscaling. Several projects have been carried out over the last years to validate the performance of statistical and dynamical downscaling, yet several aspects have not been systematically addressed: variability on sub-daily, decadal and longer time-scales, extreme events, spatial variability and inter-variable relationships. Different downscaling approaches such as dynamical downscaling, statistical downscaling and bias correction approaches have not been systematically compared. Furthermore, collaboration between different communities, in particular regional climate modellers, statistical downscalers and statisticians has been limited. To address these gaps, the EU Cooperation in Science and Technology (COST) action VALUE (www.value-cost.eu) has been brought into life. VALUE is a research network with participants from currently 23 European countries running from 2012 to 2015. Its main aim is to systematically validate and develop downscaling methods for climate change research in order to improve regional climate change scenarios for use in climate impact studies. Inspired by the co-design idea of the international research initiative "future earth", stakeholders of climate change information have been involved in the definition of research questions to be addressed and are actively participating in the network. The key idea of VALUE is to identify the relevant weather and climate characteristics required as input for a wide range of impact models and to define an open framework to systematically validate these characteristics. Based on a range of benchmark data sets, in principle every downscaling method can be validated and compared with competing methods. The results of this exercise will directly provide end users with important information about the uncertainty of regional climate scenarios, and will furthermore provide the basis for further developing downscaling methods. This presentation will provide background information on VALUE and discuss the identified characteristics and the validation framework.

Critical appraisal of fundamental items in approved clinical trial research proposals in Mashhad University of Medical Sciences

PubMed Central

Shakeri, Mohammad-Taghi; Taghipour, Ali; Sadeghi, Masoumeh; Nezami, Hossein; Amirabadizadeh, Ali-Reza; Bonakchi, Hossein

2017-01-01

Background: Writing, designing, and conducting a clinical trial research proposal has an important role in achieving valid and reliable findings. Thus, this study aimed at critically appraising fundamental information in approved clinical trial research proposals in Mashhad University of Medical Sciences (MUMS) from 2008 to 2014. Methods: This cross-sectional study was conducted on all 935 approved clinical trial research proposals in MUMS from 2008 to 2014. A valid and reliable as well as comprehensive, simple, and usable checklist in sessions with biostatisticians and methodologists, consisting of 11 main items as research tool, were used. Agreement rate between the reviewers of the proposals, who were responsible for data collection, was assessed during 3 sessions, and Kappa statistics was calculated at the last session as 97%. Results: More than 60% of the research proposals had a methodologist consultant, moreover, type of study or study design had been specified in almost all of them (98%). Appropriateness of study aims with hypotheses was not observed in a significant number of research proposals (585 proposals, 62.6%). The required sample size for 66.8% of the approved proposals was based on a sample size formula; however, in 25% of the proposals, sample size formula was not in accordance with the study design. Data collection tool was not selected appropriately in 55.2% of the approved research proposals. Type and method of randomization were unknown in 21% of the proposals and dealing with missing data had not been described in most of them (98%). Inclusion and exclusion criteria were (92%) fully and adequately explained. Moreover, 44% and 31% of the research proposals were moderate and weak in rank, respectively, with respect to the correctness of the statistical analysis methods. Conclusion: Findings of the present study revealed that a large portion of the approved proposals were highly biased or ambiguous with respect to randomization, blinding, dealing with missing data, data collection tool, sampling methods, and statistical analysis. Thus, it is essential to consult and collaborate with a methodologist in all parts of a proposal to control the possible and specific biases in clinical trials. PMID:29445703

Critical appraisal of fundamental items in approved clinical trial research proposals in Mashhad University of Medical Sciences.

PubMed

Shakeri, Mohammad-Taghi; Taghipour, Ali; Sadeghi, Masoumeh; Nezami, Hossein; Amirabadizadeh, Ali-Reza; Bonakchi, Hossein

2017-01-01

Background: Writing, designing, and conducting a clinical trial research proposal has an important role in achieving valid and reliable findings. Thus, this study aimed at critically appraising fundamental information in approved clinical trial research proposals in Mashhad University of Medical Sciences (MUMS) from 2008 to 2014. Methods: This cross-sectional study was conducted on all 935 approved clinical trial research proposals in MUMS from 2008 to 2014. A valid and reliable as well as comprehensive, simple, and usable checklist in sessions with biostatisticians and methodologists, consisting of 11 main items as research tool, were used. Agreement rate between the reviewers of the proposals, who were responsible for data collection, was assessed during 3 sessions, and Kappa statistics was calculated at the last session as 97%. Results: More than 60% of the research proposals had a methodologist consultant, moreover, type of study or study design had been specified in almost all of them (98%). Appropriateness of study aims with hypotheses was not observed in a significant number of research proposals (585 proposals, 62.6%). The required sample size for 66.8% of the approved proposals was based on a sample size formula; however, in 25% of the proposals, sample size formula was not in accordance with the study design. Data collection tool was not selected appropriately in 55.2% of the approved research proposals. Type and method of randomization were unknown in 21% of the proposals and dealing with missing data had not been described in most of them (98%). Inclusion and exclusion criteria were (92%) fully and adequately explained. Moreover, 44% and 31% of the research proposals were moderate and weak in rank, respectively, with respect to the correctness of the statistical analysis methods. Conclusion: Findings of the present study revealed that a large portion of the approved proposals were highly biased or ambiguous with respect to randomization, blinding, dealing with missing data, data collection tool, sampling methods, and statistical analysis. Thus, it is essential to consult and collaborate with a methodologist in all parts of a proposal to control the possible and specific biases in clinical trials.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Mixed-Methods Research in Nutrition and Dietetics.

PubMed

Zoellner, Jamie; Harris, Jeffrey E

2017-05-01

This work focuses on mixed-methods research (MMR) and is the 11th in a series exploring the importance of research design, statistical analysis, and epidemiologic methods as applied to nutrition and dietetics research. MMR research is an investigative technique that applies both quantitative and qualitative data. The purpose of this article is to define MMR; describe its history and nature; provide reasons for its use; describe and explain the six different MMR designs; describe sample selection; and provide guidance in data collection, analysis, and inference. MMR concepts are applied and integrated with nutrition-related scenarios in real-world research contexts and summary recommendations are provided. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Probabilistic Component Mode Synthesis of Nondeterministic Substructures

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1996-01-01

Standard methods of structural dynamic analysis assume that the structural characteristics are deterministic. Recognizing that these characteristics are actually statistical in nature researchers have recently developed a variety of methods that use this information to determine probabilities of a desired response characteristic, such as natural frequency, without using expensive Monte Carlo simulations. One of the problems in these methods is correctly identifying the statistical properties of primitive variables such as geometry, stiffness, and mass. We present a method where the measured dynamic properties of substructures are used instead as the random variables. The residual flexibility method of component mode synthesis is combined with the probabilistic methods to determine the cumulative distribution function of the system eigenvalues. A simple cantilever beam test problem is presented that illustrates the theory.

Sources of method bias in social science research and recommendations on how to control it.

PubMed

Podsakoff, Philip M; MacKenzie, Scott B; Podsakoff, Nathan P

2012-01-01

Despite the concern that has been expressed about potential method biases, and the pervasiveness of research settings with the potential to produce them, there is disagreement about whether they really are a problem for researchers in the behavioral sciences. Therefore, the purpose of this review is to explore the current state of knowledge about method biases. First, we explore the meaning of the terms "method" and "method bias" and then we examine whether method biases influence all measures equally. Next, we review the evidence of the effects that method biases have on individual measures and on the covariation between different constructs. Following this, we evaluate the procedural and statistical remedies that have been used to control method biases and provide recommendations for minimizing method bias.

Online Statistical Modeling (Regression Analysis) for Independent Responses

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

Can We Spin Straw Into Gold? An Evaluation of Immigrant Legal Status Imputation Approaches

PubMed Central

Van Hook, Jennifer; Bachmeier, James D.; Coffman, Donna; Harel, Ofer

2014-01-01

Researchers have developed logical, demographic, and statistical strategies for imputing immigrants’ legal status, but these methods have never been empirically assessed. We used Monte Carlo simulations to test whether, and under what conditions, legal status imputation approaches yield unbiased estimates of the association of unauthorized status with health insurance coverage. We tested five methods under a range of missing data scenarios. Logical and demographic imputation methods yielded biased estimates across all missing data scenarios. Statistical imputation approaches yielded unbiased estimates only when unauthorized status was jointly observed with insurance coverage; when this condition was not met, these methods overestimated insurance coverage for unauthorized relative to legal immigrants. We next showed how bias can be reduced by incorporating prior information about unauthorized immigrants. Finally, we demonstrated the utility of the best-performing statistical method for increasing power. We used it to produce state/regional estimates of insurance coverage among unauthorized immigrants in the Current Population Survey, a data source that contains no direct measures of immigrants’ legal status. We conclude that commonly employed legal status imputation approaches are likely to produce biased estimates, but data and statistical methods exist that could substantially reduce these biases. PMID:25511332

Regionalisation of statistical model outputs creating gridded data sets for Germany

NASA Astrophysics Data System (ADS)

Höpp, Simona Andrea; Rauthe, Monika; Deutschländer, Thomas

2016-04-01

The goal of the German research program ReKliEs-De (regional climate projection ensembles for Germany, http://.reklies.hlug.de) is to distribute robust information about the range and the extremes of future climate for Germany and its neighbouring river catchment areas. This joint research project is supported by the German Federal Ministry of Education and Research (BMBF) and was initiated by the German Federal States. The Project results are meant to support the development of adaptation strategies to mitigate the impacts of future climate change. The aim of our part of the project is to adapt and transfer the regionalisation methods of the gridded hydrological data set (HYRAS) from daily station data to the station based statistical regional climate model output of WETTREG (regionalisation method based on weather patterns). The WETTREG model output covers the period of 1951 to 2100 with a daily temporal resolution. For this, we generate a gridded data set of the WETTREG output for precipitation, air temperature and relative humidity with a spatial resolution of 12.5 km x 12.5 km, which is common for regional climate models. Thus, this regionalisation allows comparing statistical to dynamical climate model outputs. The HYRAS data set was developed by the German Meteorological Service within the German research program KLIWAS (www.kliwas.de) and consists of daily gridded data for Germany and its neighbouring river catchment areas. It has a spatial resolution of 5 km x 5 km for the entire domain for the hydro-meteorological elements precipitation, air temperature and relative humidity and covers the period of 1951 to 2006. After conservative remapping the HYRAS data set is also convenient for the validation of climate models. The presentation will consist of two parts to present the actual state of the adaptation of the HYRAS regionalisation methods to the statistical regional climate model WETTREG: First, an overview of the HYRAS data set and the regionalisation methods for precipitation (REGNIE method based on a combination of multiple linear regression with 5 predictors and inverse distance weighting), air temperature and relative humidity (optimal interpolation) will be given. Finally, results of the regionalisation of WETTREG model output will be shown.

Trends in study design and the statistical methods employed in a leading general medicine journal.

PubMed

Gosho, M; Sato, Y; Nagashima, K; Takahashi, S

2018-02-01

Study design and statistical methods have become core components of medical research, and the methodology has become more multifaceted and complicated over time. The study of the comprehensive details and current trends of study design and statistical methods is required to support the future implementation of well-planned clinical studies providing information about evidence-based medicine. Our purpose was to illustrate study design and statistical methods employed in recent medical literature. This was an extension study of Sato et al. (N Engl J Med 2017; 376: 1086-1087), which reviewed 238 articles published in 2015 in the New England Journal of Medicine (NEJM) and briefly summarized the statistical methods employed in NEJM. Using the same database, we performed a new investigation of the detailed trends in study design and individual statistical methods that were not reported in the Sato study. Due to the CONSORT statement, prespecification and justification of sample size are obligatory in planning intervention studies. Although standard survival methods (eg Kaplan-Meier estimator and Cox regression model) were most frequently applied, the Gray test and Fine-Gray proportional hazard model for considering competing risks were sometimes used for a more valid statistical inference. With respect to handling missing data, model-based methods, which are valid for missing-at-random data, were more frequently used than single imputation methods. These methods are not recommended as a primary analysis, but they have been applied in many clinical trials. Group sequential design with interim analyses was one of the standard designs, and novel design, such as adaptive dose selection and sample size re-estimation, was sometimes employed in NEJM. Model-based approaches for handling missing data should replace single imputation methods for primary analysis in the light of the information found in some publications. Use of adaptive design with interim analyses is increasing after the presentation of the FDA guidance for adaptive design. © 2017 John Wiley & Sons Ltd.

Difficulties in learning and teaching statistics: teacher views

NASA Astrophysics Data System (ADS)

Koparan, Timur

2015-01-01

The purpose of this study is to define teacher views about the difficulties in learning and teaching middle school statistics subjects. To serve this aim, a number of interviews were conducted with 10 middle school maths teachers in 2011-2012 school year in the province of Trabzon. Of the qualitative descriptive research methods, the semi-structured interview technique was applied in the research. In accordance with the aim, teacher opinions about the statistics subjects were examined and analysed. Similar responses from the teachers were grouped and evaluated. The teachers stated that it was positive that middle school statistics subjects were taught gradually in every grade but some difficulties were experienced in the teaching of this subject. The findings are presented in eight themes which are context, sample, data representation, central tendency and dispersion measure, probability, variance, and other difficulties.

Evaluating Differential Effects Using Regression Interactions and Regression Mixture Models

ERIC Educational Resources Information Center

Van Horn, M. Lee; Jaki, Thomas; Masyn, Katherine; Howe, George; Feaster, Daniel J.; Lamont, Andrea E.; George, Melissa R. W.; Kim, Minjung

2015-01-01

Research increasingly emphasizes understanding differential effects. This article focuses on understanding regression mixture models, which are relatively new statistical methods for assessing differential effects by comparing results to using an interactive term in linear regression. The research questions which each model answers, their…

CORSSA: Community Online Resource for Statistical Seismicity Analysis

NASA Astrophysics Data System (ADS)

Zechar, J. D.; Hardebeck, J. L.; Michael, A. J.; Naylor, M.; Steacy, S.; Wiemer, S.; Zhuang, J.

2011-12-01

Statistical seismology is critical to the understanding of seismicity, the evaluation of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology-especially to those aspects with great impact on public policy-statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA, www.corssa.org). We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each will contain between four and eight articles. CORSSA now includes seven articles with an additional six in draft form along with forums for discussion, a glossary, and news about upcoming meetings, special issues, and recent papers. Each article is peer-reviewed and presents a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. We have also begun curating a collection of statistical seismology software packages.

Statistical Learning Theory for High Dimensional Prediction: Application to Criterion-Keyed Scale Development

PubMed Central

Chapman, Benjamin P.; Weiss, Alexander; Duberstein, Paul

2016-01-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in “big data” problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how three common SLT algorithms–Supervised Principal Components, Regularization, and Boosting—can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach—or perhaps because of them–SLT methods may hold value as a statistically rigorous approach to exploratory regression. PMID:27454257

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Colombano, Silvano; Scargle, Jeff; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2003-01-01

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

In pursuit of a science of agriculture: the role of statistics in field experiments.

PubMed

Parolini, Giuditta

2015-09-01

Since the beginning of the twentieth century statistics has reshaped the experimental cultures of agricultural research taking part in the subtle dialectic between the epistemic and the material that is proper to experimental systems. This transformation has become especially relevant in field trials and the paper will examine the British agricultural institution, Rothamsted Experimental Station, where statistical methods nowadays popular in the planning and analysis of field experiments were developed in the 1920s. At Rothamsted statistics promoted randomisation over systematic arrangements, factorisation over one-question trials, and emphasised the importance of the experimental error in assessing field trials. These changes in methodology transformed also the material culture of agricultural science, and a new body, the Field Plots Committee, was created to manage the field research of the agricultural institution. Although successful, the vision of field experimentation proposed by the Rothamsted statisticians was not unproblematic. Experimental scientists closely linked to the farming community questioned it in favour of a field research that could be more easily understood by farmers. The clash between the two agendas reveals how the role attributed to statistics in field experimentation defined different pursuits of agricultural research, alternately conceived of as a scientists' science or as a farmers' science.

Effect Size as the Essential Statistic in Developing Methods for mTBI Diagnosis.

PubMed

Gibson, Douglas Brandt

2015-01-01

The descriptive statistic known as "effect size" measures the distinguishability of two sets of data. Distingishability is at the core of diagnosis. This article is intended to point out the importance of effect size in the development of effective diagnostics for mild traumatic brain injury and to point out the applicability of the effect size statistic in comparing diagnostic efficiency across the main proposed TBI diagnostic methods: psychological, physiological, biochemical, and radiologic. Comparing diagnostic approaches is difficult because different researcher in different fields have different approaches to measuring efficacy. Converting diverse measures to effect sizes, as is done in meta-analysis, is a relatively easy way to make studies comparable.

Frequent statistics of link-layer bit stream data based on AC-IM algorithm

NASA Astrophysics Data System (ADS)

Cao, Chenghong; Lei, Yingke; Xu, Yiming

2017-08-01

At present, there are many relevant researches on data processing using classical pattern matching and its improved algorithm, but few researches on statistical data of link-layer bit stream. This paper adopts a frequent statistical method of link-layer bit stream data based on AC-IM algorithm for classical multi-pattern matching algorithms such as AC algorithm has high computational complexity, low efficiency and it cannot be applied to binary bit stream data. The method's maximum jump distance of the mode tree is length of the shortest mode string plus 3 in case of no missing? In this paper, theoretical analysis is made on the principle of algorithm construction firstly, and then the experimental results show that the algorithm can adapt to the binary bit stream data environment and extract the frequent sequence more accurately, the effect is obvious. Meanwhile, comparing with the classical AC algorithm and other improved algorithms, AC-IM algorithm has a greater maximum jump distance and less time-consuming.

Evaluation of airborne lidar data to predict vegetation Presence/Absence

USGS Publications Warehouse

Palaseanu-Lovejoy, M.; Nayegandhi, A.; Brock, J.; Woodman, R.; Wright, C.W.

2009-01-01

This study evaluates the capabilities of the Experimental Advanced Airborne Research Lidar (EAARL) in delineating vegetation assemblages in Jean Lafitte National Park, Louisiana. Five-meter-resolution grids of bare earth, canopy height, canopy-reflection ratio, and height of median energy were derived from EAARL data acquired in September 2006. Ground-truth data were collected along transects to assess species composition, canopy cover, and ground cover. To decide which model is more accurate, comparisons of general linear models and generalized additive models were conducted using conventional evaluation methods (i.e., sensitivity, specificity, Kappa statistics, and area under the curve) and two new indexes, net reclassification improvement and integrated discrimination improvement. Generalized additive models were superior to general linear models in modeling presence/absence in training vegetation categories, but no statistically significant differences between the two models were achieved in determining the classification accuracy at validation locations using conventional evaluation methods, although statistically significant improvements in net reclassifications were observed. ?? 2009 Coastal Education and Research Foundation.

An improved method for determining force balance calibration accuracy

NASA Technical Reports Server (NTRS)

Ferris, Alice T.

1993-01-01

The results of an improved statistical method used at Langley Research Center for determining and stating the accuracy of a force balance calibration are presented. The application of the method for initial loads, initial load determination, auxiliary loads, primary loads, and proof loads is described. The data analysis is briefly addressed.

Adult Learners' Preferred Methods of Learning Preventative Heart Disease Care

ERIC Educational Resources Information Center

Alavi, Nasim

2016-01-01

The purpose of this study was to investigate the preferred method of learning about heart disease by adult learners. This research study also investigated if there was a statistically significant difference between race/ethnicity, age, and gender of adult learners and their preferred method of learning preventative heart disease care. This…

Evaluation of methods for managing censored results when calculating the geometric mean.

PubMed

Mikkonen, Hannah G; Clarke, Bradley O; Dasika, Raghava; Wallis, Christian J; Reichman, Suzie M

2018-01-01

Currently, there are conflicting views on the best statistical methods for managing censored environmental data. The method commonly applied by environmental science researchers and professionals is to substitute half the limit of reporting for derivation of summary statistics. This approach has been criticised by some researchers, raising questions around the interpretation of historical scientific data. This study evaluated four complete soil datasets, at three levels of simulated censorship, to test the accuracy of a range of censored data management methods for calculation of the geometric mean. The methods assessed included removal of censored results, substitution of a fixed value (near zero, half the limit of reporting and the limit of reporting), substitution by nearest neighbour imputation, maximum likelihood estimation, regression on order substitution and Kaplan-Meier/survival analysis. This is the first time such a comprehensive range of censored data management methods have been applied to assess the accuracy of calculation of the geometric mean. The results of this study show that, for describing the geometric mean, the simple method of substitution of half the limit of reporting is comparable or more accurate than alternative censored data management methods, including nearest neighbour imputation methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

The effects of modeling instruction on high school physics academic achievement

NASA Astrophysics Data System (ADS)

Wright, Tiffanie L.

The purpose of this study was to explore whether Modeling Instruction, compared to traditional lecturing, is an effective instructional method to promote academic achievement in selected high school physics classes at a rural middle Tennessee high school. This study used an ex post facto , quasi-experimental research methodology. The independent variables in this study were the instructional methods of teaching. The treatment variable was Modeling Instruction and the control variable was traditional lecture instruction. The Treatment Group consisted of participants in Physical World Concepts who received Modeling Instruction. The Control Group consisted of participants in Physical Science who received traditional lecture instruction. The dependent variable was gains scores on the Force Concepts Inventory (FCI). The participants for this study were 133 students each in both the Treatment and Control Groups (n = 266), who attended a public, high school in rural middle Tennessee. The participants were administered the Force Concepts Inventory (FCI) prior to being taught the mechanics of physics. The FCI data were entered into the computer-based Statistical Package for the Social Science (SPSS). Two independent samples t-tests were conducted to answer the research questions. There was a statistically significant difference between the treatment and control groups concerning the instructional method. Modeling Instructional methods were found to be effective in increasing the academic achievement of students in high school physics. There was no statistically significant difference between FCI gains scores for gender. Gender was found to have no effect on the academic achievement of students in high school physics classes. However, even though there was not a statistically significant difference, female students' gains scores were higher than male students' gains scores when Modeling Instructional methods of teaching were used. Based on these findings, it is recommended that high school science teachers should use Modeling Instructional methods of teaching daily in their classrooms. A recommendation for further research is to expand the Modeling Instructional methods of teaching into different content areas, (i.e., reading and language arts) to explore academic achievement gains.

Endpoints and cutpoints in head and neck oncology trials: methodical background, challenges, current practice and perspectives.

PubMed

Hezel, Marcus; von Usslar, Kathrin; Kurzweg, Thiemo; Lörincz, Balazs B; Knecht, Rainald

2016-04-01

This article reviews the methodical and statistical basics of designing a trial, with a special focus on the process of defining and choosing endpoints and cutpoints as the foundations of clinical research, and ultimately that of evidence-based medicine. There has been a significant progress in the treatment of head and neck cancer in the past few decades. Currently available treatment options can have a variety of different goals, depending e.g. on tumor stage, among other factors. The outcome of a specific treatment in clinical trials is measured using endpoints. Besides classical endpoints, such as overall survival or organ preservation, other endpoints like quality of life are becoming increasingly important in designing and conducting a trial. The present work is based on electronic research and focuses on the solid methodical and statistical basics of a clinical trial, on the structure of study designs and on the presentation of various endpoints.

A note on the kappa statistic for clustered dichotomous data.

PubMed

Zhou, Ming; Yang, Zhao

2014-06-30

The kappa statistic is widely used to assess the agreement between two raters. Motivated by a simulation-based cluster bootstrap method to calculate the variance of the kappa statistic for clustered physician-patients dichotomous data, we investigate its special correlation structure and develop a new simple and efficient data generation algorithm. For the clustered physician-patients dichotomous data, based on the delta method and its special covariance structure, we propose a semi-parametric variance estimator for the kappa statistic. An extensive Monte Carlo simulation study is performed to evaluate the performance of the new proposal and five existing methods with respect to the empirical coverage probability, root-mean-square error, and average width of the 95% confidence interval for the kappa statistic. The variance estimator ignoring the dependence within a cluster is generally inappropriate, and the variance estimators from the new proposal, bootstrap-based methods, and the sampling-based delta method perform reasonably well for at least a moderately large number of clusters (e.g., the number of clusters K ⩾50). The new proposal and sampling-based delta method provide convenient tools for efficient computations and non-simulation-based alternatives to the existing bootstrap-based methods. Moreover, the new proposal has acceptable performance even when the number of clusters is as small as K = 25. To illustrate the practical application of all the methods, one psychiatric research data and two simulated clustered physician-patients dichotomous data are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.

Methods to Measure Physical Activity Behaviors in Health Education Research

ERIC Educational Resources Information Center

Fitzhugh, Eugene C.

2015-01-01

Regular physical activity (PA) is an important concept to measure in health education research. The health education researcher might need to measure physical activity because it is the primary measure of interest, or PA might be a confounding measure that needs to be controlled for in statistical analysis. The purpose of this commentary is to…

A Methodological Review of Statistical Methods for Handling Multilevel Non-Nested Longitudinal Data in Educational Research

ERIC Educational Resources Information Center

Sun, Shuyan; Pan, Wei

2014-01-01

As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…

Statistical sampling methods for soils monitoring

Treesearch

Ann M. Abbott

2010-01-01

Development of the best sampling design to answer a research question should be an interactive venture between the land manager or researcher and statisticians, and is the result of answering various questions. A series of questions that can be asked to guide the researcher in making decisions that will arrive at an effective sampling plan are described, and a case...

Statistical assessment of speech system performance

NASA Technical Reports Server (NTRS)

Moshier, Stephen L.

1977-01-01

Methods for the normalization of performance tests results of speech recognition systems are presented. Technological accomplishments in speech recognition systems, as well as planned research activities are described.

Improving the dependability of research in personality and social psychology: recommendations for research and educational practice.

PubMed

Funder, David C; Levine, John M; Mackie, Diane M; Morf, Carolyn C; Sansone, Carol; Vazire, Simine; West, Stephen G

2014-02-01

In this article, the Society for Personality and Social Psychology (SPSP) Task Force on Publication and Research Practices offers a brief statistical primer and recommendations for improving the dependability of research. Recommendations for research practice include (a) describing and addressing the choice of N (sample size) and consequent issues of statistical power, (b) reporting effect sizes and 95% confidence intervals (CIs), (c) avoiding "questionable research practices" that can inflate the probability of Type I error, (d) making available research materials necessary to replicate reported results, (e) adhering to SPSP's data sharing policy, (f) encouraging publication of high-quality replication studies, and (g) maintaining flexibility and openness to alternative standards and methods. Recommendations for educational practice include (a) encouraging a culture of "getting it right," (b) teaching and encouraging transparency of data reporting, (c) improving methodological instruction, and (d) modeling sound science and supporting junior researchers who seek to "get it right."

Investigating Student Understanding of Histograms

ERIC Educational Resources Information Center

Kaplan, Jennifer J.; Gabrosek, John G.; Curtiss, Phyllis; Malone, Chris

2014-01-01

Histograms are adept at revealing the distribution of data values, especially the shape of the distribution and any outlier values. They are included in introductory statistics texts, research methods texts, and in the popular press, yet students often have difficulty interpreting the information conveyed by a histogram. This research identifies…

Quantifying and Interpreting Group Differences in Interest Profiles

ERIC Educational Resources Information Center

Armstrong, Patrick Ian; Fouad, Nadya A.; Rounds, James; Hubert, Lawrence

2010-01-01

Research on group differences in interests has often focused on structural hypotheses and mean-score differences in Holland's (1997) theory, with comparatively little research on basic interest measures. Group differences in interest profiles were examined using statistical methods for matching individuals with occupations, the C-index, Q…

[Analysis of master degree thesis of otolaryngology head and neck surgery in Xinjiang].

PubMed

Ayiheng, Qukuerhan; Niliapaer, Alimu; Yalikun, Yasheng

2010-12-01

To understand the basic situation and development of knowledge structure and ability of master degree of Otolaryngology Head and Neck Surgery in Xinjiang region in order to provide reference to further improve the quality of postgraduate students. Fourty-six papers of Otolaryngology master degree thesis were reviewed at randomly in terms of types, subject selection ranges as well as statistical methods during 1998-2009 in Xinjiang region in order to analyze and explore its advantages and characteristics and suggest a solution for its disadvantages. In 46 degree thesis, nine of them are scientific dissertations accounting for 19.57%, 37 are clinical professional degree thesis, accounting for 80.43%. Five are Experimental research papers, 30 are clinical research papers, 10 are clinical and experimental research papers, 1 of them is experimental epidemiology research paper; in this study, the kinds of diseases including every subject of ENT, various statistical methods are involved; references are 37.46 in average, 19.55 of them are foreign literatures references in nearly 5 years are 13.57; four ethnic groups are exist in postgraduate students with high teaching professional level of tutors. The clinical research should be focused in order to further research on ENT common diseases, the application of advanced research methods, the full application of the latest literature, tutors with high-level, training of students of various nationalities, basic research needs to be innovative and should be focus the subject characteristics, to avoid excessive duplication of research.

The expectancy-value muddle in the theory of planned behaviour - and some proposed solutions.

PubMed

French, David P; Hankins, Matthew

2003-02-01

The authors of the Theories of Reasoned Action and Planned Behaviour recommended a method for statistically analysing the relationships between beliefs and the Attitude, Subjective Norm, and Perceived Behavioural Control constructs. This method has been used in the overwhelming majority of studies using these theories. However, there is a growing awareness that this method yields statistically uninterpretable results (Evans, 1991). Despite this, the use of this method is continuing, as is uninformed interpretation of this problematic research literature. This is probably due to the lack of a simple account of where the problem lies, and the large number of alternatives available. This paper therefore summarizes the problem as simply as possible, gives consideration to the conclusions that can be validly drawn from studies that contain this problem, and critically reviews the many alternatives that have been proposed to address this problem. Different techniques are identified as being suitable, according to the purpose of the specific research project.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

[The research protocol III. Study population].

PubMed

Arias-Gómez, Jesús; Villasís-Keever, Miguel Ángel; Miranda-Novales, María Guadalupe

2016-01-01

The study population is defined as a set of cases, determined, limited, and accessible, that will constitute the subjects for the selection of the sample, and must fulfill several characteristics and distinct criteria. The objectives of this manuscript are focused on specifying each one of the elements required to make the selection of the participants of a research project, during the elaboration of the protocol, including the concepts of study population, sample, selection criteria and sampling methods. After delineating the study population, the researcher must specify the criteria that each participant has to comply. The criteria that include the specific characteristics are denominated selection or eligibility criteria. These criteria are inclusion, exclusion and elimination, and will delineate the eligible population. The sampling methods are divided in two large groups: 1) probabilistic or random sampling and 2) non-probabilistic sampling. The difference lies in the employment of statistical methods to select the subjects. In every research, it is necessary to establish at the beginning the specific number of participants to be included to achieve the objectives of the study. This number is the sample size, and can be calculated or estimated with mathematical formulas and statistic software.

Interactions among Knowledge, Beliefs, and Goals in Framing a Qualitative Study in Statistics Education

ERIC Educational Resources Information Center

Groth, Randall E.

2010-01-01

In the recent past, qualitative research methods have become more prevalent in the field of statistics education. This paper offers thoughts on the process of framing a qualitative study by means of an illustrative example. The decisions that influenced the framing of a study of pre-service teachers' understanding of the concept of statistical…

Statistical Methods for Assessments in Simulations and Serious Games. Research Report. ETS RR-14-12

ERIC Educational Resources Information Center

Fu, Jianbin; Zapata, Diego; Mavronikolas, Elia

2014-01-01

Simulation or game-based assessments produce outcome data and process data. In this article, some statistical models that can potentially be used to analyze data from simulation or game-based assessments are introduced. Specifically, cognitive diagnostic models that can be used to estimate latent skills from outcome data so as to scale these…

A systematic review of statistical methods used to test for reliability of medical instruments measuring continuous variables.

PubMed

Zaki, Rafdzah; Bulgiba, Awang; Nordin, Noorhaire; Azina Ismail, Noor

2013-06-01

Reliability measures precision or the extent to which test results can be replicated. This is the first ever systematic review to identify statistical methods used to measure reliability of equipment measuring continuous variables. This studyalso aims to highlight the inappropriate statistical method used in the reliability analysis and its implication in the medical practice. In 2010, five electronic databases were searched between 2007 and 2009 to look for reliability studies. A total of 5,795 titles were initially identified. Only 282 titles were potentially related, and finally 42 fitted the inclusion criteria. The Intra-class Correlation Coefficient (ICC) is the most popular method with 25 (60%) studies having used this method followed by the comparing means (8 or 19%). Out of 25 studies using the ICC, only 7 (28%) reported the confidence intervals and types of ICC used. Most studies (71%) also tested the agreement of instruments. This study finds that the Intra-class Correlation Coefficient is the most popular method used to assess the reliability of medical instruments measuring continuous outcomes. There are also inappropriate applications and interpretations of statistical methods in some studies. It is important for medical researchers to be aware of this issue, and be able to correctly perform analysis in reliability studies.

Accounting for isotopic clustering in Fourier transform mass spectrometry data analysis for clinical diagnostic studies.

PubMed

Kakourou, Alexia; Vach, Werner; Nicolardi, Simone; van der Burgt, Yuri; Mertens, Bart

2016-10-01

Mass spectrometry based clinical proteomics has emerged as a powerful tool for high-throughput protein profiling and biomarker discovery. Recent improvements in mass spectrometry technology have boosted the potential of proteomic studies in biomedical research. However, the complexity of the proteomic expression introduces new statistical challenges in summarizing and analyzing the acquired data. Statistical methods for optimally processing proteomic data are currently a growing field of research. In this paper we present simple, yet appropriate methods to preprocess, summarize and analyze high-throughput MALDI-FTICR mass spectrometry data, collected in a case-control fashion, while dealing with the statistical challenges that accompany such data. The known statistical properties of the isotopic distribution of the peptide molecules are used to preprocess the spectra and translate the proteomic expression into a condensed data set. Information on either the intensity level or the shape of the identified isotopic clusters is used to derive summary measures on which diagnostic rules for disease status allocation will be based. Results indicate that both the shape of the identified isotopic clusters and the overall intensity level carry information on the class outcome and can be used to predict the presence or absence of the disease.

Methodological Reporting in Qualitative, Quantitative, and Mixed Methods Health Services Research Articles

PubMed Central

Wisdom, Jennifer P; Cavaleri, Mary A; Onwuegbuzie, Anthony J; Green, Carla A

2012-01-01

Objectives Methodologically sound mixed methods research can improve our understanding of health services by providing a more comprehensive picture of health services than either method can alone. This study describes the frequency of mixed methods in published health services research and compares the presence of methodological components indicative of rigorous approaches across mixed methods, qualitative, and quantitative articles. Data Sources All empirical articles (n = 1,651) published between 2003 and 2007 from four top-ranked health services journals. Study Design All mixed methods articles (n = 47) and random samples of qualitative and quantitative articles were evaluated to identify reporting of key components indicating rigor for each method, based on accepted standards for evaluating the quality of research reports (e.g., use of p-values in quantitative reports, description of context in qualitative reports, and integration in mixed method reports). We used chi-square tests to evaluate differences between article types for each component. Principal Findings Mixed methods articles comprised 2.85 percent (n = 47) of empirical articles, quantitative articles 90.98 percent (n = 1,502), and qualitative articles 6.18 percent (n = 102). There was a statistically significant difference (χ2(1) = 12.20, p = .0005, Cramer's V = 0.09, odds ratio = 1.49 [95% confidence interval = 1,27, 1.74]) in the proportion of quantitative methodological components present in mixed methods compared to quantitative papers (21.94 versus 47.07 percent, respectively) but no statistically significant difference (χ2(1) = 0.02, p = .89, Cramer's V = 0.01) in the proportion of qualitative methodological components in mixed methods compared to qualitative papers (21.34 versus 25.47 percent, respectively). Conclusion Few published health services research articles use mixed methods. The frequency of key methodological components is variable. Suggestions are provided to increase the transparency of mixed methods studies and the presence of key methodological components in published reports. PMID:22092040

Understanding spatial organizations of chromosomes via statistical analysis of Hi-C data

PubMed Central

Hu, Ming; Deng, Ke; Qin, Zhaohui; Liu, Jun S.

2015-01-01

Understanding how chromosomes fold provides insights into the transcription regulation, hence, the functional state of the cell. Using the next generation sequencing technology, the recently developed Hi-C approach enables a global view of spatial chromatin organization in the nucleus, which substantially expands our knowledge about genome organization and function. However, due to multiple layers of biases, noises and uncertainties buried in the protocol of Hi-C experiments, analyzing and interpreting Hi-C data poses great challenges, and requires novel statistical methods to be developed. This article provides an overview of recent Hi-C studies and their impacts on biomedical research, describes major challenges in statistical analysis of Hi-C data, and discusses some perspectives for future research. PMID:26124977

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, George

1993-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, Stanislav

1992-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.

ARC Researchers at ASME 2015 Internal Combustion Engine Division Fall

Science.gov Websites

-sense. Therefore, the focus of this paper is on the various methods of computing CA50 for analysing and classifying cycle-to-cycle variability. The assumptions made to establish fast and possibly on-line methods SI engine. Then the various fast methods for computing CA50 feed the two statistical methods

Research progress on expansive soil cracks under changing environment.

PubMed

Shi, Bei-xiao; Zheng, Cheng-feng; Wu, Jin-kun

2014-01-01

Engineering problems shunned previously rise to the surface gradually with the activities of reforming the natural world in depth, the problem of expansive soil crack under the changing environment becoming a control factor of expansive soil slope stability. The problem of expansive soil crack has gradually become a research hotspot, elaborates the occurrence and development of cracks from the basic properties of expansive soil, and points out the role of controlling the crack of expansive soil strength. We summarize the existing research methods and results of expansive soil crack characteristics. Improving crack measurement and calculation method and researching the crack depth measurement, statistical analysis method, crack depth and surface feature relationship will be the future direction.

Single-case research design in pediatric psychology: considerations regarding data analysis.

PubMed

Cohen, Lindsey L; Feinstein, Amanda; Masuda, Akihiko; Vowles, Kevin E

2014-03-01

Single-case research allows for an examination of behavior and can demonstrate the functional relation between intervention and outcome in pediatric psychology. This review highlights key assumptions, methodological and design considerations, and options for data analysis. Single-case methodology and guidelines are reviewed with an in-depth focus on visual and statistical analyses. Guidelines allow for the careful evaluation of design quality and visual analysis. A number of statistical techniques have been introduced to supplement visual analysis, but to date, there is no consensus on their recommended use in single-case research design. Single-case methodology is invaluable for advancing pediatric psychology science and practice, and guidelines have been introduced to enhance the consistency, validity, and reliability of these studies. Experts generally agree that visual inspection is the optimal method of analysis in single-case design; however, statistical approaches are becoming increasingly evaluated and used to augment data interpretation.

Research on Time Selection of Mass Sports in Tibetan Areas Plateau of Gansu Province Based on Environmental Science

NASA Astrophysics Data System (ADS)

Gao, Jike

2018-01-01

Through using the method of literature review, instrument measuring, questionnaire and mathematical statistics, this paper analyzed the current situation in Mass Sports of Tibetan Areas Plateau in Gansu Province. Through experimental test access to Tibetan areas in gansu province of air pollutants and meteorological index data as the foundation, control related national standard and exercise science, statistical analysis of data, the Tibetan plateau, gansu province people participate in physical exercise is dedicated to providing you with scientific methods and appropriate time.

Measurement of the local food environment: a comparison of existing data sources.

PubMed

Bader, Michael D M; Ailshire, Jennifer A; Morenoff, Jeffrey D; House, James S

2010-03-01

Studying the relation between the residential environment and health requires valid, reliable, and cost-effective methods to collect data on residential environments. This 2002 study compared the level of agreement between measures of the presence of neighborhood businesses drawn from 2 common sources of data used for research on the built environment and health: listings of businesses from commercial databases and direct observations of city blocks by raters. Kappa statistics were calculated for 6 types of businesses-drugstores, liquor stores, bars, convenience stores, restaurants, and grocers-located on 1,663 city blocks in Chicago, Illinois. Logistic regressions estimated whether disagreement between measurement methods was systematically correlated with the socioeconomic and demographic characteristics of neighborhoods. Levels of agreement between the 2 sources were relatively high, with significant (P < 0.001) kappa statistics for each business type ranging from 0.32 to 0.70. Most business types were more likely to be reported by direct observations than in the commercial database listings. Disagreement between the 2 sources was not significantly correlated with the socioeconomic and demographic characteristics of neighborhoods. Results suggest that researchers should have reasonable confidence using whichever method (or combination of methods) is most cost-effective and theoretically appropriate for their research design.

Statistical reporting inconsistencies in experimental philosophy

PubMed Central

Colombo, Matteo; Duev, Georgi; Nuijten, Michèle B.; Sprenger, Jan

2018-01-01

Experimental philosophy (x-phi) is a young field of research in the intersection of philosophy and psychology. It aims to make progress on philosophical questions by using experimental methods traditionally associated with the psychological and behavioral sciences, such as null hypothesis significance testing (NHST). Motivated by recent discussions about a methodological crisis in the behavioral sciences, questions have been raised about the methodological standards of x-phi. Here, we focus on one aspect of this question, namely the rate of inconsistencies in statistical reporting. Previous research has examined the extent to which published articles in psychology and other behavioral sciences present statistical inconsistencies in reporting the results of NHST. In this study, we used the R package statcheck to detect statistical inconsistencies in x-phi, and compared rates of inconsistencies in psychology and philosophy. We found that rates of inconsistencies in x-phi are lower than in the psychological and behavioral sciences. From the point of view of statistical reporting consistency, x-phi seems to do no worse, and perhaps even better, than psychological science. PMID:29649220

Suggestions for presenting the results of data analyses

USGS Publications Warehouse

Anderson, David R.; Link, William A.; Johnson, Douglas H.; Burnham, Kenneth P.

2001-01-01

We give suggestions for the presentation of research results from frequentist, information-theoretic, and Bayesian analysis paradigms, followed by several general suggestions. The information-theoretic and Bayesian methods offer alternative approaches to data analysis and inference compared to traditionally used methods. Guidance is lacking on the presentation of results under these alternative procedures and on nontesting aspects of classical frequentists methods of statistical analysis. Null hypothesis testing has come under intense criticism. We recommend less reporting of the results of statistical tests of null hypotheses in cases where the null is surely false anyway, or where the null hypothesis is of little interest to science or management.

New methods of testing nonlinear hypothesis using iterative NLLS estimator

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results.

PubMed

Pfeifer, Mischa D; Scholkmann, Felix; Labruyère, Rob

2017-01-01

Even though research in the field of functional near-infrared spectroscopy (fNIRS) has been performed for more than 20 years, consensus on signal processing methods is still lacking. A significant knowledge gap exists between established researchers and those entering the field. One major issue regularly observed in publications from researchers new to the field is the failure to consider possible signal contamination by hemodynamic changes unrelated to neurovascular coupling (i.e., scalp blood flow and systemic blood flow). This might be due to the fact that these researchers use the signal processing methods provided by the manufacturers of their measurement device without an advanced understanding of the performed steps. The aim of the present study was to investigate how different signal processing approaches (including and excluding approaches that partially correct for the possible signal contamination) affect the results of a typical functional neuroimaging study performed with fNIRS. In particular, we evaluated one standard signal processing method provided by a commercial company and compared it to three customized approaches. We thereby investigated the influence of the chosen method on the statistical outcome of a clinical data set (task-evoked motor cortex activity). No short-channels were used in the present study and therefore two types of multi-channel corrections based on multiple long-channels were applied. The choice of the signal processing method had a considerable influence on the outcome of the study. While methods that ignored the contamination of the fNIRS signals by task-evoked physiological noise yielded several significant hemodynamic responses over the whole head, the statistical significance of these findings disappeared when accounting for part of the contamination using a multi-channel regression. We conclude that adopting signal processing methods that correct for physiological confounding effects might yield more realistic results in cases where multi-distance measurements are not possible. Furthermore, we recommend using manufacturers' standard signal processing methods only in case the user has an advanced understanding of every signal processing step performed.

Galton's legacy to research on intelligence.

PubMed

Jensen, Arthur R

2002-04-01

In the 1999 Galton Lecture for the annual conference of The Galton Institute, the author summarizes the main elements of Galton's ideas about human mental ability and the research paradigm they generated, including the concept of 'general' mental ability, its hereditary component, its physical basis, racial differences, and methods for measuring individual differences in general ability. Although the conclusions Galton drew from his empirical studies were seldom compelling for lack of the needed technology and methods of statistical inference in his day, contemporary research has generally borne out most of Galton's original and largely intuitive ideas, which still inspire mainstream scientific research on intelligence.

Interview with Antony John Kunnan on Language Assessment

ERIC Educational Resources Information Center

Nimehchisalem, Vahid

2015-01-01

Antony John Kunnan is a language assessment specialist. His research interests are fairness of tests and testing practice, assessment literacy, research methods and statistics, ethics and standards, and language assessment policy. His most recent publications include a four-volume edited collection of 140 chapters titled "The Companion to…

Introducing Students to Plant Geography: Polar Ordination Applied to Hanging Gardens.

ERIC Educational Resources Information Center

Malanson, George P.; And Others

1993-01-01

Reports on a research study in which college students used a statistical ordination method to reveal relationships among plant community structures and physical, disturbance, and spatial variables. Concludes that polar ordination helps students understand the methodology of plant geography and encourages further student research. (CFR)

Analysis of Publications and Citations from a Geophysics Research Institute.

ERIC Educational Resources Information Center

Frohlich, Cliff; Resler, Lynn

2001-01-01

Performs an analysis of all 1128 publications produced by scientists during their employment at the University of Texas Institute for Geophysics, thus assessing research performance using as bibliometric indicators such statistics as publications per year, citations per paper, and cited half-lives. Evaluates five different methods for determining…

Economic Psychology: Its Connections with Research-Oriented Courses

ERIC Educational Resources Information Center

Christopher, Andrew N.; Marek, Pam; Benigno, Joann

2003-01-01

To enhance student interest in research methods, tests and measurement, and statistics classes, we describe how teachers may use resources from economic psychology to illustrate key concepts in these courses. Because of their applied nature and relevance to student experiences, topics covered by these resources may capture student attention and…

Analysis and Interpretation of Findings Using Multiple Regression Techniques

ERIC Educational Resources Information Center

Hoyt, William T.; Leierer, Stephen; Millington, Michael J.

2006-01-01

Multiple regression and correlation (MRC) methods form a flexible family of statistical techniques that can address a wide variety of different types of research questions of interest to rehabilitation professionals. In this article, we review basic concepts and terms, with an emphasis on interpretation of findings relevant to research questions…

Tips, Tropes, and Trivia: Ideas for Teaching Educational Research.

ERIC Educational Resources Information Center

Stallings, William M.; And Others

The collective experience of more than 50 years has led to the development of approaches that have enhanced student comprehension in the teaching of educational research methods, statistics, and measurement. Tips for teachers include using illustrative problems with one-digit numbers, using common situations and everyday objects to illustrate…

Approaches to Art Therapy for Cancer Inpatients: Research and Practice Considerations

ERIC Educational Resources Information Center

Nainis, Nancy A.

2008-01-01

Common symptoms reported by cancer patients include pain, fatigue, breathlessness, insomnia, lack of appetite, and anxiety. A study conducted by an interdisciplinary research team (Nainis et al., 2006) demonstrated statistically significant reductions in these cancer symptoms with the use of traditional art therapy methods. The study found a…

"Adultspan" Publication Patterns: Author and Article Characteristics from 1999 to 2009

ERIC Educational Resources Information Center

Erford, Bradley T.; Clark, Kelly H.; Erford, Breann M.

2011-01-01

Publication patterns of articles in "Adultspan" from 1999 to 2009 were reviewed. Author characteristics and article content were analyzed to determine trends over time. Research articles were analyzed specifically for type of research design, classification, sampling method, types of participants, sample size, types of statistics used, and…

Evaluation of Models of the Reading Process.

ERIC Educational Resources Information Center

Balajthy, Ernest

A variety of reading process models have been proposed and evaluated in reading research. Traditional approaches to model evaluation specify the workings of a system in a simplified fashion to enable organized, systematic study of the system's components. Following are several statistical methods of model evaluation: (1) empirical research on…

Eric Kozubal | NREL

Science.gov Websites

researches new methods and technologies for energy-efficient air conditioning systems. He has tested more -6155 Eric joined NREL in 2002 and is a member of the Commercial Buildings Research Group. Eric recommendations. He uses tools such as CAD, Matlab, Engineer Equation Solver, Excel, and statistical software to

Examining Multidimensional Middle Grade Outcomes after Early Elementary School Grade Retention

ERIC Educational Resources Information Center

Hwang, Sophia; Cappella, Elise; Schwartz, Kate

2016-01-01

Recently, researchers have begun to employ rigorous statistical methods and developmentally-informed theories to evaluate outcomes for students retained in non-kindergarten early elementary school. However, the majority of this research focuses on academic outcomes. Gaps remain regarding retention's effects on psychosocial outcomes important to…

One Hundred Years of Research: Prudent Aspirations

ERIC Educational Resources Information Center

Glass, Gene V.

2016-01-01

The statistical method "meta-analysis" is perhaps unique as a contribution to empirical inquiry of many types because it arose entirely within the practice of education research. In spite of its origins, meta-analysis has found its widest application and most important contributions in the field of medicine. Contrasting the success of…

Computer Simulation of Classic Studies in Psychology.

ERIC Educational Resources Information Center

Bradley, Drake R.

This paper describes DATASIM, a comprehensive software package which generates simulated data for actual or hypothetical research designs. DATASIM is primarily intended for use in statistics and research methods courses, where it is used to generate "individualized" datasets for students to analyze, and later to correct their answers.…

The Application of Bayesian Analysis to Issues in Developmental Research

ERIC Educational Resources Information Center

Walker, Lawrence J.; Gustafson, Paul; Frimer, Jeremy A.

2007-01-01

This article reviews the concepts and methods of Bayesian statistical analysis, which can offer innovative and powerful solutions to some challenging analytical problems that characterize developmental research. In this article, we demonstrate the utility of Bayesian analysis, explain its unique adeptness in some circumstances, address some…

Cluster Analysis of Minnesota School Districts. A Research Report.

ERIC Educational Resources Information Center

Cleary, James

The term "cluster analysis" refers to a set of statistical methods that classify entities with similar profiles of scores on a number of measured dimensions, in order to create empirically based typologies. A 1980 Minnesota House Research Report employed cluster analysis to categorize school districts according to their relative mixtures…

Using Microsoft Excel to teach statistics in a graduate advanced practice nursing program.

PubMed

DiMaria-Ghalili, Rose Ann; Ostrow, C Lynne

2009-02-01

This article describes the authors' experiences during 3 years of using Microsoft Excel to teach graduate-level statistics, as part of the research core required by the American Association of Colleges of Nursing for all professional graduate nursing programs. The advantages to using this program instead of specialized statistical programs are ease of accessibility, increased transferability of skills, and reduced cost for students. The authors share their insight about realistic goals for teaching statistics to master's-level students and the resources that are available to faculty to help them to learn and use Excel in their courses. Several online sites that are excellent resources for both faculty and students are discussed. Detailed attention is given to an online course (Carnegie-Mellon University Open Learning Initiative, n.d.), which the authors have incorporated into their graduate-level research methods course.

Case Selection via Matching

ERIC Educational Resources Information Center

Nielsen, Richard A.

2016-01-01

This article shows how statistical matching methods can be used to select "most similar" cases for qualitative analysis. I first offer a methodological justification for research designs based on selecting most similar cases. I then discuss the applicability of existing matching methods to the task of selecting most similar cases and…

Computer Mediated Communication: Online Instruction and Interactivity.

ERIC Educational Resources Information Center

Lavooy, Maria J.; Newlin, Michael H.

2003-01-01

Explores the different forms and potential applications of computer mediated communication (CMC) for Web-based and Web-enhanced courses. Based on their experiences with three different Web courses (Research Methods in Psychology, Statistical Methods in Psychology, and Basic Learning Processes) taught repeatedly over the last five years, the…

An evaluation of the quality of statistical design and analysis of published medical research: results from a systematic survey of general orthopaedic journals.

PubMed

Parsons, Nick R; Price, Charlotte L; Hiskens, Richard; Achten, Juul; Costa, Matthew L

2012-04-25

The application of statistics in reported research in trauma and orthopaedic surgery has become ever more important and complex. Despite the extensive use of statistical analysis, it is still a subject which is often not conceptually well understood, resulting in clear methodological flaws and inadequate reporting in many papers. A detailed statistical survey sampled 100 representative orthopaedic papers using a validated questionnaire that assessed the quality of the trial design and statistical analysis methods. The survey found evidence of failings in study design, statistical methodology and presentation of the results. Overall, in 17% (95% confidence interval; 10-26%) of the studies investigated the conclusions were not clearly justified by the results, in 39% (30-49%) of studies a different analysis should have been undertaken and in 17% (10-26%) a different analysis could have made a difference to the overall conclusions. It is only by an improved dialogue between statistician, clinician, reviewer and journal editor that the failings in design methodology and analysis highlighted by this survey can be addressed.

Critically appraising qualitative research: a guide for clinicians more familiar with quantitative techniques.

PubMed

Kisely, Stephen; Kendall, Elizabeth

2011-08-01

Papers using qualitative methods are increasingly common in psychiatric journals. This overview is an introduction to critically appraising a qualitative paper for clinicians who are more familiar with quantitative methods. Qualitative research uses data from interviews (semi-structured or unstructured), focus groups, observations or written materials. Data analysis is inductive, allowing meaning to emerge from the data, rather than the more deductive, hypothesis centred approach of quantitative research. This overview compares and contrasts quantitative and qualitative research methods. Quantitative concepts such as reliability, validity, statistical power, bias and generalisability have qualitative equivalents. These include triangulation, trustworthiness, saturation, reflexivity and applicability. Reflexivity also shares features of transference. Qualitative approaches include: ethnography, action-assessment, grounded theory, case studies and mixed methods. Qualitative research can complement quantitative approaches. An understanding of both is useful in critically appraising the psychiatric literature.

Qualitative versus quantitative methods in psychiatric research.

PubMed

Razafsha, Mahdi; Behforuzi, Hura; Azari, Hassan; Zhang, Zhiqun; Wang, Kevin K; Kobeissy, Firas H; Gold, Mark S

2012-01-01

Qualitative studies are gaining their credibility after a period of being misinterpreted as "not being quantitative." Qualitative method is a broad umbrella term for research methodologies that describe and explain individuals' experiences, behaviors, interactions, and social contexts. In-depth interview, focus groups, and participant observation are among the qualitative methods of inquiry commonly used in psychiatry. Researchers measure the frequency of occurring events using quantitative methods; however, qualitative methods provide a broader understanding and a more thorough reasoning behind the event. Hence, it is considered to be of special importance in psychiatry. Besides hypothesis generation in earlier phases of the research, qualitative methods can be employed in questionnaire design, diagnostic criteria establishment, feasibility studies, as well as studies of attitude and beliefs. Animal models are another area that qualitative methods can be employed, especially when naturalistic observation of animal behavior is important. However, since qualitative results can be researcher's own view, they need to be statistically confirmed, quantitative methods. The tendency to combine both qualitative and quantitative methods as complementary methods has emerged over recent years. By applying both methods of research, scientists can take advantage of interpretative characteristics of qualitative methods as well as experimental dimensions of quantitative methods.

Extreme Quantile Estimation in Binary Response Models

DTIC Science & Technology

1990-03-01

in Cancer Research," Biometria , VoL 66, pp. 307-316. Hsi, B.P. [1969], ’The Multiple Sample Up-and-Down Method in Bioassay," Journal of the American...New Method of Estimation," Biometria , VoL 53, pp. 439-454. Wetherill, G.B. [1976], Sequential Methods in Statistics, London: Chapman and Hall. Wu, C.FJ

A Mixed-Methods Study Investigating the Relationship between Media Multitasking Orientation and Grade Point Average

ERIC Educational Resources Information Center

Lee, Jennifer

2012-01-01

The intent of this study was to examine the relationship between media multitasking orientation and grade point average. The study utilized a mixed-methods approach to investigate the research questions. In the quantitative section of the study, the primary method of statistical analyses was multiple regression. The independent variables for the…

A New Sample Size Formula for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.

The focus of this research was to determine the efficacy of a new method of selecting sample sizes for multiple linear regression. A Monte Carlo simulation was used to study both empirical predictive power rates and empirical statistical power rates of the new method and seven other methods: those of C. N. Park and A. L. Dudycha (1974); J. Cohen…

The allele combinations of three loci based on, liver, stomach cancers, hematencephalon, COPD and normal population: A preliminary study.

PubMed

Gai, Liping; Liu, Hui; Cui, Jing-Hui; Yu, Weijian; Ding, Xiao-Dong

2017-03-20

The purpose of this study was to examine the specific allele combinations of three loci connected with the liver cancers, stomach cancers, hematencephalon and patients with chronic obstructive pulmonary disease (COPD) and to explore the feasibility of the research methods. We explored different mathematical methods for statistical analyses to assess the association between the genotype and phenotype. At the same time we still analyses the statistical results of allele combinations of three loci by difference value method and ratio method. All the DNA blood samples were collected from patients with 50 liver cancers, 75 stomach cancers, 50 hematencephalon, 72 COPD and 200 normal populations. All the samples were from Chinese. Alleles from short tandem repeat (STR) loci were determined using the STR Profiler plus PCR amplification kit (15 STR loci). Previous research was based on combinations of single-locus alleles, and combinations of cross-loci (two loci) alleles. Allele combinations of three loci were obtained by computer counting and stronger genetic signal was obtained. The methods of allele combinations of three loci can help to identify the statistically significant differences of allele combinations between liver cancers, stomach cancers, patients with hematencephalon, COPD and the normal population. The probability of illness followed different rules and had apparent specificity. This method can be extended to other diseases and provide reference for early clinical diagnosis. Copyright © 2016. Published by Elsevier B.V.

Toward Reflective Judgment in Exploratory Factor Analysis Decisions: Determining the Extraction Method and Number of Factors To Retain.

ERIC Educational Resources Information Center

Knight, Jennifer L.

This paper considers some decisions that must be made by the researcher conducting an exploratory factor analysis. The primary purpose is to aid the researcher in making informed decisions during the factor analysis instead of relying on defaults in statistical programs or traditions of previous researchers. Three decision areas are addressed.…

Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

PubMed

Ma, Yan; Mazumdar, Madhu

2011-10-30

Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

Misrepresenting random sampling? A systematic review of research papers in the Journal of Advanced Nursing.

PubMed

Williamson, Graham R

2003-11-01

This paper discusses the theoretical limitations of the use of random sampling and probability theory in the production of a significance level (or P-value) in nursing research. Potential alternatives, in the form of randomization tests, are proposed. Research papers in nursing, medicine and psychology frequently misrepresent their statistical findings, as the P-values reported assume random sampling. In this systematic review of studies published between January 1995 and June 2002 in the Journal of Advanced Nursing, 89 (68%) studies broke this assumption because they used convenience samples or entire populations. As a result, some of the findings may be questionable. The key ideas of random sampling and probability theory for statistical testing (for generating a P-value) are outlined. The result of a systematic review of research papers published in the Journal of Advanced Nursing is then presented, showing how frequently random sampling appears to have been misrepresented. Useful alternative techniques that might overcome these limitations are then discussed. REVIEW LIMITATIONS: This review is limited in scope because it is applied to one journal, and so the findings cannot be generalized to other nursing journals or to nursing research in general. However, it is possible that other nursing journals are also publishing research articles based on the misrepresentation of random sampling. The review is also limited because in several of the articles the sampling method was not completely clearly stated, and in this circumstance a judgment has been made as to the sampling method employed, based on the indications given by author(s). Quantitative researchers in nursing should be very careful that the statistical techniques they use are appropriate for the design and sampling methods of their studies. If the techniques they employ are not appropriate, they run the risk of misinterpreting findings by using inappropriate, unrepresentative and biased samples.

Building the Community Online Resource for Statistical Seismicity Analysis (CORSSA)

NASA Astrophysics Data System (ADS)

Michael, A. J.; Wiemer, S.; Zechar, J. D.; Hardebeck, J. L.; Naylor, M.; Zhuang, J.; Steacy, S.; Corssa Executive Committee

2010-12-01

Statistical seismology is critical to the understanding of seismicity, the testing of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology - especially to those aspects with great impact on public policy - statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA). CORSSA is a web-based educational platform that is authoritative, up-to-date, prominent, and user-friendly. We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each containing between four and eight articles. The CORSSA web page, www.corssa.org, officially unveiled on September 6, 2010, debuts with an initial set of approximately 10 to 15 articles available online for viewing and commenting with additional articles to be added over the coming months. Each article will be peer-reviewed and will present a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles will include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. A special article will compare and review available statistical seismology software packages.

Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

PubMed

Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

2016-01-01

Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Development of a Probabilistic Component Mode Synthesis Method for the Analysis of Non-Deterministic Substructures

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1995-01-01

Standard methods of structural dynamic analysis assume that the structural characteristics are deterministic. Recognizing that these characteristics are actually statistical in nature, researchers have recently developed a variety of methods that use this information to determine probabilities of a desired response characteristic, such as natural frequency, without using expensive Monte Carlo simulations. One of the problems in these methods is correctly identifying the statistical properties of primitive variables such as geometry, stiffness, and mass. This paper presents a method where the measured dynamic properties of substructures are used instead as the random variables. The residual flexibility method of component mode synthesis is combined with the probabilistic methods to determine the cumulative distribution function of the system eigenvalues. A simple cantilever beam test problem is presented that illustrates the theory.

A Review and Comparison of Methods for Recreating Individual Patient Data from Published Kaplan-Meier Survival Curves for Economic Evaluations: A Simulation Study

PubMed Central

Wan, Xiaomin; Peng, Liubao; Li, Yuanjian

2015-01-01

Background In general, the individual patient-level data (IPD) collected in clinical trials are not available to independent researchers to conduct economic evaluations; researchers only have access to published survival curves and summary statistics. Thus, methods that use published survival curves and summary statistics to reproduce statistics for economic evaluations are essential. Four methods have been identified: two traditional methods 1) least squares method, 2) graphical method; and two recently proposed methods by 3) Hoyle and Henley, 4) Guyot et al. The four methods were first individually reviewed and subsequently assessed regarding their abilities to estimate mean survival through a simulation study. Methods A number of different scenarios were developed that comprised combinations of various sample sizes, censoring rates and parametric survival distributions. One thousand simulated survival datasets were generated for each scenario, and all methods were applied to actual IPD. The uncertainty in the estimate of mean survival time was also captured. Results All methods provided accurate estimates of the mean survival time when the sample size was 500 and a Weibull distribution was used. When the sample size was 100 and the Weibull distribution was used, the Guyot et al. method was almost as accurate as the Hoyle and Henley method; however, more biases were identified in the traditional methods. When a lognormal distribution was used, the Guyot et al. method generated noticeably less bias and a more accurate uncertainty compared with the Hoyle and Henley method. Conclusions The traditional methods should not be preferred because of their remarkable overestimation. When the Weibull distribution was used for a fitted model, the Guyot et al. method was almost as accurate as the Hoyle and Henley method. However, if the lognormal distribution was used, the Guyot et al. method was less biased compared with the Hoyle and Henley method. PMID:25803659

Measuring post-secondary stem majors' engagement in sustainability: The creation, assessment, and validation of an instrument for sustainability curricula evaluation

NASA Astrophysics Data System (ADS)

Little, David L., II

Ongoing changes in values, pedagogy, and curriculum concerning sustainability education necessitate that strong curricular elements are identified in sustainability education. However, quantitative research in sustainability education is largely undeveloped or relies on outdated instruments. In part, this is because no widespread quantitative instrument for measuring related educational outcomes has been developed for the field, though their development is pivotal for future efforts in sustainability education related to STEM majors. This research study details the creation, evaluation, and validation of an instrument -- the STEM Sustainability Engagement Instrument (STEMSEI) -- designed to measure sustainability engagement in post-secondary STEM majors. The study was conducted in three phases, using qualitative methods in phase 1, a concurrent mixed methods design in phase 2, and a sequential mixed methods design in phase 3. The STEMSEI was able to successfully predict statistically significant differences in the sample (n= 1017) that were predicted by prior research in environmental education. The STEMSEI also revealed statistically significant differences between STEM majors' sustainability engagement with a large effect size (.203 ≤ eta2 ≤ .211). As hypothesized, statistically significant differences were found on the environmental scales across gender and present religion. With respect to gender, self-perceived measures of emotional engagement with environmental sustainability was higher with females while males had higher measures in cognitive engagement with respect to knowing information related to environmental sustainability. With respect to present religion, self-perceived measures of general engagement and emotional engagement in environmental sustainability were higher for non-Christians as compared to Christians. On the economic scales, statistically significant differences were found across gender. Specifically, measures of males' self-perceived cognitive engagement in knowing information related to economic sustainability were greater than those of females. Future research should establish the generalizability of these results and further test the validity of the STEMSEI.

A Monte Carlo Simulation Comparing the Statistical Precision of Two High-Stakes Teacher Evaluation Methods: A Value-Added Model and a Composite Measure

ERIC Educational Resources Information Center

Spencer, Bryden

2016-01-01

Value-added models are a class of growth models used in education to assign responsibility for student growth to teachers or schools. For value-added models to be used fairly, sufficient statistical precision is necessary for accurate teacher classification. Previous research indicated precision below practical limits. An alternative approach has…

A Review of the Study Designs and Statistical Methods Used in the Determination of Predictors of All-Cause Mortality in HIV-Infected Cohorts: 2002–2011

PubMed Central

Otwombe, Kennedy N.; Petzold, Max; Martinson, Neil; Chirwa, Tobias

2014-01-01

Background Research in the predictors of all-cause mortality in HIV-infected people has widely been reported in literature. Making an informed decision requires understanding the methods used. Objectives We present a review on study designs, statistical methods and their appropriateness in original articles reporting on predictors of all-cause mortality in HIV-infected people between January 2002 and December 2011. Statistical methods were compared between 2002–2006 and 2007–2011. Time-to-event analysis techniques were considered appropriate. Data Sources Pubmed/Medline. Study Eligibility Criteria Original English-language articles were abstracted. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports and any other ineligible articles were excluded. Results A total of 189 studies were identified (n = 91 in 2002–2006 and n = 98 in 2007–2011) out of which 130 (69%) were prospective and 56 (30%) were retrospective. One hundred and eighty-two (96%) studies described their sample using descriptive statistics while 32 (17%) made comparisons using t-tests. Kaplan-Meier methods for time-to-event analysis were commonly used in the earlier period (n = 69, 76% vs. n = 53, 54%, p = 0.002). Predictors of mortality in the two periods were commonly determined using Cox regression analysis (n = 67, 75% vs. n = 63, 64%, p = 0.12). Only 7 (4%) used advanced survival analysis methods of Cox regression analysis with frailty in which 6 (3%) were used in the later period. Thirty-two (17%) used logistic regression while 8 (4%) used other methods. There were significantly more articles from the first period using appropriate methods compared to the second (n = 80, 88% vs. n = 69, 70%, p-value = 0.003). Conclusion Descriptive statistics and survival analysis techniques remain the most common methods of analysis in publications on predictors of all-cause mortality in HIV-infected cohorts while prospective research designs are favoured. Sophisticated techniques of time-dependent Cox regression and Cox regression with frailty are scarce. This motivates for more training in the use of advanced time-to-event methods. PMID:24498313

A review and comparison of methods for recreating individual patient data from published Kaplan-Meier survival curves for economic evaluations: a simulation study.

PubMed

Wan, Xiaomin; Peng, Liubao; Li, Yuanjian

2015-01-01

In general, the individual patient-level data (IPD) collected in clinical trials are not available to independent researchers to conduct economic evaluations; researchers only have access to published survival curves and summary statistics. Thus, methods that use published survival curves and summary statistics to reproduce statistics for economic evaluations are essential. Four methods have been identified: two traditional methods 1) least squares method, 2) graphical method; and two recently proposed methods by 3) Hoyle and Henley, 4) Guyot et al. The four methods were first individually reviewed and subsequently assessed regarding their abilities to estimate mean survival through a simulation study. A number of different scenarios were developed that comprised combinations of various sample sizes, censoring rates and parametric survival distributions. One thousand simulated survival datasets were generated for each scenario, and all methods were applied to actual IPD. The uncertainty in the estimate of mean survival time was also captured. All methods provided accurate estimates of the mean survival time when the sample size was 500 and a Weibull distribution was used. When the sample size was 100 and the Weibull distribution was used, the Guyot et al. method was almost as accurate as the Hoyle and Henley method; however, more biases were identified in the traditional methods. When a lognormal distribution was used, the Guyot et al. method generated noticeably less bias and a more accurate uncertainty compared with the Hoyle and Henley method. The traditional methods should not be preferred because of their remarkable overestimation. When the Weibull distribution was used for a fitted model, the Guyot et al. method was almost as accurate as the Hoyle and Henley method. However, if the lognormal distribution was used, the Guyot et al. method was less biased compared with the Hoyle and Henley method.

A Comparison of Didactic and Inquiry Teaching Methods in a Rural Community College Earth Science Course

NASA Astrophysics Data System (ADS)

Beam, Margery Elizabeth

The combination of increasing enrollment and the importance of providing transfer students a solid foundation in science calls for science faculty to evaluate teaching methods in rural community colleges. The purpose of this study was to examine and compare the effectiveness of two teaching methods, inquiry teaching methods and didactic teaching methods, applied in a rural community college earth science course. Two groups of students were taught the same content via inquiry and didactic teaching methods. Analysis of quantitative data included a non-parametric ranking statistical testing method in which the difference between the rankings and the median of the post-test scores was analyzed for significance. Results indicated there was not a significant statistical difference between the teaching methods for the group of students participating in the research. The practical and educational significance of this study provides valuable perspectives on teaching methods and student learning styles in rural community colleges.

A Comparison of Approaches for Setting Proficiency Standards.

ERIC Educational Resources Information Center

Koffler, Stephen L.

This research compared the cut-off scores estimated from an empirical procedure (Contrasting group method) to those determined from a more theoretical process (Nedelsky method). A methodological and statistical framework was also provided for analysis of the data to obtain the most appropriate standard using the empirical procedure. Data were…

78 FR 57860 - Draft NIH Genomic Data Sharing Policy Request for Public Comments

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-20

... underlying disease, development of statistical research methods, the study of populations origins). If so... community will be notified through appropriate communication methods (e.g., The NIH Guide for Grants and... Sharing Policy Request for Public Comments SUMMARY: The National Institutes of Health (NIH) is seeking...

A Comparison of Normal and Elliptical Estimation Methods in Structural Equation Models.

ERIC Educational Resources Information Center

Schumacker, Randall E.; Cheevatanarak, Suchittra

Monte Carlo simulation compared chi-square statistics, parameter estimates, and root mean square error of approximation values using normal and elliptical estimation methods. Three research conditions were imposed on the simulated data: sample size, population contamination percent, and kurtosis. A Bentler-Weeks structural model established the…

Efficient computational methods to study new and innovative signal detection techniques in SETI

NASA Technical Reports Server (NTRS)

Deans, Stanley R.

1991-01-01

The purpose of the research reported here is to provide a rapid computational method for computing various statistical parameters associated with overlapped Hann spectra. These results are important for the Targeted Search part of the Search for ExtraTerrestrial Intelligence (SETI) Microwave Observing Project.

Statistical learning theory for high dimensional prediction: Application to criterion-keyed scale development.

PubMed

Chapman, Benjamin P; Weiss, Alexander; Duberstein, Paul R

2016-12-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in "big data" problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how 3 common SLT algorithms-supervised principal components, regularization, and boosting-can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach-or perhaps because of them-SLT methods may hold value as a statistically rigorous approach to exploratory regression. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Diffusion-Based Density-Equalizing Maps: an Interdisciplinary Approach to Visualizing Homicide Rates and Other Georeferenced Statistical Data

NASA Astrophysics Data System (ADS)

Mazzitello, Karina I.; Candia, Julián

2012-12-01

In every country, public and private agencies allocate extensive funding to collect large-scale statistical data, which in turn are studied and analyzed in order to determine local, regional, national, and international policies regarding all aspects relevant to the welfare of society. One important aspect of that process is the visualization of statistical data with embedded geographical information, which most often relies on archaic methods such as maps colored according to graded scales. In this work, we apply nonstandard visualization techniques based on physical principles. We illustrate the method with recent statistics on homicide rates in Brazil and their correlation to other publicly available data. This physics-based approach provides a novel tool that can be used by interdisciplinary teams investigating statistics and model projections in a variety of fields such as economics and gross domestic product research, public health and epidemiology, sociodemographics, political science, business and marketing, and many others.

Accumuler le capital humain tout au long de la vie: Quels facteurs prédictifs de la participation à la formation permanente?

NASA Astrophysics Data System (ADS)

Boudard, Emmanuel; Morlaix, Sophie

2003-09-01

This article addresses the main predictors of adult education, using statistical methods different from those generally used by social science researchers. Its aim is twofold. First, it seeks to explain in a simple and comprehensible manner the methodological value of these methods (in relation to the use of structural models); secondly, it demonstrates the concrete usefulness of these methods on the basis of a recent piece of research on the data from the International Adult Literacy Survey (IALS).

TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data.

PubMed

Lim, Jae Hyun; Lee, Soo Youn; Kim, Ju Han

2017-03-01

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

An operational definition of a statistically meaningful trend.

PubMed

Bryhn, Andreas C; Dimberg, Peter H

2011-04-28

Linear trend analysis of time series is standard procedure in many scientific disciplines. If the number of data is large, a trend may be statistically significant even if data are scattered far from the trend line. This study introduces and tests a quality criterion for time trends referred to as statistical meaningfulness, which is a stricter quality criterion for trends than high statistical significance. The time series is divided into intervals and interval mean values are calculated. Thereafter, r(2) and p values are calculated from regressions concerning time and interval mean values. If r(2) ≥ 0.65 at p ≤ 0.05 in any of these regressions, then the trend is regarded as statistically meaningful. Out of ten investigated time series from different scientific disciplines, five displayed statistically meaningful trends. A Microsoft Excel application (add-in) was developed which can perform statistical meaningfulness tests and which may increase the operationality of the test. The presented method for distinguishing statistically meaningful trends should be reasonably uncomplicated for researchers with basic statistics skills and may thus be useful for determining which trends are worth analysing further, for instance with respect to causal factors. The method can also be used for determining which segments of a time trend may be particularly worthwhile to focus on.

Statistical Analysis of the Uncertainty in Pre-Flight Aerodynamic Database of a Hypersonic Vehicle

NASA Astrophysics Data System (ADS)

Huh, Lynn

The objective of the present research was to develop a new method to derive the aerodynamic coefficients and the associated uncertainties for flight vehicles via post- flight inertial navigation analysis using data from the inertial measurement unit. Statistical estimates of vehicle state and aerodynamic coefficients are derived using Monte Carlo simulation. Trajectory reconstruction using the inertial navigation system (INS) is a simple and well used method. However, deriving realistic uncertainties in the reconstructed state and any associated parameters is not so straight forward. Extended Kalman filters, batch minimum variance estimation and other approaches have been used. However, these methods generally depend on assumed physical models, assumed statistical distributions (usually Gaussian) or have convergence issues for non-linear problems. The approach here assumes no physical models, is applicable to any statistical distribution, and does not have any convergence issues. The new approach obtains the statistics directly from a sufficient number of Monte Carlo samples using only the generally well known gyro and accelerometer specifications and could be applied to the systems of non-linear form and non-Gaussian distribution. When redundant data are available, the set of Monte Carlo simulations are constrained to satisfy the redundant data within the uncertainties specified for the additional data. The proposed method was applied to validate the uncertainty in the pre-flight aerodynamic database of the X-43A Hyper-X research vehicle. In addition to gyro and acceleration data, the actual flight data include redundant measurements of position and velocity from the global positioning system (GPS). The criteria derived from the blend of the GPS and INS accuracy was used to select valid trajectories for statistical analysis. The aerodynamic coefficients were derived from the selected trajectories by either direct extraction method based on the equations in dynamics, or by the inquiry of the pre-flight aerodynamic database. After the application of the proposed method to the case of the X-43A Hyper-X research vehicle, it was found that 1) there were consistent differences in the aerodynamic coefficients from the pre-flight aerodynamic database and post-flight analysis, 2) the pre-flight estimation of the pitching moment coefficients was significantly different from the post-flight analysis, 3) the type of distribution of the states from the Monte Carlo simulation were affected by that of the perturbation parameters, 4) the uncertainties in the pre-flight model were overestimated, 5) the range where the aerodynamic coefficients from the pre-flight aerodynamic database and post-flight analysis are in closest agreement is between Mach *.* and *.* and more data points may be needed between Mach * and ** in the pre-flight aerodynamic database, 6) selection criterion for valid trajectories from the Monte Carlo simulations was mostly driven by the horizontal velocity error, 7) the selection criterion must be based on reasonable model to ensure the validity of the statistics from the proposed method, and 8) the results from the proposed method applied to the two different flights with the identical geometry and similar flight profile were consistent.

Analysis of nonintervention studies: technical supplement.

PubMed

Aickin, Mikel

2012-01-01

Methods for analyzing data in nonintervention clinical studies are substantially different from those that are appropriate for randomized clinical trials. Although the latter methods are well known, the former are not. A systematic approach for dealing with statistical confounding in nonintervention research has been developed over the past 30 to 40 years, and the essence of this theory constitutes the contents of this article. An accompanying, less technical article explains the implications of these results for clinical research.

Characterizing the D2 statistic: word matches in biological sequences.

PubMed

Forêt, Sylvain; Wilson, Susan R; Burden, Conrad J

2009-01-01

Word matches are often used in sequence comparison methods, either as a measure of sequence similarity or in the first search steps of algorithms such as BLAST or BLAT. The D2 statistic is the number of matches of words of k letters between two sequences. Recent advances have been made in the characterization of this statistic and in the approximation of its distribution. Here, these results are extended to the case of approximate word matches. We compute the exact value of the variance of the D2 statistic for the case of a uniform letter distribution, and introduce a method to provide accurate approximations of the variance in the remaining cases. This enables the distribution of D2 to be approximated for typical situations arising in biological research. We apply these results to the identification of cis-regulatory modules, and show that this method detects such sequences with a high accuracy. The ability to approximate the distribution of D2 for both exact and approximate word matches will enable the use of this statistic in a more precise manner for sequence comparison, database searches, and identification of transcription factor binding sites.

Spatial scan statistics for detection of multiple clusters with arbitrary shapes.

PubMed

Lin, Pei-Sheng; Kung, Yi-Hung; Clayton, Murray

2016-12-01

In applying scan statistics for public health research, it would be valuable to develop a detection method for multiple clusters that accommodates spatial correlation and covariate effects in an integrated model. In this article, we connect the concepts of the likelihood ratio (LR) scan statistic and the quasi-likelihood (QL) scan statistic to provide a series of detection procedures sufficiently flexible to apply to clusters of arbitrary shape. First, we use an independent scan model for detection of clusters and then a variogram tool to examine the existence of spatial correlation and regional variation based on residuals of the independent scan model. When the estimate of regional variation is significantly different from zero, a mixed QL estimating equation is developed to estimate coefficients of geographic clusters and covariates. We use the Benjamini-Hochberg procedure (1995) to find a threshold for p-values to address the multiple testing problem. A quasi-deviance criterion is used to regroup the estimated clusters to find geographic clusters with arbitrary shapes. We conduct simulations to compare the performance of the proposed method with other scan statistics. For illustration, the method is applied to enterovirus data from Taiwan. © 2016, The International Biometric Society.

[How to start a neuroimaging study].

PubMed

Narumoto, Jin

2012-06-01

In order to help researchers understand how to start a neuroimaging study, several tips are described in this paper. These include 1) Choice of an imaging modality, 2) Statistical method, and 3) Interpretation of the results. 1) There are several imaging modalities available in clinical research. Advantages and disadvantages of each modality are described. 2) Statistical Parametric Mapping, which is the most common statistical software for neuroimaging analysis, is described in terms of parameter setting in normalization and level of significance. 3) In the discussion section, the region which shows a significant difference between patients and normal controls should be discussed in relation to the neurophysiology of the disease, making reference to previous reports from neuroimaging studies in normal controls, lesion studies and animal studies. A typical pattern of discussion is described.

Mathematical problem solving ability of sport students in the statistical study

NASA Astrophysics Data System (ADS)

Sari, E. F. P.; Zulkardi; Putri, R. I. I.

2017-12-01

This study aims to determine the problem-solving ability of sport students of PGRI Palembang semester V in the statistics course. Subjects in this study were sport students of PGRI Palembang semester V which amounted to 31 people. The research method used is quasi experiment type one case shoot study. Data collection techniques in this study use the test and data analysis used is quantitative descriptive statistics. The conclusion of this study shown that the mathematical problem solving ability of PGRI Palembang sport students of V semester in the statistical course is categorized well with the average of the final test score of 80.3.

Computer-assisted qualitative data analysis software.

PubMed

Cope, Diane G

2014-05-01

Advances in technology have provided new approaches for data collection methods and analysis for researchers. Data collection is no longer limited to paper-and-pencil format, and numerous methods are now available through Internet and electronic resources. With these techniques, researchers are not burdened with entering data manually and data analysis is facilitated by software programs. Quantitative research is supported by the use of computer software and provides ease in the management of large data sets and rapid analysis of numeric statistical methods. New technologies are emerging to support qualitative research with the availability of computer-assisted qualitative data analysis software (CAQDAS).CAQDAS will be presented with a discussion of advantages, limitations, controversial issues, and recommendations for this type of software use.

The Politics and Statistics of Value-Added Modeling for Accountability of Teacher Preparation Programs

ERIC Educational Resources Information Center

Lincove, Jane Arnold; Osborne, Cynthia; Dillon, Amanda; Mills, Nicholas

2014-01-01

Despite questions about validity and reliability, the use of value-added estimation methods has moved beyond academic research into state accountability systems for teachers, schools, and teacher preparation programs (TPPs). Prior studies of value-added measurement for TPPs test the validity of researcher-designed models and find that measuring…

Using Interactive "Shiny" Applications to Facilitate Research-Informed Learning and Teaching

ERIC Educational Resources Information Center

Fawcett, Lee

2018-01-01

In this article we discuss our attempt to incorporate research-informed learning and teaching activities into a final year undergraduate Statistics course. We make use of the Shiny web-based application framework for R to develop "Shiny apps" designed to help facilitate student interaction with methods from recently published papers in…

Using Cluster Analysis for Data Mining in Educational Technology Research

ERIC Educational Resources Information Center

Antonenko, Pavlo D.; Toy, Serkan; Niederhauser, Dale S.

2012-01-01

Cluster analysis is a group of statistical methods that has great potential for analyzing the vast amounts of web server-log data to understand student learning from hyperlinked information resources. In this methodological paper we provide an introduction to cluster analysis for educational technology researchers and illustrate its use through…

From Research and Relaxation to Combination and Creativity: American Versions of Suggestopedia.

ERIC Educational Resources Information Center

Bancroft, W. Jane

In the early 1970s, American educators commenced experiments on Suggestopedia. Educational psychologists enlarged upon the relaxation and visualizations contained in the Bulgarian method and provided a solid, statistical basis to Suggestopedic research. Part I of this paper discusses the contribution of Donald Schuster, and his development of…

How Social Network Position Relates to Knowledge Building in Online Learning Communities

ERIC Educational Resources Information Center

Wang, Lu

2010-01-01

Social Network Analysis, Statistical Analysis, Content Analysis and other research methods were used to research online learning communities at Capital Normal University, Beijing. Analysis of the two online courses resulted in the following conclusions: (1) Social networks of the two online courses form typical core-periphery structures; (2)…

Outlier Detection in High-Stakes Certification Testing. Research Report.

ERIC Educational Resources Information Center

Meijer, Rob R.

Recent developments of person-fit analysis in computerized adaptive testing (CAT) are discussed. Methods from statistical process control are presented that have been proposed to classify an item score pattern as fitting or misfitting the underlying item response theory (IRT) model in a CAT. Most person-fit research in CAT is restricted to…

Have the Focus and Sophistication of Research in Health Education Changed?

ERIC Educational Resources Information Center

Merrill, Ray M.; Lindsay, Christopher A.; Shields, Eric C.; Stoddard, Julianne

2007-01-01

This study assessed the types of research and the statistical methods used in three representative health education journals from 1994 through 2003. Editorials, commentaries, program/practice notes, and perspectives represent 17.6% of the journals' content. The most common types of articles are cross-sectional studies (27.5%), reviews (23.2%), and…

Identifying future research needs in landscape genetics: Where to from here?

Treesearch

Niko Balkenhol; Felix Gugerli; Sam A. Cushman; Lisette P. Waits; Aurelie Coulon; J. W. Arntzen; Rolf Holderegger; Helene H. Wagner

2009-01-01

Landscape genetics is an emerging interdisciplinary field that combines methods and concepts from population genetics, landscape ecology, and spatial statistics. The interest in landscape genetics is steadily increasing, and the field is evolving rapidly. We here outline four major challenges for future landscape genetic research that were identified during an...

Collaborative Writing in a Statistics and Research Methods Course.

ERIC Educational Resources Information Center

Dunn, Dana S.

1996-01-01

Describes a collaborative writing project in which students must identify key variables, search and read relevant literature, and reason through a research idea by working closely with a partner. The end result is a polished laboratory report in the APA style. The class includes a peer review workshop prior to final editing. (MJP)

Nuclear magnetic resonance (NMR)-based metabolomics for cancer research.

PubMed

Ranjan, Renuka; Sinha, Neeraj

2018-05-07

Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research. Copyright © 2018 John Wiley & Sons, Ltd.

Health care research by degrees N Reid Health care research by degrees Blackwell Scientific 162pp £13.99 0632-03466-1 [Formula: see text].

PubMed

1993-03-03

Inadequately understood statistics so often cloud both the argument of the researcher and the judgement of the reader. Norma Reid brings a refreshing clarity to a complex topic; she takes the mystification and mystique out of statistics. Her basic premiss that theory ought to be based on practical utility and relevance shines through her text and helps to make the subject accessible co clinicians who want to understand the underpinnings of their practice. Research methods, particularly qualitative approaches, are sketchily dealt with when compared with the wealth of detail on the mechanics of computing. Also, it is awkward to find methods and analysis not clearly separated in places (eg, Delphi studies), but ample references direct the reader to more expansive sources. Any attempt to steer the uninitiated through the minefields of computing is fraught with difficulties, and some will be disappointed to find one system used exclusively, but, perhaps, it serves as an illustration rather than a course to be slavishly followed.

The multiple imputation method: a case study involving secondary data analysis.

PubMed

Walani, Salimah R; Cleland, Charles M

2015-05-01

To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

Application of multivariate statistical techniques in microbial ecology

PubMed Central

Paliy, O.; Shankar, V.

2016-01-01

Recent advances in high-throughput methods of molecular analyses have led to an explosion of studies generating large scale ecological datasets. Especially noticeable effect has been attained in the field of microbial ecology, where new experimental approaches provided in-depth assessments of the composition, functions, and dynamic changes of complex microbial communities. Because even a single high-throughput experiment produces large amounts of data, powerful statistical techniques of multivariate analysis are well suited to analyze and interpret these datasets. Many different multivariate techniques are available, and often it is not clear which method should be applied to a particular dataset. In this review we describe and compare the most widely used multivariate statistical techniques including exploratory, interpretive, and discriminatory procedures. We consider several important limitations and assumptions of these methods, and we present examples of how these approaches have been utilized in recent studies to provide insight into the ecology of the microbial world. Finally, we offer suggestions for the selection of appropriate methods based on the research question and dataset structure. PMID:26786791

Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part II. Statistical Methods of Meta-Analysis

PubMed Central

Lee, Juneyoung; Kim, Kyung Won; Choi, Sang Hyun; Huh, Jimi

2015-01-01

Meta-analysis of diagnostic test accuracy studies differs from the usual meta-analysis of therapeutic/interventional studies in that, it is required to simultaneously analyze a pair of two outcome measures such as sensitivity and specificity, instead of a single outcome. Since sensitivity and specificity are generally inversely correlated and could be affected by a threshold effect, more sophisticated statistical methods are required for the meta-analysis of diagnostic test accuracy. Hierarchical models including the bivariate model and the hierarchical summary receiver operating characteristic model are increasingly being accepted as standard methods for meta-analysis of diagnostic test accuracy studies. We provide a conceptual review of statistical methods currently used and recommended for meta-analysis of diagnostic test accuracy studies. This article could serve as a methodological reference for those who perform systematic review and meta-analysis of diagnostic test accuracy studies. PMID:26576107

Examination of the Equivalence of Self-Report Survey-Based Paper-and-Pencil and Internet Data Collection Methods

ERIC Educational Resources Information Center

Weigold, Arne; Weigold, Ingrid K.; Russell, Elizabeth J.

2013-01-01

Self-report survey-based data collection is increasingly carried out using the Internet, as opposed to the traditional paper-and-pencil method. However, previous research on the equivalence of these methods has yielded inconsistent findings. This may be due to methodological and statistical issues present in much of the literature, such as…

[Evaluation of the results of clinical trials using a new non-statistical method].

PubMed

Zofková, I

1994-04-04

The author presents information on the possibilities and some advantages associated with the application of a new nonstatistical (gnostic) method for evaluation of results in clinical trials. The mentioned method is among other properties very robust, i.e. suited for evaluation of small groups of highly scattered data, a situation very frequently encountered in clinical research.

Application of Bayesian methods to habitat selection modeling of the northern spotted owl in California: new statistical methods for wildlife research

Treesearch

Howard B. Stauffer; Cynthia J. Zabel; Jeffrey R. Dunk

2005-01-01

We compared a set of competing logistic regression habitat selection models for Northern Spotted Owls (Strix occidentalis caurina) in California. The habitat selection models were estimated, compared, evaluated, and tested using multiple sample datasets collected on federal forestlands in northern California. We used Bayesian methods in interpreting...

Directly assessing interpersonal RSA influences in the frequency domain: An illustration with generalized partial directed coherence.

PubMed

Liu, Siwei; Gates, Kathleen M; Blandon, Alysia Y

2018-06-01

Despite recent research indicating that interpersonal linkage in physiology is a common phenomenon during social interactions, and the well-established role of respiratory sinus arrhythmia (RSA) in socially facilitative physiological regulation, little research has directly examined interpersonal influences in RSA, perhaps due to methodological challenges in analyzing multivariate RSA data. In this article, we aim to bridge this methodological gap by introducing a new method for quantifying interpersonal RSA influences. Specifically, we show that a frequency-domain statistic, generalized partial directed coherence (gPDC), can be used to capture lagged relations in RSA between social partners without first estimating RSA for each person. We illustrate its utility by examining the relation between gPDC and marital conflict in a sample of married couples. Finally, we discuss how gPDC complements existing methods in the time domain and provide guidelines for choosing among these different statistical techniques. © 2018 Society for Psychophysiological Research.

A novel approach to generating CER hypotheses based on mining clinical data.

PubMed

Zhang, Shuo; Li, Lin; Yu, Yiqin; Sun, Xingzhi; Xu, Linhao; Zhao, Wei; Teng, Xiaofei; Pan, Yue

2013-01-01

Comparative effectiveness research (CER) is a scientific method of investigating the effectiveness of alternative intervention methods. In a CER study, clinical researchers typically start with a CER hypothesis, and aim to evaluate it by applying a series of medical statistical methods. Traditionally, the CER hypotheses are defined manually by clinical researchers. This makes the task of hypothesis generation very time-consuming and the quality of hypothesis heavily dependent on the researchers' skills. Recently, with more electronic medical data being collected, it is highly promising to apply the computerized method for discovering CER hypotheses from clinical data sets. In this poster, we proposes a novel approach to automatically generating CER hypotheses based on mining clinical data, and presents a case study showing that the approach can facilitate clinical researchers to identify potentially valuable hypotheses and eventually define high quality CER studies.

Classical Statistics and Statistical Learning in Imaging Neuroscience

PubMed Central

Bzdok, Danilo

2017-01-01

Brain-imaging research has predominantly generated insight by means of classical statistics, including regression-type analyses and null-hypothesis testing using t-test and ANOVA. Throughout recent years, statistical learning methods enjoy increasing popularity especially for applications in rich and complex data, including cross-validated out-of-sample prediction using pattern classification and sparsity-inducing regression. This concept paper discusses the implications of inferential justifications and algorithmic methodologies in common data analysis scenarios in neuroimaging. It is retraced how classical statistics and statistical learning originated from different historical contexts, build on different theoretical foundations, make different assumptions, and evaluate different outcome metrics to permit differently nuanced conclusions. The present considerations should help reduce current confusion between model-driven classical hypothesis testing and data-driven learning algorithms for investigating the brain with imaging techniques. PMID:29056896

PREFACE: Advanced many-body and statistical methods in mesoscopic systems

NASA Astrophysics Data System (ADS)

Anghel, Dragos Victor; Sabin Delion, Doru; Sorin Paraoanu, Gheorghe

2012-02-01

It has increasingly been realized in recent times that the borders separating various subfields of physics are largely artificial. This is the case for nanoscale physics, physics of lower-dimensional systems and nuclear physics, where the advanced techniques of many-body theory developed in recent times could provide a unifying framework for these disciplines under the general name of mesoscopic physics. Other fields, such as quantum optics and quantum information, are increasingly using related methods. The 6-day conference 'Advanced many-body and statistical methods in mesoscopic systems' that took place in Constanta, Romania, between 27 June and 2 July 2011 was, we believe, a successful attempt at bridging an impressive list of topical research areas: foundations of quantum physics, equilibrium and non-equilibrium quantum statistics/fractional statistics, quantum transport, phases and phase transitions in mesoscopic systems/superfluidity and superconductivity, quantum electromechanical systems, quantum dissipation, dephasing, noise and decoherence, quantum information, spin systems and their dynamics, fundamental symmetries in mesoscopic systems, phase transitions, exactly solvable methods for mesoscopic systems, various extension of the random phase approximation, open quantum systems, clustering, decay and fission modes and systematic versus random behaviour of nuclear spectra. This event brought together participants from seventeen countries and five continents. Each of the participants brought considerable expertise in his/her field of research and, at the same time, was exposed to the newest results and methods coming from the other, seemingly remote, disciplines. The talks touched on subjects that are at the forefront of topical research areas and we hope that the resulting cross-fertilization of ideas will lead to new, interesting results from which everybody will benefit. We are grateful for the financial and organizational support from IFIN-HH, Ovidius University (where the conference took place), the Academy of Romanian Scientists and the Romanian National Authority for Scientific Research. This conference proceedings volume brings together some of the invited and contributed talks of the conference. The hope of the editors is that they will constitute reference material for applying many-body techniques to problems in mesoscopic and nuclear physics. We thank all the participants for their contribution to the success of this conference. D V Anghel and D S Delion IFIN-HH, Bucharest, Romania G S Paraoanu Aalto University, Finland Conference photograph

Securing wide appreciation of health statistics

PubMed Central

Pyrrait, A. M. DO Amaral; Aubenque, M. J.; Benjamin, B.; DE Groot, Meindert J. W.; Kohn, R.

1954-01-01

All the authors are agreed on the need for a certain publicizing of health statistics, but do Amaral Pyrrait points out that the medical profession prefers to convince itself rather than to be convinced. While there is great utility in articles and reviews in the professional press (especially for paramedical personnel) Aubenque, de Groot, and Kohn show how appreciation can effectively be secured by making statistics more easily understandable to the non-expert by, for instance, including readable commentaries in official publications, simplifying charts and tables, and preparing simple manuals on statistical methods. Aubenque and Kohn also stress the importance of linking health statistics to other economic and social information. Benjamin suggests that the principles of market research could to advantage be applied to health statistics to determine the precise needs of the “consumers”. At the same time, Aubenque points out that the value of the ultimate results must be clear to those who provide the data; for this, Kohn suggests that the enumerators must know exactly what is wanted and why. There is general agreement that some explanation of statistical methods and their uses should be given in the curricula of medical schools and that lectures and postgraduate courses should be arranged for practising physicians. PMID:13199668

Using generalized estimating equations and extensions in randomized trials with missing longitudinal patient reported outcome data.

PubMed

Bell, Melanie L; Horton, Nicholas J; Dhillon, Haryana M; Bray, Victoria J; Vardy, Janette

2018-05-26

Patient reported outcomes (PROs) are important in oncology research; however, missing data can pose a threat to the validity of results. Psycho-oncology researchers should be aware of the statistical options for handling missing data robustly. One rarely used set of methods, which includes extensions for handling missing data, is generalized estimating equations (GEEs). Our objective was to demonstrate use of GEEs to analyze PROs with missing data in randomized trials with assessments at fixed time points. We introduce GEEs and show, with a worked example, how to use GEEs that account for missing data: inverse probability weighted GEEs and multiple imputation with GEE. We use data from an RCT evaluating a web-based brain training for cancer survivors reporting cognitive symptoms after chemotherapy treatment. The primary outcome for this demonstration is the binary outcome of cognitive impairment. Several methods are used, and results are compared. We demonstrate that estimates can vary depending on the choice of analytical approach, with odds ratios for no cognitive impairment ranging from 2.04 to 5.74. While most of these estimates were statistically significant (P < 0.05), a few were not. Researchers using PROs should use statistical methods that handle missing data in a way as to result in unbiased estimates. GEE extensions are analytic options for handling dropouts in longitudinal RCTs, particularly if the outcome is not continuous. Copyright © 2018 John Wiley & Sons, Ltd.

Study/Experimental/Research Design: Much More Than Statistics

PubMed Central

Knight, Kenneth L.

2010-01-01

Abstract Context: The purpose of study, experimental, or research design in scientific manuscripts has changed significantly over the years. It has evolved from an explanation of the design of the experiment (ie, data gathering or acquisition) to an explanation of the statistical analysis. This practice makes “Methods” sections hard to read and understand. Objective: To clarify the difference between study design and statistical analysis, to show the advantages of a properly written study design on article comprehension, and to encourage authors to correctly describe study designs. Description: The role of study design is explored from the introduction of the concept by Fisher through modern-day scientists and the AMA Manual of Style. At one time, when experiments were simpler, the study design and statistical design were identical or very similar. With the complex research that is common today, which often includes manipulating variables to create new variables and the multiple (and different) analyses of a single data set, data collection is very different than statistical design. Thus, both a study design and a statistical design are necessary. Advantages: Scientific manuscripts will be much easier to read and comprehend. A proper experimental design serves as a road map to the study methods, helping readers to understand more clearly how the data were obtained and, therefore, assisting them in properly analyzing the results. PMID:20064054

A Statistical Testing Approach for Quantifying Software Reliability; Application to an Example System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chu, Tsong-Lun; Varuttamaseni, Athi; Baek, Joo-Seok

The U.S. Nuclear Regulatory Commission (NRC) encourages the use of probabilistic risk assessment (PRA) technology in all regulatory matters, to the extent supported by the state-of-the-art in PRA methods and data. Although much has been accomplished in the area of risk-informed regulation, risk assessment for digital systems has not been fully developed. The NRC established a plan for research on digital systems to identify and develop methods, analytical tools, and regulatory guidance for (1) including models of digital systems in the PRAs of nuclear power plants (NPPs), and (2) incorporating digital systems in the NRC's risk-informed licensing and oversight activities.more » Under NRC's sponsorship, Brookhaven National Laboratory (BNL) explored approaches for addressing the failures of digital instrumentation and control (I and C) systems in the current NPP PRA framework. Specific areas investigated included PRA modeling digital hardware, development of a philosophical basis for defining software failure, and identification of desirable attributes of quantitative software reliability methods. Based on the earlier research, statistical testing is considered a promising method for quantifying software reliability. This paper describes a statistical software testing approach for quantifying software reliability and applies it to the loop-operating control system (LOCS) of an experimental loop of the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL).« less

Instrumental variable methods in comparative safety and effectiveness research.

PubMed

Brookhart, M Alan; Rassen, Jeremy A; Schneeweiss, Sebastian

2010-06-01

Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial.

In Defense of P Values

PubMed Central

Verhulst, Brad

2016-01-01

P values have become the scapegoat for a wide variety of problems in science. P values are generally over-emphasized, often incorrectly applied, and in some cases even abused. However, alternative methods of hypothesis testing will likely fall victim to the same criticisms currently leveled at P values if more fundamental changes are not made in the research process. Increasing the general level of statistical literacy and enhancing training in statistical methods provide a potential avenue for identifying, correcting, and preventing erroneous conclusions from entering the academic literature and for improving the general quality of patient care. PMID:28366961

The critical period hypothesis in second language acquisition: a statistical critique and a reanalysis.

PubMed

Vanhove, Jan

2013-01-01

In second language acquisition research, the critical period hypothesis (cph) holds that the function between learners' age and their susceptibility to second language input is non-linear. This paper revisits the indistinctness found in the literature with regard to this hypothesis's scope and predictions. Even when its scope is clearly delineated and its predictions are spelt out, however, empirical studies-with few exceptions-use analytical (statistical) tools that are irrelevant with respect to the predictions made. This paper discusses statistical fallacies common in cph research and illustrates an alternative analytical method (piecewise regression) by means of a reanalysis of two datasets from a 2010 paper purporting to have found cross-linguistic evidence in favour of the cph. This reanalysis reveals that the specific age patterns predicted by the cph are not cross-linguistically robust. Applying the principle of parsimony, it is concluded that age patterns in second language acquisition are not governed by a critical period. To conclude, this paper highlights the role of confirmation bias in the scientific enterprise and appeals to second language acquisition researchers to reanalyse their old datasets using the methods discussed in this paper. The data and R commands that were used for the reanalysis are provided as supplementary materials.

Use of Statistical Analyses in the Ophthalmic Literature

PubMed Central

Lisboa, Renato; Meira-Freitas, Daniel; Tatham, Andrew J.; Marvasti, Amir H.; Sharpsten, Lucie; Medeiros, Felipe A.

2014-01-01

Purpose To identify the most commonly used statistical analyses in the ophthalmic literature and to determine the likely gain in comprehension of the literature that readers could expect if they were to sequentially add knowledge of more advanced techniques to their statistical repertoire. Design Cross-sectional study Methods All articles published from January 2012 to December 2012 in Ophthalmology, American Journal of Ophthalmology and Archives of Ophthalmology were reviewed. A total of 780 peer-reviewed articles were included. Two reviewers examined each article and assigned categories to each one depending on the type of statistical analyses used. Discrepancies between reviewers were resolved by consensus. Main Outcome Measures Total number and percentage of articles containing each category of statistical analysis were obtained. Additionally we estimated the accumulated number and percentage of articles that a reader would be expected to be able to interpret depending on their statistical repertoire. Results Readers with little or no statistical knowledge would be expected to be able to interpret the statistical methods presented in only 20.8% of articles. In order to understand more than half (51.4%) of the articles published, readers were expected to be familiar with at least 15 different statistical methods. Knowledge of 21 categories of statistical methods was necessary to comprehend 70.9% of articles, while knowledge of more than 29 categories was necessary to comprehend more than 90% of articles. Articles in retina and glaucoma subspecialties showed a tendency for using more complex analysis when compared to cornea. Conclusions Readers of clinical journals in ophthalmology need to have substantial knowledge of statistical methodology to understand the results of published studies in the literature. The frequency of use of complex statistical analyses also indicates that those involved in the editorial peer-review process must have sound statistical knowledge in order to critically appraise articles submitted for publication. The results of this study could provide guidance to direct the statistical learning of clinical ophthalmologists, researchers and educators involved in the design of courses for residents and medical students. PMID:24612977

A close examination of double filtering with fold change and t test in microarray analysis

PubMed Central

2009-01-01

Background Many researchers use the double filtering procedure with fold change and t test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods. Results This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while t statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure. Conclusion We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure. PMID:19995439

Applications of modern statistical methods to analysis of data in physical science

NASA Astrophysics Data System (ADS)

Wicker, James Eric

Modern methods of statistical and computational analysis offer solutions to dilemmas confronting researchers in physical science. Although the ideas behind modern statistical and computational analysis methods were originally introduced in the 1970's, most scientists still rely on methods written during the early era of computing. These researchers, who analyze increasingly voluminous and multivariate data sets, need modern analysis methods to extract the best results from their studies. The first section of this work showcases applications of modern linear regression. Since the 1960's, many researchers in spectroscopy have used classical stepwise regression techniques to derive molecular constants. However, problems with thresholds of entry and exit for model variables plagues this analysis method. Other criticisms of this kind of stepwise procedure include its inefficient searching method, the order in which variables enter or leave the model and problems with overfitting data. We implement an information scoring technique that overcomes the assumptions inherent in the stepwise regression process to calculate molecular model parameters. We believe that this kind of information based model evaluation can be applied to more general analysis situations in physical science. The second section proposes new methods of multivariate cluster analysis. The K-means algorithm and the EM algorithm, introduced in the 1960's and 1970's respectively, formed the basis of multivariate cluster analysis methodology for many years. However, several shortcomings of these methods include strong dependence on initial seed values and inaccurate results when the data seriously depart from hypersphericity. We propose new cluster analysis methods based on genetic algorithms that overcomes the strong dependence on initial seed values. In addition, we propose a generalization of the Genetic K-means algorithm which can accurately identify clusters with complex hyperellipsoidal covariance structures. We then use this new algorithm in a genetic algorithm based Expectation-Maximization process that can accurately calculate parameters describing complex clusters in a mixture model routine. Using the accuracy of this GEM algorithm, we assign information scores to cluster calculations in order to best identify the number of mixture components in a multivariate data set. We will showcase how these algorithms can be used to process multivariate data from astronomical observations.

Metrically adjusted questionnaires can provide more information for scientists- an example from the tourism.

PubMed

Sindik, Joško; Miljanović, Maja

2017-03-01

The article deals with the issue of research methodology, illustrating the use of known research methods for new purposes. Questionnaires that originally do not have metric characteristics can be called »handy questionnaires«. In this article, the author is trying to consider the possibilities of their improved scientific usability, which can be primarily ensured by improving their metric characteristics, consequently using multivariate instead of univariate statistical methods. In order to establish the base for the application of multivariate statistical procedures, the main idea is to develop strategies to design measurement instruments from parts of the handy questionnaires. This can be accomplished in two ways: before deciding upon the methods for data collection (redesigning the handy questionnaires) and before the collection of the data (a priori) or after the data has been collected, without modifying the questionnaire (a posteriori). The basic principles of applying these two strategies of the metrical adaptation of handy questionnaires are described.

Forest Soil Disturbance Monitoring Protocol: Volume II: Supplementary methods, statistics, and data collection

Treesearch

Deborah S. Page-Dumroese; Ann M. Abbott; Thomas M. Rice

2009-01-01

Volume I and volume II of the Forest Soil Disturbance Monitoring Protocol (FSDMP) provide information for a wide range of users, including technicians, field crew leaders, private landowners, land managers, forest professionals, and researchers. Volume I: Rapid Assessment includes the basic methods for establishing forest soil monitoring transects and consistently...

A General Linear Method for Equating with Small Samples

ERIC Educational Resources Information Center

Albano, Anthony D.

2015-01-01

Research on equating with small samples has shown that methods with stronger assumptions and fewer statistical estimates can lead to decreased error in the estimated equating function. This article introduces a new approach to linear observed-score equating, one which provides flexible control over how form difficulty is assumed versus estimated…

Inquiring the Most Critical Teacher's Technology Education Competences in the Highest Efficient Technology Education Learning Organization

ERIC Educational Resources Information Center

Yung-Kuan, Chan; Hsieh, Ming-Yuan; Lee, Chin-Feng; Huang, Chih-Cheng; Ho, Li-Chih

2017-01-01

Under the hyper-dynamic education situation, this research, in order to comprehensively explore the interplays between Teacher Competence Demands (TCD) and Learning Organization Requests (LOR), cross-employs the data refined method of Descriptive Statistics (DS) method and Analysis of Variance (ANOVA) and Principal Components Analysis (PCA)…

Power Analysis for Complex Mediational Designs Using Monte Carlo Methods

ERIC Educational Resources Information Center

Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

2010-01-01

Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex…

Estimation procedures for the combined 1990s periodic forest inventories of California, Oregon, and Washington.

Treesearch

T.M. Barrett

2004-01-01

During the 1990s, forest inventories for California, Oregon, and Washington were conducted by different agencies using different methods. The Pacific Northwest Research Station Forest Inventory and Analysis program recently integrated these inventories into a single database. This document briefly describes potential statistical methods for estimating population totals...

Advantages of Social Network Analysis in Educational Research

ERIC Educational Resources Information Center

Ushakov, K. M.; Kukso, K. N.

2015-01-01

Currently one of the main tools for the large scale studies of schools is statistical analysis. Although it is the most common method and it offers greatest opportunities for analysis, there are other quantitative methods for studying schools, such as network analysis. We discuss the potential advantages that network analysis has for educational…

The Census in One Hour?: The Development of an Effective One-Shot BI Session.

ERIC Educational Resources Information Center

Sanford, Carolyn C.

1991-01-01

Describes the continuing development of a bibliographic instruction (BI) course at Carleton College for a sociology/anthropology research methods course that focuses on statistical sources. Goals and objectives of the course are explained, and various methods of teaching search strategies are described, including overhead transparencies, handouts,…

Coloc-stats: a unified web interface to perform colocalization analysis of genomic features.

PubMed

Simovski, Boris; Kanduri, Chakravarthi; Gundersen, Sveinung; Titov, Dmytro; Domanska, Diana; Bock, Christoph; Bossini-Castillo, Lara; Chikina, Maria; Favorov, Alexander; Layer, Ryan M; Mironov, Andrey A; Quinlan, Aaron R; Sheffield, Nathan C; Trynka, Gosia; Sandve, Geir K

2018-06-05

Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/.

Use of missing data methods in longitudinal studies: the persistence of bad practices in developmental psychology.

PubMed

Jelicić, Helena; Phelps, Erin; Lerner, Richard M

2009-07-01

Developmental science rests on describing, explaining, and optimizing intraindividual changes and, hence, empirically requires longitudinal research. Problems of missing data arise in most longitudinal studies, thus creating challenges for interpreting the substance and structure of intraindividual change. Using a sample of reports of longitudinal studies obtained from three flagship developmental journals-Child Development, Developmental Psychology, and Journal of Research on Adolescence-we examined the number of longitudinal studies reporting missing data and the missing data techniques used. Of the 100 longitudinal studies sampled, 57 either reported having missing data or had discrepancies in sample sizes reported for different analyses. The majority of these studies (82%) used missing data techniques that are statistically problematic (either listwise deletion or pairwise deletion) and not among the methods recommended by statisticians (i.e., the direct maximum likelihood method and the multiple imputation method). Implications of these results for developmental theory and application, and the need for understanding the consequences of using statistically inappropriate missing data techniques with actual longitudinal data sets, are discussed.

Use of statistical study methods for the analysis of the results of the imitation modeling of radiation transfer

NASA Astrophysics Data System (ADS)

Alekseenko, M. A.; Gendrina, I. Yu.

2017-11-01

Recently, due to the abundance of various types of observational data in the systems of vision through the atmosphere and the need for their processing, the use of various methods of statistical research in the study of such systems as correlation-regression analysis, dynamic series, variance analysis, etc. is actual. We have attempted to apply elements of correlation-regression analysis for the study and subsequent prediction of the patterns of radiation transfer in these systems same as in the construction of radiation models of the atmosphere. In this paper, we present some results of statistical processing of the results of numerical simulation of the characteristics of vision systems through the atmosphere obtained with the help of a special software package.1

Statistical physics of hard combinatorial optimization: Vertex cover problem

NASA Astrophysics Data System (ADS)

Zhao, Jin-Hua; Zhou, Hai-Jun

2014-07-01

Typical-case computation complexity is a research topic at the boundary of computer science, applied mathematics, and statistical physics. In the last twenty years, the replica-symmetry-breaking mean field theory of spin glasses and the associated message-passing algorithms have greatly deepened our understanding of typical-case computation complexity. In this paper, we use the vertex cover problem, a basic nondeterministic-polynomial (NP)-complete combinatorial optimization problem of wide application, as an example to introduce the statistical physical methods and algorithms. We do not go into the technical details but emphasize mainly the intuitive physical meanings of the message-passing equations. A nonfamiliar reader shall be able to understand to a large extent the physics behind the mean field approaches and to adjust the mean field methods in solving other optimization problems.

Microscopic saw mark analysis: an empirical approach.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles

2015-01-01

Microscopic saw mark analysis is a well published and generally accepted qualitative analytical method. However, little research has focused on identifying and mitigating potential sources of error associated with the method. The presented study proposes the use of classification trees and random forest classifiers as an optimal, statistically sound approach to mitigate the potential for error of variability and outcome error in microscopic saw mark analysis. The statistical model was applied to 58 experimental saw marks created with four types of saws. The saw marks were made in fresh human femurs obtained through anatomical gift and were analyzed using a Keyence digital microscope. The statistical approach weighed the variables based on discriminatory value and produced decision trees with an associated outcome error rate of 8.62-17.82%. © 2014 American Academy of Forensic Sciences.

Measurement of the Local Food Environment: A Comparison of Existing Data Sources

PubMed Central

Bader, Michael D. M.; Ailshire, Jennifer A.; Morenoff, Jeffrey D.; House, James S.

2010-01-01

Studying the relation between the residential environment and health requires valid, reliable, and cost-effective methods to collect data on residential environments. This 2002 study compared the level of agreement between measures of the presence of neighborhood businesses drawn from 2 common sources of data used for research on the built environment and health: listings of businesses from commercial databases and direct observations of city blocks by raters. Kappa statistics were calculated for 6 types of businesses—drugstores, liquor stores, bars, convenience stores, restaurants, and grocers—located on 1,663 city blocks in Chicago, Illinois. Logistic regressions estimated whether disagreement between measurement methods was systematically correlated with the socioeconomic and demographic characteristics of neighborhoods. Levels of agreement between the 2 sources were relatively high, with significant (P < 0.001) kappa statistics for each business type ranging from 0.32 to 0.70. Most business types were more likely to be reported by direct observations than in the commercial database listings. Disagreement between the 2 sources was not significantly correlated with the socioeconomic and demographic characteristics of neighborhoods. Results suggest that researchers should have reasonable confidence using whichever method (or combination of methods) is most cost-effective and theoretically appropriate for their research design. PMID:20123688

Students' perspectives of undergraduate research methods education at three public medical schools in Uganda.

PubMed

Munabi, Ian Guyton; Buwembo, William; Joseph, Ruberwa; Peter, Kawungezi; Bajunirwe, Francis; Mwaka, Erisa Sabakaki

2016-01-01

In this study we used a model of adult learning to explore undergraduate students' views on how to improve the teaching of research methods and biostatistics. This was a secondary analysis of survey data of 600 undergraduate students from three medical schools in Uganda. The analysis looked at student's responses to an open ended section of a questionnaire on their views on undergraduate teaching of research methods and biostatistics. Qualitative phenomenological data analysis was done with a bias towards principles of adult learning. Students appreciated the importance of learning research methods and biostatistics as a way of understanding research problems; appropriately interpreting statistical concepts during their training and post-qualification practice; and translating the knowledge acquired. Stressful teaching environment and inadequate educational resource materials were identified as impediments to effective learning. Suggestions for improved learning included: early and continuous exposure to the course; more active and practical approach to teaching; and a need for mentorship. The current methods of teaching research methods and biostatistics leave most of the students in the dissonance phase of learning resulting in none or poor student engagement that results in a failure to comprehend and/or appreciate the principles governing the use of different research methods.

Statistical results on restorative dentistry experiments: effect of the interaction between main variables

PubMed Central

CAVALCANTI, Andrea Nóbrega; MARCHI, Giselle Maria; AMBROSANO, Gláucia Maria Bovi

2010-01-01

Statistical analysis interpretation is a critical field in scientific research. When there is more than one main variable being studied in a research, the effect of the interaction between those variables is fundamental on experiments discussion. However, some doubts can occur when the p-value of the interaction is greater than the significance level. Objective To determine the most adequate interpretation for factorial experiments with p-values of the interaction nearly higher than the significance level. Materials and methods The p-values of the interactions found in two restorative dentistry experiments (0.053 and 0.068) were interpreted in two distinct ways: considering the interaction as not significant and as significant. Results Different findings were observed between the two analyses, and studies results became more coherent when the significant interaction was used. Conclusion The p-value of the interaction between main variables must be analyzed with caution because it can change the outcomes of research studies. Researchers are strongly advised to interpret carefully the results of their statistical analysis in order to discuss the findings of their experiments properly. PMID:20857003

A statistical approach to selecting and confirming validation targets in -omics experiments

PubMed Central

2012-01-01

Background Genomic technologies are, by their very nature, designed for hypothesis generation. In some cases, the hypotheses that are generated require that genome scientists confirm findings about specific genes or proteins. But one major advantage of high-throughput technology is that global genetic, genomic, transcriptomic, and proteomic behaviors can be observed. Manual confirmation of every statistically significant genomic result is prohibitively expensive. This has led researchers in genomics to adopt the strategy of confirming only a handful of the most statistically significant results, a small subset chosen for biological interest, or a small random subset. But there is no standard approach for selecting and quantitatively evaluating validation targets. Results Here we present a new statistical method and approach for statistically validating lists of significant results based on confirming only a small random sample. We apply our statistical method to show that the usual practice of confirming only the most statistically significant results does not statistically validate result lists. We analyze an extensively validated RNA-sequencing experiment to show that confirming a random subset can statistically validate entire lists of significant results. Finally, we analyze multiple publicly available microarray experiments to show that statistically validating random samples can both (i) provide evidence to confirm long gene lists and (ii) save thousands of dollars and hundreds of hours of labor over manual validation of each significant result. Conclusions For high-throughput -omics studies, statistical validation is a cost-effective and statistically valid approach to confirming lists of significant results. PMID:22738145

A Review of Astronomy Education Research

NASA Astrophysics Data System (ADS)

Bailey, Janelle M.; Slater, Timothy F.

The field of astronomy education is rapidly growing beyond merely sharing effective activities or curriculum ideas. This paper categorizes and summarizes the literature in astronomy education research and contains more than 100 references to articles, books, and Web-based materials. Research into student understanding on a variety of topics now occupies a large part of the literature. Topics include the shape of Earth and gravity, lunar phases, seasons, astrobiology, and cosmology. The effectiveness of instructional methods is now being tested systematically, taking data beyond the anecdotal with powerful research designs and statistical analyses. Quantitative, qualitative, and mixed-methods approaches have found their places in the researcher's toolbox. In all cases, the connection between the research performed and its effect on classroom instruction is largely lacking.

The potential contributions of geographic information science to the study of social determinants of health in Iran.

PubMed

Rabiei-Dastjerdi, Hamidreza; Matthews, Stephen A

2018-01-01

Recent interest in the social determinants of health (SDOH) and the effects of neighborhood contexts on individual health and well-being has grown exponentially. In this brief communication, we describe recent developments in both analytical perspectives and methods that have opened up new opportunities for researchers interested in exploring neighborhoods and health research within a SDOH framework. We focus specifically on recent advances in geographic information science, statistical methods, and spatial analytical tools. We close with a discussion of how these recent developments have the potential to enhance SDOH research in Iran.

Clinician-Scientists in Canada: Barriers to Career Entry and Progress

PubMed Central

Lander, Bryn; Hanley, Gillian E.; Atkinson-Grosjean, Janet

2010-01-01

Background Clinician-scientists play an important role in translating between research and clinical practice. Significant concerns about a decline in their numbers have been raised. Potential barriers for career entry and progress are explored in this study. Methods Case-study research methods were used to identify barriers perceived by clinician-scientists and their research teams in two Canadian laboratories. These perceptions were then compared against statistical analysis of data from Canadian Institutes of Health Research (CIHR) databases on grant and award performance of clinician-scientists and non-clinical PhDs for fiscal years 2000 to 2008. Results Three main barriers were identified through qualitative analysis: research training, research salaries, and research grants. We then looked for evidence of these barriers in the Canada-wide statistical dataset for our study period. Clinician-scientists had a small but statistically significant higher mean number of degrees (3.3) than non-clinical scientists (3.2), potentially confirming the perception of longer training times. But evidence of the other two barriers was equivocal. For example, while overall growth in salary awards was minimal, awards to clinician-scientists increased by 45% compared to 6.3% for non-clinical PhDs. Similarly, in terms of research funding, awards to clinician-scientists increased by more than 25% compared with 5% for non-clinical PhDs. However, clinician-scientist-led grants funded under CIHR's Clinical thematic area decreased significantly from 61% to 51% (p-value<0.001) suggesting that clinician-scientists may be shifting their attention to other research domains. Conclusion While clinician-scientists continue to perceive barriers to career entry and progress, quantitative results suggest improvements over the last decade. Clinician-scientists are awarded an increasing proportion of CIHR research grants and salary awards. Given the translational importance of this group, however, it may be prudent to adopt specific policy and funding incentives to ensure the ongoing viability of the career path. PMID:20957175

An Investigation of the Variety and Complexity of Statistical Methods Used in Current Internal Medicine Literature.

PubMed

Narayanan, Roshni; Nugent, Rebecca; Nugent, Kenneth

2015-10-01

Accreditation Council for Graduate Medical Education guidelines require internal medicine residents to develop skills in the interpretation of medical literature and to understand the principles of research. A necessary component is the ability to understand the statistical methods used and their results, material that is not an in-depth focus of most medical school curricula and residency programs. Given the breadth and depth of the current medical literature and an increasing emphasis on complex, sophisticated statistical analyses, the statistical foundation and education necessary for residents are uncertain. We reviewed the statistical methods and terms used in 49 articles discussed at the journal club in the Department of Internal Medicine residency program at Texas Tech University between January 1, 2013 and June 30, 2013. We collected information on the study type and on the statistical methods used for summarizing and comparing samples, determining the relations between independent variables and dependent variables, and estimating models. We then identified the typical statistics education level at which each term or method is learned. A total of 14 articles came from the Journal of the American Medical Association Internal Medicine, 11 from the New England Journal of Medicine, 6 from the Annals of Internal Medicine, 5 from the Journal of the American Medical Association, and 13 from other journals. Twenty reported randomized controlled trials. Summary statistics included mean values (39 articles), category counts (38), and medians (28). Group comparisons were based on t tests (14 articles), χ2 tests (21), and nonparametric ranking tests (10). The relations between dependent and independent variables were analyzed with simple regression (6 articles), multivariate regression (11), and logistic regression (8). Nine studies reported odds ratios with 95% confidence intervals, and seven analyzed test performance using sensitivity and specificity calculations. These papers used 128 statistical terms and context-defined concepts, including some from data analysis (56), epidemiology-biostatistics (31), modeling (24), data collection (12), and meta-analysis (5). Ten different software programs were used in these articles. Based on usual undergraduate and graduate statistics curricula, 64.3% of the concepts and methods used in these papers required at least a master's degree-level statistics education. The interpretation of the current medical literature can require an extensive background in statistical methods at an education level exceeding the material and resources provided to most medical students and residents. Given the complexity and time pressure of medical education, these deficiencies will be hard to correct, but this project can serve as a basis for developing a curriculum in study design and statistical methods needed by physicians-in-training.

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

NASA Technical Reports Server (NTRS)

Feiveson, Alan; Glenn, Nancy L.

2013-01-01

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.