Sentences with phrase «statistical review of data»

Perform Statistical review of data to ensure data quality by utilizing SAS procedures such as PROC FREQ.

Not exact matches

The authors» responsibilities were as follows — CNM: had leadership responsibility for the research planning and execution, wrote the manuscript, and had primary responsibility for the final content of the manuscript; CNM, HE, and BN: formulated the study idea and designed the research; EV and JM: managed the day - to - day conduct of the study and oversaw the data collection; YJ: performed statistical analyses of the study data; and all authors: provided critical review and commentary on the draft of the manuscript and read and approved the final manuscript.

The two reviews investigating moderators of effectiveness both suffer from statistical limitations such as use of small data sets and underestimation of heterogeneity.

Studies had to be case control for the purpose of the statistical analysis; have breastfeeding as a measured exposure and leukemia as a measured outcome; include data on breastfeeding duration in months, including but not limited to, 6 months or more (where relevant data were unavailable in the publication, the authors of the studies were contacted); and been published in peer - reviewed journals with full text available in English.

The Steering Group agreed the terms of reference for the review and, in consultation with the UK Human Geography community, appointed an International Panel of leading international experts, chaired by Professor David Ley, University of British Columbia, Canada The International Panel visited the UK for one week in May 2012 and met with about 150 stakeholders in UK Human Geography Prior to its UK visit, the Panel was provided with a range of background data including: Overviews of research trends and outputs since 2000 completed by representatives of the nine Human Geography sub-disciplines Two - page assessments by Heads of UK Geography Departments of strengths, weaknesses, overall health, and future opportunities and challenges to Human Geography in the UK (15 submissions were received) A statistical profile of UK Human Geography: Briefing Document: Statistical Overview and Commentary by Paul Wakeling (2012) Bibliometric Data for the ESRC International Benchmarking Review of Human Geography by Thomson Reuters (2012) A Short Introduction to UK Research Funding Policy by David Mills (2012) Survey of Users of Human Geography Research by Steve Johnson, David Gibbs and Ian Mills (review and, in consultation with the UK Human Geography community, appointed an International Panel of leading international experts, chaired by Professor David Ley, University of British Columbia, Canada The International Panel visited the UK for one week in May 2012 and met with about 150 stakeholders in UK Human Geography Prior to its UK visit, the Panel was provided with a range of background data including: Overviews of research trends and outputs since 2000 completed by representatives of the nine Human Geography sub-disciplines Two - page assessments by Heads of UK Geography Departments of strengths, weaknesses, overall health, and future opportunities and challenges to Human Geography in the UK (15 submissions were received) A statistical profile of UK Human Geography: Briefing Document: Statistical Overview and Commentary by Paul Wakeling (2012) Bibliometric Data for the ESRC International Benchmarking Review of Human Geography by Thomson Reuters (2012) A Short Introduction to UK Research Funding Policy by David Mills (2012) Survey of Users of Human Geography Research by Steve Johnson, David Gibbs and Ian Mills (20data including: Overviews of research trends and outputs since 2000 completed by representatives of the nine Human Geography sub-disciplines Two - page assessments by Heads of UK Geography Departments of strengths, weaknesses, overall health, and future opportunities and challenges to Human Geography in the UK (15 submissions were received) A statistical profile of UK Human Geography: Briefing Document: Statistical Overview and Commentary by Paul Wakeling (2012) Bibliometric Data for the ESRC International Benchmarking Review of Human Geography by Thomson Reuters (2012) A Short Introduction to UK Research Funding Policy by David Mills (2012) Survey of Users of Human Geography Research by Steve Johnson, David Gibbs and Ian Mistatistical profile of UK Human Geography: Briefing Document: Statistical Overview and Commentary by Paul Wakeling (2012) Bibliometric Data for the ESRC International Benchmarking Review of Human Geography by Thomson Reuters (2012) A Short Introduction to UK Research Funding Policy by David Mills (2012) Survey of Users of Human Geography Research by Steve Johnson, David Gibbs and Ian MiStatistical Overview and Commentary by Paul Wakeling (2012) Bibliometric Data for the ESRC International Benchmarking Review of Human Geography by Thomson Reuters (2012) A Short Introduction to UK Research Funding Policy by David Mills (2012) Survey of Users of Human Geography Research by Steve Johnson, David Gibbs and Ian Mills (20Data for the ESRC International Benchmarking Review of Human Geography by Thomson Reuters (2012) A Short Introduction to UK Research Funding Policy by David Mills (2012) Survey of Users of Human Geography Research by Steve Johnson, David Gibbs and Ian Mills (Review of Human Geography by Thomson Reuters (2012) A Short Introduction to UK Research Funding Policy by David Mills (2012) Survey of Users of Human Geography Research by Steve Johnson, David Gibbs and Ian Mills (2012).

«It is my hope that this review and analysis of the statistical data will ensure that the Justice Center is utilizing the taxpayer's money properly to investigate abuse so no child will ever have to suffer due to inadequate protection.»

«The so - called «trick» was nothing more than a statistical method used to bring two or more different kinds of data sets together in a legitimate fashion by a technique that has been reviewed by a broad array of peers in the field,» the panel said.

For example, there is a lot of interest on collaborative team science, study registration, stronger study designs and statistical tools, and better peer review, along with making scientific data, analyses and protocols widely available so that others can replicate experiments, thereby fostering trust in the conclusions of those studies.

An increasing number of journals, including Nature and Science, have adopted measures such as checklists for study design and reporting while improving statistical review and encouraging access to data and protocols.

According to one major statistical review (Cohen E, et al., Statistical Review of U.S. Macronutrient Consumption Data, 1965 — 2011), the number of overweight and obese Americans rose from 42.3 % to 66.1 % from 1971 to 2011 and duringstatistical review (Cohen E, et al., Statistical Review of U.S. Macronutrient Consumption Data, 1965 — 2011), the number of overweight and obese Americans rose from 42.3 % to 66.1 % from 1971 to 2011 and during thisreview (Cohen E, et al., Statistical Review of U.S. Macronutrient Consumption Data, 1965 — 2011), the number of overweight and obese Americans rose from 42.3 % to 66.1 % from 1971 to 2011 and duringStatistical Review of U.S. Macronutrient Consumption Data, 1965 — 2011), the number of overweight and obese Americans rose from 42.3 % to 66.1 % from 1971 to 2011 and during thisReview of U.S. Macronutrient Consumption Data, 1965 — 2011), the number of overweight and obese Americans rose from 42.3 % to 66.1 % from 1971 to 2011 and during this time:

Despite this statistical need to achieve a result from poor data, the main problem must be that no attempt was given to provide the symptom of plantar heel pain a diagnosis in some of the studies involved in the review.

Our staff accomplish this mission using a variety of research techniques, including education data analysis, literature reviews, interviews, surveys, panel or focus group discussions, and statistical analyses.

APA has expertise in a wide range of approaches that we leverage in conducting our work, including: data analysis, cost modeling, statistical modeling, surveys, interviews, focus groups, facilitation, and literature reviews.

In thirty years of reading statistical research papers, I have never seen a peer - reviewed statistical research paper where the author considered that a statistical hypothesis had been proven, when the data did not achieve even a 10 % confidence level (or a 1 in 10).

Guest post: Roger Andrews Renewable energy, particularly wind and solar, continues to set records for electicity generation and installed capacity in many parts of the world, and as shown in Figure 1 wind and solar growth in recent years has indeed been quite spectacular (the data used to construct this and following Figures are from the 2014 BP Statistical Review of World Energy): Figure 1: Electricity Generated from Solar and Wind, 1965 - 2013 But Figure 1 doesn't tell the whole story because solar and wind are only two of the four main sources of renewable energy.

We will continue with exploratory data analysis (a statistical method developed by John Tukey), and we will share our results with the public in the forms of memos posted online and of papers submitted to peer reviewed journals.

Hubbert linearization for world hydrocarbon production (total of oil, natural gas, and natural gas liquids), based on production data from the 2007 BP Statistical Review.

I developed own global by country models of consumption breaking with decomposition of GDP, population and energy consumption / energy type based on published data from IEA, EIA, and BP Statistical review... I found that to be the same model concept as the Kaya identity which is now commonplace.

This is the 5th installment in a series that examines data from the recently released 2013 BP Statistical Review of World Energy.

[iii] BP Statistical Review of World Energy data workbook, http://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/downloads.html

As «influential scientific or statistical information,» the National Assessment also fails the FDQA's «reproducibility» standard, which requires transparency regarding data and methods of analysis, «a quality standard above and beyond some peer review quality standards.»

As the statutorily designed steering document for policymaking, the National Assessment is «influential scientific or statistical information»; therefore, it must also meet a «reproducibility» standard that requires transparency regarding data and methods of analysis, «as a quality standard above and beyond some peer review quality standards.»

Steve's observations here are more evidence that the error bars around the proxy - reconstructions are much wider than the published estimates — a point that Judith Curry has been making, and that McShayne & Wyner demonstrated pretty convincingly in their statistical review of the proxy data.

The chart was compiled by Robert Wilson, an ecosystem and climate change researcher at the University of Strathclyde in Glasgow, Scotland, and is based on data from the 2015 BP Statistical Review Of World Energof Strathclyde in Glasgow, Scotland, and is based on data from the 2015 BP Statistical Review Of World EnergOf World Energy.

Maybe if the AGW proponents stopped calling those skeptical of their hypotheses «deniers», and did something about the continued tenure of those who engaged in unscientific practises such as data bending, opaque statistical massaging and weighting, email deletion, undermining the peer review process and subverting journal editor's independence, then the big bad nasty «deniers» might stop using the «Alarmist» tag and highlighting climategate.

-- Overstating alarming scenarios — Understating uncertainty — Suppressing legitimate minority viewpoints — Suppressing legitimate criticism of their work — Subverting the peer - review process — Not reporting known adverse data in their publications — Cherry - picking data to show a desired result — Not taking steps to counter media and political exaggerations based on but unsupported by their work — Using new and poorly characterized statistical methods without which their results would change substantially

Using the RCP data and BP's Statistical Review of World Energy 2015, I will demonstrate the absurdity of RCP 8.5 in a more «apples to apples» manner than my previous post.

The so - called «trick» was nothing more than a statistical method used to bring two or more different kinds of data sets together in a legitimate fashion by a technique that has been reviewed by a broad array of peers in the field.

I reviewed Mann's method, and found that the statistical bias he applied was for temperatures proportional to the time rate of change of temperatures, which defines an exponential function of temperature independent of the initial data.

They think they can get away with their massaging of data, cherry - picking, perversion of statistical methodology and corrupting peer / grant review.

(2) thou shalt not fudge the data (3) thou shalt not invent arbitrary statistical methods to suit thy data (4) thou shalt not indulge in any form of bias e.g. thou shalt not employ incomplete, highly selective, subjective literature reviews (6) in the interests of transparency and replication thou shalt not hide the data or code (7) thou shalt not make vague or exaggerated statements unsupported by evidence (8) thou shalt not tolerate actual or potential conflicts of interest (9) thou shalt not allow political interference to compromise scientific integrity (10) thou shalt not use unvalidated computer models (11) Thy university shall insulate undergraduate fees from research expenses and require research to be self supporting independent of the teaching.

(2) thou shalt not fudge the data (3) thou shalt not invent arbitrary statistical methods to suit thy data (4) thou shalt not indulge in any form of bias e.g. thou shalt not employ incomplete, highly selective, subjective literature reviews (5) thou shalt not exaggerate (6) in the interests of transparency and replication thou shalt not hide the data or code (7) thou shalt not make vague statements unsupported by evidence (8) thou shalt not tolerate actual or potential conflicts of interest (9) thou shalt not allow political interference to compromise scientific integrity (10) thou shalt not use unvalidated computer models

* According to the Berkeley group, the Earth's surface temperature will have risen (on average) slightly less than what indicated by NASA, NOAA and the Met Office * Differences will be on the edge of statistical significance, leaving a lot open to subjective interpretation * Several attempts will be made by climate change conformists and True Believers to smear the work of BEST, and to prevent them from publishing their data * After publication, organised groups of people will try to cloud the issue to the point of leaving the public unsure about what exactly was found by BEST * New questions will be raised regarding UHI, however the next IPCC assessment's first draft will be singularly forgetful of any peer - reviewed paper on the topic * We will all be left with a slightly - warming world, the only other certitude being that all mitigation efforts will be among the stupidest ideas that ever sprung to human mind.

The research, carried out over three months, draws on a review of official documents, research and statistical data, as well as 21 interviews with barristers, solicitors, immigration judges and other specialists.

Performing periodic reviews across Colorado state to get the exact statistical data of orphan children

Assisted in the planning, review, and reporting of statistical data results of program / project studies.

My extended knowledge of reviewing statistical data to analyze customer opinion and managing related pricing along with identifying opportunities for growth is what makes me an expert in managing merchandising tasks successfully.

Assisted with the preparation and presentation of 6 quarterly reports per client, statistical market data collection and market research and preparation of client review meetings

MCKESSON, Hartford, CT Data Entry Specialist 2014 — Present • Reconcile monthly datasets and check the same for errors • Correct and update any errors identified in report review • Integrate data from various sources to build a validated pool of information • Run the statistical analysis to organize data • Retrieve authorized data sets upon request while ensuring data confidentiality • Segregate source data into meaningful strata leveraging the online database system effectiData Entry Specialist 2014 — Present • Reconcile monthly datasets and check the same for errors • Correct and update any errors identified in report review • Integrate data from various sources to build a validated pool of information • Run the statistical analysis to organize data • Retrieve authorized data sets upon request while ensuring data confidentiality • Segregate source data into meaningful strata leveraging the online database system effectidata from various sources to build a validated pool of information • Run the statistical analysis to organize data • Retrieve authorized data sets upon request while ensuring data confidentiality • Segregate source data into meaningful strata leveraging the online database system effectidata • Retrieve authorized data sets upon request while ensuring data confidentiality • Segregate source data into meaningful strata leveraging the online database system effectidata sets upon request while ensuring data confidentiality • Segregate source data into meaningful strata leveraging the online database system effectidata confidentiality • Segregate source data into meaningful strata leveraging the online database system effectidata into meaningful strata leveraging the online database system effectively

PARK RIDGE LIVING CENTER, Stamford, CT (Oct 2012 — Present) Home Care Coordinator • Assess patients» care needs by delving into their medical histories • Create and implement in - home care plans to ensure patient safety and medical wellbeing • Arrange for needed services, supplies and appliances to help patients with their daily care regimens • Review home care policies and procedures with families, physicians, agency care providers and insurance providers • Contact physicians and insurance companies to obtain authorizations for services • Determine need for appropriate precautions, including isolation, reverse isolation and restraints • Implement admitting orders and evaluate criteria for patient status • Provide direction and support to administrative officers to ensure efficient patient access flow • Work with discharge planning teams to refer patients needing additional resources • Collect and maintain patient history and statistical data of all referred patients • Coordinate facility admissions and discharge duties • Collaborate with facility care coordinators and social workers to find solutions for challenging patients requiring constant home care

• Confer with document originators to understand document control needs • Gain access to records and determine appropriate ways of recording it • Compile and maintain records and related files such as blueprints, drawings and documents • Examine records to ensure their integrity and completeness • Handle data management duties such as reviewing and coding documents • Analyze documents to appropriate statistical coding • Input data into databases and prepare documents for electronic imaging • Operate micrographic equipment including digital scanners and archive readers to assist readers • Retrieve document data and information in databases and code information into computer records • Take and verify requests for retrieval of records and information and respond to requests as deemed appropriate • Perform minor repair and maintenance on micrographic equipment • Purge hard copy of files according to approved procedures • Develop, design and maintain systems for filing and retrieving records • Determine workflow priorities and develop and implement clerical procedures • Assist in projects such as information gathering and research work • Reproduce and distribute documents on special request of staff members • Ascertain that all records and files are properly labeled and categorized

Other Duties: • Managed medical records by ensuring data entry services • Reviewed discharge and admission records • Collected and filed resident charts • Prepared medical records for court trials • Compiled statistical data and file documents • Assisted physicians and specialists by taking vitals and providing other direct patient care services • Maintained order and cleanliness of work space

UNDP, Fremont, NH, Mar 2010 — Present Project Assistant • Coordinate activities between projects • Distribute project information to various departments • Prepare material for information on projects • Assist with production of project briefs • Assist with coordination of project events • Research and collect financial and statistical data from multiple sources • Review applications and issue permits for project related activities

Extremely organized, research coordinator with over 10 years experience in research related activities including literature review, database creation and maintenance, data collection, data cleaning, statistical analyses, coordination of multi-site research projects, dissemination of findings, maintaining project integrity, supervision of junior level staff, and report, manuscript, book chapter, and grant writing.

About Blog BMC Bioinformatics is an open access, peer - reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology.

Areas of Expertise IT Management Network Engineering Citrix Engineer \ Administration Active Directory / File Security Manager VMWare Engineer \ Administration Network Design / Architecture Local Area Networks (LAN) Wide Area Networks (WAN Help Desk Management Data Center Management / Design * Altiris Administration System Automation Server Configuration Security Systems Management * Hardware Installation Software Configuration Remote Software Deployment Patch Management * Change Management Project Management Business Process Analysis Business Communications Sales / Marketing Management Risk Management / Disaster Recovery Analyst Statistical Analysis Database Management Policy Development Contract Negotiation * Grant Writing Total Quality Management (TQM) Training & Development TCP / IP Configuration Change Management Monitoring Ability to increase organizational effectiveness and staff skill level through training and awareness of best practices Unique blend of technical experience administrative skills and team - building capabilities Mastery of all phases of project development life cycle including requirements analysis specifications development application design implementation data conversion design review and system testing * Proven ability to communicate effectively with all involved parties to ensure the development of viable business solutions to technical issues Ability to manage complex systems spanning multiple platforms and multiple functionalities * Demonstrated leadership and team - building capabilities in the professional environment as well as through active community involvement * Ability to cultivate trust and respect through open communication and shared goals among various business uData Center Management / Design * Altiris Administration System Automation Server Configuration Security Systems Management * Hardware Installation Software Configuration Remote Software Deployment Patch Management * Change Management Project Management Business Process Analysis Business Communications Sales / Marketing Management Risk Management / Disaster Recovery Analyst Statistical Analysis Database Management Policy Development Contract Negotiation * Grant Writing Total Quality Management (TQM) Training & Development TCP / IP Configuration Change Management Monitoring Ability to increase organizational effectiveness and staff skill level through training and awareness of best practices Unique blend of technical experience administrative skills and team - building capabilities Mastery of all phases of project development life cycle including requirements analysis specifications development application design implementation data conversion design review and system testing * Proven ability to communicate effectively with all involved parties to ensure the development of viable business solutions to technical issues Ability to manage complex systems spanning multiple platforms and multiple functionalities * Demonstrated leadership and team - building capabilities in the professional environment as well as through active community involvement * Ability to cultivate trust and respect through open communication and shared goals among various business udata conversion design review and system testing * Proven ability to communicate effectively with all involved parties to ensure the development of viable business solutions to technical issues Ability to manage complex systems spanning multiple platforms and multiple functionalities * Demonstrated leadership and team - building capabilities in the professional environment as well as through active community involvement * Ability to cultivate trust and respect through open communication and shared goals among various business units

Early Loss Mitigation Supervisor (9/2008 — 4/2010) • Managed unit of approximately 8 to 15 collectors while ensuring the achievement of unit objectives and related standards • Compiled and analyzed statistical data relative to unit productivity, monitoring live calls while providing feedback to staff • Provide advice and question resolution concerning collection activities, reviewing the status of severely delinquent accounts and handling all loss mitigation efforts • Advised staff of any changes in policy and procedures, allocated critical resources, and developed work schedules • Train current and new staff members as well as conduct performance reviews, making recommendations as needed regarding corrective actions and suggested dismissals • Assist departmental manager with training course scheduling for entire department • Create and distribute various reports to staff and peers on a regular and ad - hoc basis • Traveled to Chatsworth, CA as supervisor, developing observations and recommendations which led to facility improvements • Acted as representative to the Washington Mutual conversion to early loss mitigation in Albion, NY, sharing best practices from Chase

Professional Experience JP MORGAN CHASE Tempe, AZ Early Loss Mitigation Supervisor (September 2008 to present) • Manage a unit of approximately of 8 to 15 collectors ensuring their unit objectives and standards are met • Compile and analyze statistical data relative to unit productivity, monitor live calls and provide feedback to staff • Provide advice and answer questions concerning collection activities, review status of the most delinquent accounts and handle the Loss Mitigation efforts.

Several systematic reviews have drawn attention to the number of studies that fail to employ proper statistical procedures to account for nesting or clustering of data [3, 7, 9].

A Critical Review of Selye's Stress Theory: The Statistical Analyses of Selye's Own Experimental Data Disprove It