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Search results “Meta analysis study type”
Cohort, Case-Control, Meta-Analysis, Cross-sectional Study Designs & Definition
 
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http://www.stomponstep1.com/cohort-case-control-meta-analysis-cross-sectional-study-designs/ Based on the types of bias that are inherent in some study designs we can rank different study designs based on their validity. The types of research studies at the top of the list have the highest validity while those at the bottom have lower validity. In most cases if 2 studies on the same topic come to different conclusions, you assume the trial of the more valid type is correct. However, this is not always the case. Any study design can have bias. A very well designed and executed cohort study can yield more valid results than a clinical trial with clear deficiencies. • Meta-analysis of multiple Randomized Trials (Highest Validity) • Randomized Trial • Prospective Cohort Studies • Case Control Studies or Retrospective Cohort • Case Series (Lowest Validity) Meta-analysis is the process of taking results from multiple different studies and combining them to reach a single conclusion. Doing this is sort of like having one huge study with a very large sample size and therefore meta-analysis has higher power than individual studies. Clinical trials are the gold standard of research for therapeutic and preventative interventions. The researchers have a high level of control over most factors. This allows for randomization and blinding which aren't possible in many other study types. Participant's groups are assigned by the researcher in clinical trials while in observational studies "natural conditions" (personal preference, genetics, social determinants, environment, lifestyle ...) assign the group. As we will see later, the incidence in different groups is compared using Relative Risk (RR). Cohort Studies are studies where you first determine whether or not a person has had an exposure and then you monitor the occurrence of health outcomes overtime. It is the observational study design with the highest validity. Cohort is just a fancy name for a group, and this should help you remember this study design. You start with a group of people (some of whom happen to have an exposure and some who don't). Then you follow this group for a certain amount of time and monitor how often certain diseases or health outcomes arise. It is easier to conceptually understand cohort studies that are prospective. However, there are retrospective cohort studies also. In this scenario you identify a group of people in the past. You then first identify whether or not these people had the particular exposure at that point in time and determine whether or not they ended up getting the health outcomes later on. As we will see later, the incidence in different groups in a cohort study is compared using Relative Risk (RR). Case-Control Studies are retrospective and observational. You first identify people who have the health outcome of interest. Then you carefully select a group of controls that are very similar to your diseased population except they don't have that particular disease. Then you try to determine whether or not the participants from each group had a particular exposure in the past. I remember this by thinking that in a case control study you start off knowing whether a person is diseased (a case) or not diseased (a control). There isn't a huge difference between retrospective cohort and case-control. You are basically doing the same steps but in a slightly different order. However, the two study designs are used in different settings. As we will see later, the incidence in different groups in a case-control study is compared using Odds Ratio (OR). A Case-Series is a small collection of individual cases. It is an observational study with a very small sample size and no control group. Basically you are just reviewing the medical records for a few people with a particular exposure or disease. A study like this is good for very rare exposures or diseases. Obviously the small sample size and lack of a control group limits the validity of any conclusions that are made, but in certain situations this is the best evidence that is available. Cross Sectional Studies are different from the others we have discussed. While the other studies measure the incidence of a particular health outcome over time, a cross-sectional study measures Prevalence. In this observational study the prevalence of the exposure and the health outcome are measured at the same time. You are basically trying to figure out how many people in the population have the disease and how many people have the exposure at one point in time. It is hard to determine an association between the exposure and disease just from this information, but you can still learn things from these studies. If the exposure and disease are both common in a particular population it may be worth investing more resources to do a different type of study to determine whether or not there is a causal relationship.
Views: 115491 Stomp On Step 1
1 What is meta-analysis?
 
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What is a meta-analysis? This tutorial walks you through the basic concepts.
Views: 21601 MetaLab
Intro to Systematic Reviews & Meta-Analyses
 
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Here's a brief introduction to how to evaluate systematic reviews.
Views: 158748 Rahul Patwari
Systematic Review and Meta analysis - All you ever need to know
 
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Meta analysis is a very common way of bringing together data to help us decide which treatments might be best. BUT, you have to take care when interpreting them - there's a lot more to it than just looking which side of the line the little black diamond is on! How do you construct a search for a systematic review?Can you trust the result of a meta analysis? How do you know if it has been done well? How to recognise different kinds of bias, how to interpret a forest plot, and funnel plot and a bubble plot. What is the I squared statistic and what does it tell you about the data and how much to trust the result? These and many more things to do with these common but complex analyses is explained by Brett Doleman, statistical guru!
Views: 15137 school of surgery
Epidemiological Studies - made easy!
 
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This video gives a simple overview of the most common types of epidemiological studies, their advantages and disadvantages. These include ecological, case-series, case control, cohort and interventional studies. It also looks at systematic reviews and meta-analysis. This video was created by Ranil Appuhamy Voiceover - James Clark -------------------------------------------------------------------------------------------------------- Disclaimer: These videos are provided for educational purposes only. Users should not rely solely on the information contained within these videos and is not intended to be a substitute for advice from other relevant sources. The author/s do not warrant or represent that the information contained in the videos are accurate, current or complete and do not accept any legal liability or responsibility for any loss, damages, costs or expenses incurred by the use of, or reliance on, or interpretation of, the information contained in the videos.
Extracting Data for Meta-Analysis: Step 1
 
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How to locate the outcomes of interest in different types of research articles Table of Contents: 00:00 - Data Extraction for Meta-Analysis 00:14 - 00:51 - 01:25 - 01:38 - 01:49 - Marker 03:26 - 03:39 - 04:39 - 04:59 - 06:32 - 06:38 - 07:33 - 07:40 - 09:12 -
Views: 35081 Scott Parrott
What is META-ANALYSIS? What does META-ANALYSIS mean? META-ANALYSIS meaning & explanation
 
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Do you travel a lot? Get yourself a mobile application to find THE CHEAPEST airline tickets deals available on the market: ANDROID - http://android.theaudiopedia.com - IPHONE - http://iphone.theaudiopedia.com or get BEST HOTEL DEALS worldwide: ANDROID - htttp://androidhotels.theaudiopedia.com - IPHONE - htttp://iphonehotels.theaudiopedia.com What is META-ANALYSIS? What does META-ANALYSIS mean? META-ANALYSIS meaning - META-ANALYSIS definition - META-ANALYSIS explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. The basic tenet of a meta-analysis is that there is a common truth behind all conceptually similar scientific studies, but which has been measured with a certain error within individual studies. The aim in meta-analysis then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. In essence, all existing methods yield a weighted average from the results of the individual studies and what differs is the manner in which these weights are allocated and also the manner in which the uncertainty is computed around the point estimate thus generated. In addition to providing an estimate of the unknown common truth, meta-analysis has the capacity to contrast results from different studies and identify patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies. Meta-analysis can be thought of as "conducting research about previous research." Meta-analysis can only proceed if we are able to identify a common statistical measure that is shared among studies, called the effect size, which has a standard error so that we can proceed with computing a weighted average of that common measure. Such weighting usually takes into consideration the sample sizes of the individual studies, although it can also include other factors, such as study quality. A key benefit of this approach is the aggregation of information leading to a higher statistical power and more robust point estimate than is possible from the measure derived from any individual study. However, in performing a meta-analysis, an investigator must make choices many of which can affect its results, including deciding how to search for studies, selecting studies based on a set of objective criteria, dealing with incomplete data, analyzing the data, and accounting for or choosing not to account for publication bias. Meta-analyses are often, but not always, important components of a systematic review procedure. For instance, a meta-analysis may be conducted on several clinical trials of a medical treatment, in an effort to obtain a better understanding of how well the treatment works. Here it is convenient to follow the terminology used by the Cochrane Collaboration, and use "meta-analysis" to refer to statistical methods of combining evidence, leaving other aspects of 'research synthesis' or 'evidence synthesis', such as combining information from qualitative studies, for the more general context of systematic reviews.
Views: 10490 The Audiopedia
Olive Oil and CV inflammation: a Meta Analysis - FORD BREWER MD MPH
 
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Please watch: "(905) Mitochondria: Central Role in Aging 2018 (and how to reverse it)( warning - geeky)- FORD BREWER " https://www.youtube.com/watch?v=mTKM0Lh078A --~-- Join the PrevMed Community: https://mailchi.mp/1224fb9e00e7/prevmed_community FORD BREWER MD MPH PrevMedHeartRisk.com To prevent disability, heart attack, stroke, dementia - visit my Youtube Channel at https://www.youtube.com/channel/UCmoEsq6a6ePXxgZeA4CVrUw?view_as=subscriber Or the PrevMed web site at https://prevmedheartrisk.com/ A viewer Shane Creamer alerted me to the following great article in Nutrient magazine in 2015. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586551/ This was an excellent study looking at the science behind the effect of olive oil on cv inflammation. The Cochrane clinical trial meta analysis processes were used well. There were 30 studies that met the criteria. These included a total of 3106 participants. Olive oil showed improvement in C-Reactive Protein, Flow-Mediated Dilation, and Interleukin 6. Differences between things such as supplementation vs diet. There was some comparison to other oils, but these comparisons were not so clear in terms of the study write-up. About Dr. Brewer - Dr. Brewer started as an Emergency Doctor. After seeing too many patients coming in dead from early heart attacks, he went to Johns Hopkins to learn Preventive Medicine. He went on to run the post-graduate training program (residency) in Preventive Medicine at Hopkins. From there, he made a career of practicing and managing preventive medicine and primary care clinics. His later role in this area was Chief Medical Officer for Premise, which has over 500 primary care/ prevention clinics. He was also the Chief Medical Officer for MDLIVE, the second largest telemedicine company. More recently, he founded PrevMed, a heart attack, stroke, and diabetes prevention clinic. At PrevMed, we focus on heart attack, stroke, disability, cancer and Alzheimer's prevention. We find a lot of undiagnosed Type 2 diabetes. Treating unrecognized risk factors like diabetes allows reduction of risk. We provide state-of-the-art genetic testing, imaging, labs and telemedicine options. We serve patients who have already experienced an event as well as those have not developed a diagnosis or event. Our team of senior clinicians includes internationally recognized leaders in the research and treatment of cardiovascular disease, preventive medicine and wellness. We also provide preventive medicine by telemedicine technology to over 30 states. Contact Dr. Brewer at [email protected] or visit http://prevmedheartrisk.com.
Views: 8752 Ford Brewer MD MPH
How to Prevent Alzheimer's, Pharmacotherapy - the AIM Meta-Analysis- FORD BREWER MD MPH
 
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Please watch: "(905) Mitochondria: Central Role in Aging 2018 (and how to reverse it)( warning - geeky)- FORD BREWER " https://www.youtube.com/watch?v=mTKM0Lh078A --~-- Join the PrevMed Community: https://mailchi.mp/1224fb9e00e7/prevmed_community FORD BREWER MD MPH PrevMedHeartRisk.com To prevent disability, heart attack, stroke, dementia - visit my Youtube Channel at https://www.youtube.com/channel/UCmoEsq6a6ePXxgZeA4CVrUw?view_as=subscriber Or the PrevMed web site at https://prevmedheartrisk.com/ On Dec 19, 2017 the Annals of Internal Medicine published a 4 part series of meta analyses re: the science of prevention of Alzheimer's. This video is on use of pharmacy approaches pharmacotherapy and prevention. Here's the pdf of the study. http://www.dssimon.com/MM/ACP-dementia/Pharmacologic_Interventions_to_Prevent_Cognitive_Decline.pdf 11,087 studies were pulled. There were 102 references included after reviews for lack of applicability, etc. 51 trials made it through more detailed review including lack of bias. Types of pharmacotherapy included were: hormones, antihypertensives, NSAIDS, lipid-lowering medications and even diabetic medications. The findings were not so much that there was NO improvement. The real challenge is the pattern that there was "NO DATA". You can't make a silk purse from a sow's ear. The research just isn't out there. It hasn't been done. There is need for studies that look at multi-system approaches including lifestyle, exercise, bp and dm management, and cognitive training. That type of study is likely to be too expensive and logistically complicated to be done any time soon. About Dr. Brewer - Dr. Brewer started as an Emergency Doctor. After seeing too many patients coming in dead from early heart attacks, he went to Johns Hopkins to learn Preventive Medicine. He went on to run the post-graduate training program (residency) in Preventive Medicine at Hopkins. From there, he made a career of practicing and managing preventive medicine and primary care clinics. His later role in this area was Chief Medical Officer for Premise, which has over 500 primary care/ prevention clinics. He was also the Chief Medical Officer for MDLIVE, the second largest telemedicine company. More recently, he founded PrevMed, a heart attack, stroke, and diabetes prevention clinic. At PrevMed, we focus on heart attack, stroke, disability, cancer and Alzheimer's prevention. We find a lot of undiagnosed Type 2 diabetes. Treating unrecognized risk factors like diabetes allows reduction of risk. We provide state-of-the-art genetic testing, imaging, labs and telemedicine options. We serve patients who have already experienced an event as well as those have not developed a diagnosis or event. Our team of senior clinicians includes internationally recognized leaders in the research and treatment of cardiovascular disease, preventive medicine and wellness. We also provide preventive medicine by telemedicine technology to over 30 states. Contact Dr. Brewer at [email protected] or visit http://prevmedheartrisk.com.
Views: 352 Ford Brewer MD MPH
RevMan Tutorial - Entering Data For Meta-Analysis
 
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In this video tutorial, I will show you how to set up and enter data in RevMan to be able to perform a meta-analysis. I will also describe the output of the results. In the example, I will use a continuous data type. However, most of the settings apply to other data types, such as odds ratios. RevMan version used: 5.3 THE ONLINE GUIDE https://toptipbio.com/enter-data-into-revman/ VIDEO BREAKDOWN Step 1: Adding references for included studies (00:43) Step 2: Adding a new comparison (02:37) Step 3: Adding a new outcome (03:16) Step 4: Adding studies and data to the new outcome (08:25) Step 5: The output (09:07) MORE HELPFUL HINTS & TIPS https://toptipbio.com/ FOLLOW US Facebook: https://www.facebook.com/TopTipBio/ Twitter: https://twitter.com/TopTipBio LinkedIn: https://www.linkedin.com/company/top-tip-bio/
Views: 220 Top Tip Bio
Meta Analysis Lecture 1
 
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Course in Meta analysis done by doctor Sulaiman Hamarneh M.D. from Massachusetts General Hospital, Harvard Medical School. link for Jordanian meta-analysis club groub https://www.facebook.com/groups/RoyaMAclub/ link for Roya Research Institute page https://www.facebook.com/pages/Roya-Research-Institute/774440309318013?sk=timeline
Views: 952 ahmad shahwan
Conducting a meta-analysis with R
 
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Meta-analysis synthesizes a body of research investigating a common research question. This video provides a practical and non-technical guide showing you how to perform a meta-analysis of correlational datasets. I use a supplementary R script to demonstrate each analytical step described in the paper, which is readily adaptable for people to use for their analyses. While the worked example is the analysis of a correlational dataset, the general meta-analytic process described in this paper is applicable for all types of effect sizes. The paper - http://journal.frontiersin.org/article/10.3389/fpsyg.2015.01549/abstract The script and datasets - https://github.com/dsquintana/corr_meta A podcast episode on meta-analysis issues https://soundcloud.com/everything-hertz/4-meta-analysis-or-mega-silliness
Views: 21100 Daniel Quintana
Systematic Review and Meta-Analysis of Animal Studies - Osama Abunar
 
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SYRCLE: https://www.radboudumc.nl/en/research/radboud-technology-centers/animal-research-facility/systematic-review-center-for-laboratory-animal-experimentation CAMARADES: http://syrf.org.uk/ PROSPERO: https://www.crd.york.ac.uk/prospero/ Facebook profile: https://www.facebook.com/osama.abunar Example: Meta-Analysis and Systematic Review of Neural Stem Cells therapy for experimental ischemia stroke in preclinical studies https://www.nature.com/articles/srep32291
Views: 286 Osama Abunar
Meta analysis - learn how to interpret - quickly
 
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All you need to know about how to interpret the results of a meta analysis in 14 minutes and 15 seconds. If you find yourself in an exam and asked to review a meta analysis in an interview or an exam, or even if you're reading one in a journal to inform your clinical practice, this will be the best 1/4 hour you have spent in ages. If you want a more detailed explanation and to properly understand the process, then download our other podcast about meta analysis, which gives the background to all you see here. With Brett Doleman and Jon Lund
Views: 11045 school of surgery
PRISMA Results & Discussion Meta analysis of Observational Studies
 
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This lecture is part of the Systematic Reviews course that teaches undergraduate students, PhD students and researchers how to build a systematic review or meta-analysis. Don’t hesitate to contact me for help with your review, to conduct a systematic review or meta-analysis or to organise a course on your location. Enjoy the course! Maurice Zeegers (www.systematicreviews.nl)
Views: 91 Maurice Zeegers
Types of statistical studies | Statistical studies | Probability and Statistics | Khan Academy
 
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Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/statistical-studies/types-of-studies/e/types-of-statistical-studies?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/statistical-studies/types-of-studies/v/correlation-and-causality?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/statistical-studies/statistical-questions/v/reasonable-samples?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it! About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to KhanAcademy’s Probability and Statistics channel: https://www.youtube.com/channel/UCRXuOXLW3LcQLWvxbZiIZ0w?sub_confirmation=1 Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 168165 Khan Academy
Meta Analysis, Calcium, and Organic Food
 
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Last week we discussed systematic reviews, and why they're better than review articles, or opinions. But they're not the only types of "studies of studies" I've presented to you. Sometimes you can go a step further. After you've collected all the appropriate studies, you can merge the data together and do one large analysis. Those studies are called meta-analyses, and they're the subject of today's Healthcare Triage For those of you who want to read more or see references, look here: http://theincidentaleconomist.com/wordpress/?p=57918 John Green -- Executive Producer Stan Muller -- Director, Producer Aaron Carroll -- Writer Mark Olsen -- Graphics http://www.twitter.com/aaronecarroll http://www.twitter.com/crashcoursestan http://www.twitter.com/realjohngreen http://www.twitter.com/olsenvideo
Views: 50008 Healthcare Triage
A three minute primer on meta-analysis
 
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Dr Jack Bowden gives us a brief overview of meta-analysis. What is it, and how does it help scientists to assess and combine evidence from many different studies? For further reading please see Jack's paper in the American Statistician which is freely available at goo.gl/8Zxuzy -------------------------------------------------------- Animation by Paupanimation. Find Pau on Twitter (@paupanimation) or at on Facebook at https://www.facebook.com/paupanimation
Views: 3628 TARG Bristol
USMLE Biostats 2: Types of Research Studies (Case Control, Cohort, RCT and more!)
 
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Welcome to LY Med, where I go over everything you need to know for the USMLE STEP 1, with new videos every day. Follow along with First Aid, or with my notes which can be found here: https://www.dropbox.com/sh/an1j9swvjxu46hh/AACd2RIXeEZqghQkGY4EtKZYa?dl=0 This video is going to be on the different types of research. There are two broad categories: experimental (interventional) and observational. There are three types of observational studies: case control, cohort, and cross sectional. Cohort studies: this is a prospective study, when you take a group of people (cohort) who do not have the disease, but have risk factors. Then you watch them prospectively and see if they develop the disease. You then compare this relative to those who don't have the risk factor: relative risk. Case control: this is the opposite. This is a retrospective disease, where you get a group of people with the disease and look retrospectively to assess for risk factors. This study helps measure the odds ratio. Cross sectional studies: this looks at the prevalence of the disease in the present. The group is gathered regardless of exposure or disease. Some other study types include twin concordance study which looks at the genetic link between disease in twins. Another one is adoption study, which looks at nature vs nuture in children who are adopted to other families. Our next big category of studies are experimental studies. The best ways to conduct an experimental study is to randomize your groups, having a control group. The gold standard for experimental studies is called a randomized controlled trial for that reason. There are some subtypes of RCTS, including a crossover study where members from one group crossover to the other. Another one is a meta-analysis, which pools common RCT that increase the sample size and power. Last topic - the stages of an RCT. The first phase is to look at safety, the pharmacokinetics and pharmacodynamics, and side effects. The second phase is on efficacy. This is where most drugs fail. Phase three is whether or not the drug is better. Phase four deals with the longevity of the drug and to monitor it for long term side effects.
Views: 4541 LY Med
NCCMT - URE - Forest Plots - Understanding a Meta-Analysis in 5 Minutes or Less
 
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Knowing how to interpret an odds ratio (OR) allows you to quickly understand whether a public health intervention works and how big an effect it has. For example, how effective is the flu vaccine in preventing people from getting the flu? Using hypothetical data, How to Calculate an Odds Ratio shows how an OR helps determine, on average, how many people who got the flu shot came down with the flu, versus the number of people who did not get the flu shot. The video explains how to calculate and interpret an OR, and decide whether it indicates a positive or negative outcome. An OR of “1” would mean that the flu shot made no difference. So, if the outcome is something we were trying to increase, such as getting the flu shot in the first place, a positive outcome would be indicated by an OR of greater than 1. But, if the intervention is intended to decrease something, such as getting sick with the flu, an OR of less than 1 would show a positive outcome. The National Collaborating Centre for Methods and Tools is funded by the Public Health Agency of Canada and affiliated with McMaster University. The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada. NCCMT is one of six National Collaborating Centres (NCCs) for Public Health. The Centres promote and improve the use of scientific research and other knowledge to strengthen public health practices and policies in Canada.
Views: 13157 The NCCMT
Systematic Reviews and Meta-Analyses - How to go through Validity Criteria
 
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In this video, I go over the validity criteria for systematic reviews.
Views: 1752 Tara Bishop MD
Statistical methods for updating meta-analyses: presentation
 
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This video is a presentation delivered by Dr Mark Simmonds from Centre for Reviews and Dissemination, University of York, UK, during a Cochrane Learning Live webinar organized by the Cochrane Statistical Methods Group, with the support from Cochrane Learning & Support Department. Systematic reviews and meta-analyses generally require updating as new studies become available; this requires multiple, repeated meta-analyses. This increases the risk of attaining spurious statistical significance in each analysis. As updating of meta-analyses becomes both more common and more frequent there is an increasing risk that meta-analysis results may be misinterpreted, particularly if readers are unaware of the updating process. In this presentation, Dr Mark Simmonds describes several methods to address this problem when meta-analyses are repeatedly updated, which have been assessed using a formal simulation study, and by applying methods to a range of recently-updated systematic reviews in the Cochrane Library.
Views: 216 Cochrane Training
Rare Cancer Meta-Analysis, pt.2.2: Setting up the meta-analysis and reviewing genes
 
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This entry is part two in a series of instructional videos detailing a meta-analysis on 8 different human gene expression studies looking at papillary renal cell carcinoma (pRCC). In this installment, I give a demonstration on collecting gene expression data from a single disease using Illumina’s BaseSpace Correlation Engine. I also describe the types of biological information we can obtain from this type of meta-analysis, as well as go over exporting the results to other statistical and visual programs for further work. A link to the actual meta-analysis used in the video in can be obtained in Correlation Engine (must have existing account) by typing in your working domain name into the following URL: https://”your domain name”.ussc.informatics.illumina.com/c/search/adv.nb?ids=853951,14029,79477,152971,56285,14033,451948,153346,14031,153313,451963,14030,14032,451966,451954,451951,13771 Inspiration for this meta-analysis on papillary kidney cancer came from an upcoming ‘Hackathon’ in May (https://sv.ai/papillary-renal-cell-carcinoma/) that brings together researchers, engineers and computer scientists to try to tackle challenging problems in life sciences. This year they are focusing on papillary renal-cell carcinoma type 1 (p1RCC), a disease that accounts for between 15 to 20% of all kidney cancers. Little is known about the genetic basis of sporadic papillary renal-cell carcinoma, and no effective forms of therapy for advanced disease exist. The opinions expressed during this video are mine and may not represent the opinions of Illumina. Any uses of Illumina’s products described in this demonstration may be uses that have not been cleared or approved by the FDA or any other applicable regulatory body. I do not get direct compensation from Illumina for these videos, but do receive reimbursement for travel when I speak at Illumina-sponsored events. Please subscribe to this YouTube channel or sign up to my blog (www.bioinfosolutions.com/blog/) to receive notifications on when the next video in the series is posted. Special thanks goes out to the biotech companies Illumina (Correlation Engine and Cohort Analyzer), Partek Inc. (Partek Genomics Suite) and Elsevier (Pathway Studio) for donating their platforms and providing technical assistance for this bioinformatics series.
Views: 48 Michael Edwards
Epidemiology Study Types: Cohort and Case-Control
 
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What makes a cohort vs. a case-control study? Find out in this video.
Views: 139256 daf189
Infrastructure and Trade, A Meta-Analysis: Guney Celbis
 
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Speaker: http://bit.ly/1zqgbFZ Paper: http://bit.ly/1LeFeBD Low levels of infrastructure quality and quantity can create trade impediments through increased transport costs. Since the late 1990s an increasing number of trade studies have taken infrastructure into account. The purpose of the present paper is to quantify the importance of infrastructure for trade by means of meta-analysis and meta-regression techniques that synthesize various studies. The type of infrastructure that we focus on is mainly public infrastructure in transportation and communication. We examine the impact of infrastructure on trade by means of estimates obtained from 36 primary studies that yielded 542 infrastructure elasticities of trade. We explicitly take into account that infrastructure can be measured in various ways and that its impact depends on the location of the infrastructure. We estimate several meta-regression models that control for observed heterogeneity in terms of variation across different methodologies, infrastructure types, geographical areas and their economic features, model specifications, and publication characteristics. Additionally, random effects account for between-study unspecified heterogeneity, while publication bias is explicitly addressed by means of the Hedges model. After controlling for all these issues we find that a 1 percent increase in own infrastructure increases exports by about 0.6 percent and imports by about 0.3 percent. Such elasticities are generally larger for developing countries, land infrastructure, IV or panel data estimation, and macro-level analyses. They also depend on the inclusion or exclusion of various common covariates in trade regressions.
Views: 320 UNU MERIT
Fixed Effects and Random Effects Models
 
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2 main types of statistical models are used to combine studies in a meta-analysis. This video will give a very basic overview of the principles behind fixed and random effects models.
Views: 60864 Terry Shaneyfelt
Interpreting a forest plot of a meta-analysis
 
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This video explains how to interpret data presented in a forest plot. Described by David Slawson, MD, Professor, University of Virginia. From the Making Decisions Better: The Information Mastery Curriculum and Assessment Program, an evidence-based medicine teaching program from Clinical Information Sciences, http://ClinicalInformationSciences.com.
People's Astonishing Proclivity to Succumb to Group Pressure  (THE SAAD TRUTH_65)
 
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I describe Solomon Asch's classic experiment from the 1950s. Would you have conformed if faced with the same situation? Meta-analysis of Asch-type studies (from 1996): http://www3.nd.edu/~wcarbona/Bond-Smith-Asch-meta-analysis.pdf Support this channel via Patreon: https://www.patreon.com/GadSaad Like my Facebook page: https://www.facebook.com/Dr.Gad.Saad Follow me on Twitter: https://twitter.com/GadSaad (@GadSaad) Psychology Today Blog: http://www.psychologytoday.com/experts/gad-saad-phd Personal Website: http://jmsb.concordia.ca/~GadSaad/ University Website: http://www.concordia.ca/jmsb/faculty/gad-saad.html Source for Thumbnail: http://bit.ly/1KC5IMf (not sure if the scale depicted in this image corresponds to any of the actual stimuli used by Asch but my objective here is to highlight the task)
Views: 4745 Gad Saad
Professor Leifert Explains Weighted vs Non-Weighted Meta-Analysis
 
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Prof Carlo Leifert of Newcastle University explains the two types of meta-analysis contributing to the quality of organic food study (http://research.ncl.ac.uk/nefg/QOF/page.php?page=1). This question and answer session was a component of the Nafferton Ecological Farming Group's Potato Party held on 15th November 2014.
Combining randomized and non-randomized evidence in network meta-analysis Georgia Salanti
 
13:47
Observational studies convey valuable information about the effectiveness of interventions in real-life clinical practice and there is a growing interest for methods to include non-randomized evidence in the decision-making process. We then present three alternative methods that allow the inclusion of observational studies in an NMA of RCTs: the design-adjusted synthesis, the use of observational evidence as prior information and the use of three-level hierarchical models.
Views: 1686 Georgia Salanti
Research Design
 
18:21
▼SUBSCRIBE To My Channel For More Research Videos▼ https://goo.gl/8f64I9 Types of research 0:12 - 2:17 Research designs 2:18 - 7:18 Data collection instruments 7:20 - 12:38 Sampling 13:26 - 18:00 To cite this video (APA): Zhang, R. (2016). Video summary on research types, research designs, data collection instruments, and sampling. [Video File]. Retrieved from https://youtu.be/WY9j_t570LY My other research videos: Zhang, R. (2017). When to use a qualitative research design? 4 things to consider. [Video File]. Retrieved from https://youtu.be/4FJPNStnTvA Zhang, R. (2017). What is a good Central Research Question? [Video File]. Retrieved from https://youtu.be/I4MfCDy7wDw Zhang, R. (2017). Research aim, research objective, research question, and investigative question. [Video File]. Retrieved from https://youtu.be/ujKIM59hy9I Please LIKE this video if you enjoyed it. Otherwise, there is a thumb-down button, too... :P ▼MY SOCIAL MEDIA PAGES▼ https://www.facebook.com/ranywayz https://nl.linkedin.com/in/ranywayz https://www.twitter.com/ranywayz #ResearchDesign #Thesis #RanywayzRandom
Views: 94531 RanYwayZ
Meta-Analysis in Statistics
 
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www.doctorpaul.org
Views: 8093 USMLEVideoLectures
Observational Studies
 
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Prepare for your USMLE/COMLEX exams with MedImmersion! Our goal is to help you quickly review the highest-yield material in as little time as possible. We love working with students. Leave us some feedback and we'll do our best to get back to you. GOOD LUCK IN SCHOOL!!
Views: 9877 Med Immersion
NCCMT - URE - Types of Reviews - What kind of review do we need
 
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Do you know when to use different types of reviews in public health decision making? Do you know the differences between a literature review, a systematic review, and a meta-analysis? Using an imaginary campaign to promote of healthy eating among adolescents as an example, this video describes how these reviews are created. You will see why combining findings from studies gives you a more accurate and generalizable understanding of what to expect from an intervention. Systematic reviews combine relevant research studies in a systematic way to answer a specific research question with minimal bias. They tell you whether or not an intervention is effective. Meta-analyses are similar to systematic reviews, but go one step further: they provide a numerical summary of the combined findings. In addition to whether or not an intervention works, meta-analyses can tell you the size of the intervention effect. Literature reviews, on the other hand, summarize multiple studies without using a systematic process for identifying, including, or combining studies. This type of review can lead to biases in the summary. Different types of reviews can affect how much confidence you can have in the findings. There can be thousands of single studies that each look at small portions of the population. Systematic reviews and meta-analyses can provide information based on all available studies making them powerful aids for evidence-informed decision making in public health. The National Collaborating Centre for Methods and Tools is funded by the Public Health Agency of Canada and affiliated with McMaster University. The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada. NCCMT is one of six National Collaborating Centres (NCCs) for Public Health. The Centres promote and improve the use of scientific research and other knowledge to strengthen public health practices and policies in Canada.
Views: 4862 The NCCMT
Manger un oeuf par jour est-il dangereux ?
 
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Analyse complète de la littérature sur le risque de maladies cardiovasculaires et de devenir diabétique avec une consommation régulière d'oeuf ! L'article est ici : http://www.dur-a-avaler.com/un-oeuf-par-jour-donne-t-il-diabete-et-maladies-cardiovasculaires Attention, dans la vidéo, quand je dis d'accompagner son omelette de "pain, riz ou patate douce", bien sûr, ils doivent être complet (hors patate douce) et ne représenter qu'1/4 de votre assiette ! Ne me fait pas dire ce que je n'ai pas dit ! La moitié de votre assiette doit être composée de végétaux, de légumes ! Voilà le message ! Les références sont là : Richard, C., C et al. (2017). Impact of egg consumption on cardiovascular risk factors in individuals with type 2 diabetes and at risk for developing diabetes: A systematic review of randomized nutritional intervention studies. Canadian journal of diabetes, 41(4), 453-463. Rong, Y., et al. (2013). Egg consumption and risk of coronary heart disease and stroke: dose-response meta-analysis of prospective cohort studies. Bmj, 346, e8539. Shin, J. Y., et al. (2013). Egg consumption in relation to risk of cardiovascular disease and diabetes: a systematic review and meta-analysis–. The American journal of clinical nutrition, 98(1), 146-159. Fuller, N. R., et al. (2015). The effect of a high-egg diet on cardiovascular risk factors in people with type 2 diabetes: the Diabetes and Egg (DIABEGG) study—a 3-mo randomized controlled trial–. The American journal of clinical nutrition, 101(4), 705-713. Li, Y., et al. (2013). Egg consumption and risk of cardiovascular diseases and diabetes: a meta-analysis. Atherosclerosis, 229(2), 524-530. Djoussé, L., et al. (2016). Egg consumption and risk of type 2 diabetes: a meta-analysis of prospective studies. The American journal of clinical nutrition, 103(2), 474-480. Larsson, S. C., et al. (2015). Egg consumption and risk of heart failure, myocardial infarction, and stroke: results from 2 prospective cohorts–3. The American journal of clinical nutrition, 102(5), 1007-1013. Xu, L., et al. (2018). Egg consumption and the risk of cardiovascular disease and all-cause mortality: Guangzhou Biobank Cohort Study and meta-analyses. European journal of nutrition, 1-12. Zamora-Ros, R., et al. (2018). Moderate egg consumption and all-cause and specific-cause mortality in the Spanish European Prospective into Cancer and Nutrition (EPIC-Spain) study. European journal of nutrition, 1-8. Jang, J., et al. (2018). Longitudinal association between egg consumption and the risk of cardiovascular disease: interaction with type 2 diabetes mellitus. Nutrition & diabetes, 8. Farvid, M. S., et al. (2017). Dietary protein sources and all-cause and cause-specific mortality: The golestan cohort study in Iran. American journal of preventive medicine, 52(2), 237-248. Díez-Espino, J., et al. (2017). Egg consumption and cardiovascular disease according to diabetic status: The PREDIMED study. Clinical Nutrition, 36(4), 1015-1021. Virtanen, J. K., et al. (2015). Egg consumption and risk of incident type 2 diabetes in men: the Kuopio Ischaemic Heart Disease Risk Factor Study–. The American journal of clinical nutrition, 101(5), 1088-1096. Tamez, M., V et al. (2016). Egg consumption and risk of incident type 2 diabetes: a dose–response meta-analysis of prospective cohort studies. British Journal of Nutrition, 115(12), 2212-2218. Djoussé, L., Petrone, A. B., Hickson, D. A., Talegawkar, S. A., Dubbert, P. M., Taylor, H., & Tucker, K. L. (2016). Egg consumption and risk of type 2 diabetes among African Americans: The Jackson Heart Study. Clinical nutrition, 35(3), 679-684. Kurotani, K., Nanri, A., Goto, A., Mizoue, T., Noda, M., Oba, S., … & Japan Public Health Center-based Prospective Study Group. (2014). Cholesterol and egg intakes and the risk of type 2 diabetes: The Japan Public Health Center-based Prospective Study. British Journal of Nutrition, 112(10), 1636-1643.
Views: 324 Jérémy Anso
BRAG - Methods for meta-analysis research
 
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Jaime Peters speaks about methods for meta-analysis research
Views: 2751 BRAGgroup
Confidence in Network Meta-Analysis: How to evaluate study limitations (theory)
 
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Aim: This video explains how to evaluate the impact of study limitations (risk of bias) in the results of network meta-analysis. Details: There is a need to evaluate the credibility of network meta-analysis evidence in a systematic way. We previously developed a framework (CINeMA; Confidence in Network Meta-analysis) to judge the confidence that can be placed in results obtained from a network meta-analysis by adapting and extending the GRADE domains (study limitations, inconsistency, indirectness, imprecision and publication bias). The system is transparent and applicable to any network structure. We are develop a user-friendly web application (called CINeMA) to simplify and speed-up the process. These videos have been prepared by Adriani Nikolakopoulou, Theodore Papakonstantinou and Georgia Salanti
Views: 402 Georgia Salanti
How to deal with heterogeneity
 
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This lecture is part of the Systematic Reviews course that teaches undergraduate students, PhD students and researchers how to build a systematic review or meta-analysis. Don’t hesitate to contact me for help with your review, to conduct a systematic review or meta-analysis or to organise a course on your location. Enjoy the course! Maurice Zeegers (www.systematicreviews.nl)
Views: 274 Maurice Zeegers
What is Heterogeneity?
 
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Systematic reviewers have to decide whather or not studies are homogeneous enough to combine. This video will describe what heterogeneity is and some of the tests used to investigate it.
Views: 79567 Terry Shaneyfelt
Meta-analysis Meaning
 
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Video shows what meta-analysis means. Any systematic procedure for statistically combining the results of many different studies.. An analysis resulting from combining the results of diverse statistical studies.. An analysis performed at a higher level of abstraction than that of basic analysis.. Meta-analysis Meaning. How to pronounce, definition audio dictionary. How to say meta-analysis. Powered by MaryTTS, Wiktionary
Views: 788 SDictionary
KETO DIET GOES WRONG - Doctors Reveal
 
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20 doctors talk about their experience with the low carb ketogenic diet. PBN INSIDERS: https://plantbasednews.org/insiders In association with: https://plantricianproject.org/ https://www.bluehorizon.com/ https://switch4good.org/ https://www.plantbasedhealthprofessionals.com/ https://www.pcrm.org/ https://nutritionstudies.org https://wellnessforumhealth.com/ The introduction was taken from PlantPure Nation: https://www.youtube.com/watch?v=A_i_vp9Vfho REFERENCES: 1. De Biase SG, Fernandes SFC, Gianini RJ, Duarte JLG. Vegetarian diet and cholesterol and triglycerides levels. Arq Bras Cardiol. 2007 Jan;88(1):35–9. 2. Saslow LR, Mason AE, Kim S, Goldman V, Ploutz-Snyder R, Bayandorian H, et al. An Online Intervention Comparing a Very Low-Carbohydrate Ketogenic Diet and Lifestyle Recommendations Versus a Plate Method Diet in Overweight Individuals With Type 2 Diabetes: A Randomized Controlled Trial. J Med Internet Res. 2017 Feb 13;19(2):e36. 3. Tay J, Luscombe-Marsh ND, Thompson CH, Noakes M, Buckley JD, Wittert GA, et al. Comparison of low- and high-carbohydrate diets for type 2 diabetes management: a randomized trial. Am J Clin Nutr. 2015 Oct;102(4):780–90. 4. Dr. Bernstein’s Diabetes Solution, low carbohydrate diet, control blood sugars [Internet]. Dr. Bernstein’s Diabetes Solution. A Complete Guide to Achieving Normal Blood Sugars. Official Web Site. [cited 2016 Mar 5]. Available from: http://www.diabetes-book.com/ 5. Hu T, Mills KT, Yao L, Demanelis K, Eloustaz M, Yancy WS, et al. Effects of Low-Carbohydrate Diets Versus Low-Fat Diets on Metabolic Risk Factors: A Meta-Analysis of Randomized Controlled Clinical Trials. Am J Epidemiol. 2012 Oct 1;176(Suppl 7):S44–54. 6. de Bock M, Lobley K, Anderson D, Davis E, Donaghue K, Pappas M, et al. Endocrine and metabolic consequences due to restrictive carbohydrate diets in children with type 1 diabetes: An illustrative case series. Pediatr Diabetes. 2017 Apr 11; 7. Noakes TD, Windt J. Evidence that supports the prescription of low-carbohydrate high-fat diets: a narrative review. Br J Sports Med. 2017 Jan;51(2):133–9. 8. Noto H, Goto A, Tsujimoto T, Noda M. Low-Carbohydrate Diets and All-Cause Mortality: A Systematic Review and Meta-Analysis of Observational Studies. PLoS ONE [Internet]. 2013 Jan 25 [cited 2014 May 9];8(1). Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3555979/ 9. Ranjan A, Schmidt S, Damm-Frydenberg C, Holst J, Madsbad S, Nørgaard K. Short-term Effects of Low Carbohydrate Diet on Glycaemic Parameters and Cardiovascular Risk Markers in Patients with Type 1 Diabetes - A Randomised Open-label Cross-over Trial. Diabetes Obes Metab. 2017 Mar 27; 10. Snorgaard O, Poulsen GM, Andersen HK, Astrup A. Systematic review and meta-analysis of dietary carbohydrate restriction in patients with type 2 diabetes. BMJ Open Diabetes Res Care. 2017;5(1):e000354. 11. Hegsted DM, McGandy RB, Myers ML, Stare FJ. Quantitative effects of dietary fat on serum cholesterol in man. Am J Clin Nutr. 1965 Nov;17(5):281–95. 12. Grundy SM, Barrett-Connor E, Rudel LL, Miettinen T, Spector AA. Workshop on the impact of dietary cholesterol on plasma lipoproteins and atherogenesis. Arterioscler Thromb Vasc Biol. 1988 Jan 1;8(1):95–101. 13. Hopkins PN. Effects of dietary cholesterol on serum cholesterol: a meta-analysis and review. Am J Clin Nutr. 1992 Jun 1;55(6):1060–70. 14. Ference BA, Mahajan N. The Role of Early LDL Lowering to Prevent the Onset of Atherosclerotic Disease. Curr Atheroscler Rep. 2013 Apr 1;15(4):312. 15. Kahn HA, Phillips RL, Snowdon DA, Choi W. Association between reported diet and all-cause mortality. Twenty-one-year follow-up on 27,530 adult Seventh-Day Adventists. Am J Epidemiol. 1984 May;119(5):775–87. 16. Orlich MJ, Singh PN, Sabaté J, Jaceldo-Siegl K, Fan J, Knutsen S, et al. Vegetarian Dietary Patterns and Mortality in Adventist Health Study 2. JAMA Intern Med. 2013 Jul 8;173(13):1230–8. 17. Levine ME, Suarez JA, Brandhorst S, Balasubramanian P, Cheng C-W, Madia F, et al. Low protein intake is associated with a major reduction in IGF-1, cancer, and overall mortality in the 65 and younger but not older population. Cell Metab. 2014 Mar 4;19(3):407–17. 18. Song M, Fung TT, Hu FB, Willett WC, Longo VD, Chan AT, et al. Association of Animal and Plant Protein Intake With All-Cause and Cause-Specific Mortality. JAMA Intern Med. 2016 Aug 1; 19. Rohrmann S, Overvad K, Bueno-de-Mesquita HB, Jakobsen MU, Egeberg R, Tjønneland A, et al. Meat consumption and mortality--results from the European Prospective Investigation into Cancer and Nutrition. 20. Djoussé L, Gaziano JM. Egg consumption in relation to cardiovascular disease and mortality: the Physicians’ Health Study. 21. Fung TT, van Dam RM, Hankinson SE, Stampfer M, Willett WC, Hu FB. Low-carbohydrate diets and all-cause and cause-specific mortality: Two cohort Studies.
Views: 80082 PLANT BASED NEWS
Siri-Tarino's Meta-Analysis, Part 1 (Saturated Fat and Heart Disease)
 
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Dr. Patty Siri-Tarino was the lead author of a meta-analysis of prospective cohort studies investigating the relationship between saturated fat and cardiovascular disease. Her conclusion that "there is no significant evidence for concluding that dietary saturated fat is associated with an increased risk" of cardiovascular disease has been frequently cited as evidence of the benign nature of saturated fat. Her paper receives a critical assessment in these two videos.
Views: 6126 Plant Positive
The MRC Clinical Trials Unit: What is the MRC CTU and what does it do?
 
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The MRC Clinical Trials Unit is a centre of excellence for clinical trials, meta-analysis and epidemiological studies. This film explores the type of work the MRC CTU does, and what sets it apart from other trials units.

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