Sentences with phrase «large statistical studies»

Not exact matches

Finally, was the study's sample size large enough to have statistical significance?

The strengths of the study include the ability to compare outcomes by the woman's planned place of birth at the start of care in labour, the high participation of midwifery units and trusts in England, the large sample size and statistical power to detect clinically important differences in adverse perinatal outcomes, the minimisation of selection bias through achievement of a high response rate and absence of self selection bias due to non-consent, the ability to compare groups that were similar in terms of identified clinical risk (according to current clinical guidelines) and to further increase the comparability of the groups by conducting an additional analysis restricted to women with no complicating conditions identified at the start of care in labour, and the ability to control for several important potential confounders.

However, individual studies have been modest in size and lacking in statistical power to exclude even quite large effects on diabetes risk.

Using statistical tests, Kamangar combined the results from studies in the U.S., Europe, Iran, China and Japan to evaluate if H. pylori helps prevent either form of esophageal cancer in such a large and geographically diverse sample pool.

The new method will be invaluable for statistical studies of large numbers of galaxies, says Laura Ferrarese of Rutgers University in Piscataway, New Jersey, co-discoverer of the velocity dispersion correlation.

In what is considered the largest statistical review of published computerized concussion testing to date, covering 37 studies and 3,960 participants all within the first week of sustaining a concussion, he and his co-authors — who include Pitt's Dr. Kontos — produced two key findings:

Although several small studies have found similar results, this large study of almost 800,000 babies and mothers expands the evidence by using a statistical method that also accounts for unmeasured or unobserved factors.

«This is a very large scale study using a new, innovative statistical method,» said study co-senior author Kenneth S. Kendler, M.D., professor of psychiatry, and human and molecular genetics in the Virginia Commonwealth University School of Medicine, and an internationally recognized psychiatric geneticist.

This work highlights the importance of appropriate statistical analyses of the large quantitative data sets that are increasingly being produced by experimentalists and are being used to study fundamental cellular mechanisms.

By studying the statistical distribution of larger and smaller swirls on the sky, they may be able to piece together a detailed picture of the energy and density distribution in the primordial universe.

Biologists have to undertake large studies that can guarantee the statistical significance of observations, and they need self - critical analysis to avoid inadvertent biases.

The second tool, SuperExactTest, establishes the very first theoretical framework for assessing the statistical significance of multi-set intersections and enables users to compare very large sets of data, such as gene sets produced from genome - wide association studies (GWAS) and differential expression analysis.

Because the meta - analysis comprises a much larger sample size than any individual study, it provides greater statistical certainty in conclusions.

Researchers compensate for the lack of control by using large sample sizes — some vitamin D studies track 50,000 people — and applying statistical techniques.

In the study fetal size was expressed as a z score, which is a statistical method of expressing difference from normal; four z scores covers the range from abnormally small to abnormally large.

The scientists then used statistical models to evaluate the distribution of cancer - linked DNA in the patients» blood samples over the seven - year study to find the largest degree of differences between patients with low and high levels of evidence of hypermethylation in their DNA.

Today, analyzing and editing genomes, proteomes and metabolomes has become a standard for many model systems; imaging beyond the diffraction limit of light and new technologies for studying protein structures provide insights deeper than ever before; the characterization of large populations of cells or organisms brings unprecedented statistical power; and studying nearly all organisms of an ecosystems as a whole allows generating comprehensive models.

Although the study had a large sample size, the number of exposed ASD cases was not large enough to provide a stable statistical estimate of the trimester - specific HR associated with influenza infection.

CSGB scientists conduct studies aimed at understanding complex genetic diseases and developing new statistical methods and software to analyze data sets emanating from large - scale genetic association and linkage studies.

Scientists in the Statistical Genetics Section capitalize on these opportunities by actively developing new statistical methods and software to analyze data sets emanating from large - scale genetStatistical Genetics Section capitalize on these opportunities by actively developing new statistical methods and software to analyze data sets emanating from large - scale genetstatistical methods and software to analyze data sets emanating from large - scale genetic studies.

The correlation of B12 deficiency with hyperhomocysteinemia could well reach statistical significance if a larger group of subjects were studied.»

The team says their paper, «What Happens After You Both Swipe Right: A Statistical Description of Mobile Dating Communications» is one of the first large scale quantitative studies to look at the way mobile dating sites are used.

As a national study, providing information at a high level of statistical precision about various subgroups (defined by characteristics such as race / ethnicity, sex, disability status, school type such as private versus public school, etc.), MGLS: 2017 is a large undertaking.

The Center's staff has extensive experience in statistical analyses and data management, qualitative research methods, randomized controlled trials and quasi-experimental studies, and large - scale surveys.

You should be especially careful about large statistical analyses, which combine data from many different studies or sources, because the data is unlikely to be consistent.

I did a statistical analysis of shelters a few months ago which showed that a high live release rate does not correlate with a smaller community size — in fact, if anything, the study showed that a high live release rate is more likely in larger communities.

Moreover, it's not even clear that the deviation has been as large as is commonly assumed (as discussed e.g. in the Cowtan and Way study earlier this year), and has little statistical significance in any case.

This sort of statistical test is the basis for a large proportion of scientific studies and is understandable and reasonable.

The IPCC range, on the other hand, encompasses the overall uncertainty across a very large number of studies, using different methods all with their own potential biases and problems (e.g., resulting from biases in proxy data used as constraints on past temperature changes, etc.) There is a number of single studies on climate sensitivity that have statistical uncertainties as small as Cox et al., yet different best estimates — some higher than the classic 3 °C, some lower.

So: The study finds a fingerprint of anthropogenic influences on large scale increase in precipitation extremes, with remaining uncertainties — namely that there is still a possibility that the widespread increase in heavy precipitation could be due to an unusual event of natural variability.The intensification of extreme rainfall is expected with warming, and there is a clear physical mechanism for it, but it is never possible to completely separate a signal of external forcing from climate variability — the separation will always be statistical in nature.

The cultural worldview scales are continuous, and should be used as continuous variables when testing study hypotheses, both to maximize statistical power and to avoid spurious findings of differences that can occur when one arbitrarily divides a larger data set into smaller parts in relation to a continuous variable.

Makowski, D., S. Asseng, F. Ewert, S. Bassu, J.L. Durand, P. Martre, M. Adam, P.K. Aggarwal, C. Angulo, C. Baron, B. Basso, P. Bertuzzi, C. Biernath, H. Boogaard, K.J. Boote, N. Brisson, D. Cammarano, A.J. Challinor, J.G. Conijn, M. Corbeels, D. Deryng, G. De Sanctis, J. Doltra, S. Gayler, R. Goldberg, P. Grassini, J.L. Hatfield, L. Heng, S.B. Hoek, J. Hooker, L.A. Hunt, J. Ingwersen, C. Izaurralde, R.E.E. Jongschaap, J.W. Jones, R.A. Kemanian, K.C. Kersebaum, S.H. Kim, J. Lizaso, C. Müller, S. Naresh Kumar, C. Nendel, G.J. O'Leary, J.E. Olesen, T.M. Osborne, T. Palosuo, M.V. Pravia, E. Priesack, D. Ripoche, C. Rosenzweig, A.C. Ruane, F. Sau, M.A. Semenov, I. Shcherbak, P. Steduto, C.O. Stöckle, P. Stratonovitch, T. Streck, I. Supit, F. Tao, E. Teixeira, P. Thorburn, D. Timlin, M. Travasso, R.P. Rötter, K. Waha, D. Wallach, J.W. White, J.R. Williams, and J. Wolf, 2015: Statistical analysis of large simulated yield datasets for studying climate effects.

While this method is useful to gain context specific insights into the effectiveness of climate policies, statistical studies based on large sample sizes allow analysts to control for various factors and yield generalizable results.

Up to then, the evidence had all be epidemiological, i.e., evidence based on large - scale statistical studies.

Even when some of the variables are aggregated or coded, from the perspective of a large statistical agency desiring to release data to the public, the study concluded that a population size of 500,000 was not sufficient to provide a reasonable guarantee that certain individuals could not be identified.

For example, some have found significant differences between children with divorced and continuously married parents even after controlling for personality traits such as depression and antisocial behavior in parents.59 Others have found higher rates of problems among children with single parents, using statistical methods that adjust for unmeasured variables that, in principle, should include parents» personality traits as well as many genetic influences.60 And a few studies have found that the link between parental divorce and children's problems is similar for adopted and biological children — a finding that can not be explained by genetic transmission.61 Another study, based on a large sample of twins, found that growing up in a single - parent family predicted depression in adulthood even with genetic resemblance controlled statistically.62 Although some degree of selection still may be operating, the weight of the evidence strongly suggests that growing up without two biological parents in the home increases children's risk of a variety of cognitive, emotional, and social problems.

CONCLUSIONS: In this large, population - based, longitudinal study, early - life SDB symptoms had strong, persistent statistical effects on subsequent behavior in childhood.

When young men cheat, for example, it is often not because of lost love, but because they struggle to deal with competing desires for recreational sex and monogamy.3 In a large meta - analysis (which is a statistical summary of the results of many research studies), men and women were similarly upset by emotional infidelity, more so than sexual infidelity.4 But what does infidelity really mean?

Decades of research has shown that men are more sexually aroused than women by erotic images, 1,2 which explains why a large meta - analysis (a study that summarizes the statistical findings from many different studies) found very strong evidence that men are more likely to use erotic materials such as magazines, videos and the Internet.3 Other researchers have found that how I interpreted the sext picture also matters.

Given the relatively small magnitude of the apparent effect size, if joint - custody and paternal custody children really do differ in adjustment, more studies with larger samples may be needed to detect the effect at the level of statistical significance.

The strength of this study is its large representative sample and the statistical approach to its results.

Research also needs to adequately control for covariates that may confound the effects of PAE, such as family processes (eg, problematic parenting or family conflict) and parental characteristics, especially maternal substance use.1, 12 Researchers also need to account for genetic liabilities that are shared by parents and offspring.13, 14 A woman's genetic risk of substance use could be passed down to her children and subsequently affect their behavior.15 Research on the consequences of PAE, therefore, needs studies with large samples, with sufficient statistical power to detect small effects, using analytical methods and designs that can account for potential confounds, including factors that are not measured.

C.M.G. conceptualized the study as a part of her postdoctoral work, conducted the literature review, coded autonomy support in 30 % of the sample for reliability testing, performed all statistical analyses, wrote and revised the manuscript; B.H. helped conceptualize the study as a part of her Master's work, coded autonomy support in the entire sample, and participated in the writing, editing and revising of the manuscript; D.M.S. participated in the conceptualization of the present study, helped with the writing in both the original and revised versions of the paper in her role as supervisor, supervised the data collection and conceptualized, designed and implemented the larger study of which the present study is only a part (the Concordia Longitudinal Risk Project); L.A.S. supervised the data collection and conceptualized, designed and implemented the larger study of which the present study is only a part.

This association lost statistical significance after adjusting for children's behavioural difficulties at age 1 1/2 years, but did not much change, which may be due to the small number of cases of hyperactivity / inattention in our study and calls for additional research in larger samples.